Category Theory Approach to Fusion of Wavelet-Based Features

Size: px
Start display at page:

Download "Category Theory Approach to Fusion of Wavelet-Based Features"

Transcription

1 Catgory Thory Approach to Fusion of Wavlt-Basd Faturs Scott A. DLoach Air Forc Institut of Tchnology Dpartmnt of Elctrical and Computr Enginring Wright-Pattrson AFB, Ohio Miczyslaw M. Kokar Northastrn Univrsity Dpartmnt of Elctrical and Computr Enginring Boston, Massachustts 02115k Abstract This papr discusss th application of catgory thory as a unifying concpt for formally dvlopd information fusion systms. Catgory thory is a mathmatically sound rprsntation tchniqu usd to captur th commonaltis and rlationships btwn objcts. This fatur maks catgory thory a vry lgant languag for dscribing information fusion systms and th information fusion procss itslf. Aftr an initial ovrviw of catgory thory, th papr invstigats th application of catgory thory to a wavlt basd multisnsor targt rcognition systm, th Automatic Multisnsor Fatur-basd Rcognition Systm (AMFRS), which was originally dvlopd using formal mthods. 1. Introduction Th goal of information fusion is to combin multipl pics of data in a way so that w can infr mor information than what is containd in th individual pics of data alon. This rquirs that w b abl to dtrmin how th individual pics of data ar rlatd. It would also b nic if w could dscrib this rlationship btwn data in a formal way so that w can automatically rason ovr th information fusion procss without th us of unrliabl and brittl huristics. In this papr w prsnt catgory thory as a unifying concpt for formally dfining information fusion systms. Th goal of catgory thory is to dfin th rlationships btwn objcts within a catgory of rlatd objcts. Catgory thory also provids oprators that allow us to rason ovr ths rlationships. Th first sction of th papr is a tutorial on algbraic spcifications and catgory thory. Nxt w dscrib a formally dfind fusion systm, th Automatic Multisnsor Fatur-basd Rcognition Systm (AMFRS), and dscrib how w could incorporat catgory thory constructs to provid a provably corrct tchniqu for implmnt th systm. 2. Thoris and Spcifications Th notation gnrally usd to captur th formal dfinitions of systms is a formal spcification. Thr ar two typs of formal spcifications commonly usd to dscrib th bhavior of softwar: oprational and dfinitional. An oprational spcification is a rcip for an implmntation that satisfis th rquirmnts whil a dfinitional spcification dscribs bhavior by listing th proprtis that an implmntation must posss. Dfinitional spcifications hav svral advantags ovr oprational spcifications. 1. Dfinitional spcifications ar gnrally shortr and clarr than oprational spcifications. 2. Dfinitional spcifications ar asir to modulariz and combin. 3. Dfinitional spcifications ar asir to rason about, which is th ky rason thy ar usd in automatd systms. It is gnrally rcognizd that crating corrct, undrstandabl formal spcifications is difficult, if not impossibl, without th us of som structuring tchniqu or mthodology. Algbraic thoris provid th advantags of dfinitional spcifications along with th dsird structuring tchniqus. Algbraic thoris ar dfind in trms of collctions of valus calld sorts, oprations dfind ovr th sorts, and axioms dfining th smantics of th sorts and oprations. Th structuring of algbraic thoris is providd by catgory thory oprations and provids an lgant way in which to combin smallr algbraic thoris into largr, mor complx thoris. Catgoris ar an abstract mathmatical construct consisting of catgory objcts and catgory arrows. In gnral, catgory objcts ar th objcts in th catgory of intrst whil catgory arrows dfin a mapping from th intrnal structur of on catgory Pag 1 of 9

2 objct to anothr. In our rsarch, th catgory objcts of intrst ar algbraic spcifications and th catgory arrows ar spcification morphisms. In this catgory, Spc, spcification morphisms map th sorts and oprations of on algbraic spcification into th sorts and oprations of a scond algbraic spcification such that th axioms in th first spcification bcom provabl thorms in th scond spcification. Thus, in ssnc, a spcification morphism dfins an mbdding of on spcification into a scond spcification Algbraic Spcification In this sction, w dfin th important aspcts of algbraic spcifications and how to combin thm using catgory thory oprations to crat nw, mor complx spcifications. As dscribd abov, catgory thory is an abstract mathmatical thory usd to dscrib th xtrnal structur of various mathmatical systms. Bfor showing its us in rlation to algbraic spcifications, w giv a formal dfinition [8]. Catgory. A catgory C is comprisd of a collction of things calld C-objcts; a collction of things calld C-arrows; oprations assigning to ach C-arrow f a C-objct dom f (th domain of f) and a C-objct cod f (th codomain of f). If a = dom f and b = cod f this is displayd as f f: a b or a b an opration,, calld composition, assigning to ach pair g, f of C-arrows with dom g = cod f, a C- arrow g f: dom f cod g, th composit of f and g such that th Associativ Law holds: Givn th configuration f g h a b c d of C-objcts and C-arrows, thn h (g f) = (h g) f. an assignmnt to ach C-objct, b, a C-arrow, id b: b b, calld th idntity arrow on b, such that th Idntity Law holds: For any C-arrows f: a b and g: b c id b f = f and g id b = g Th Catgory of Signaturs In algbraic spcifications, th structur of a spcification is dfind in trms of an abstract collction of valus, calld sorts and oprations ovr thos sorts. This structur is calld a signatur [9]. A signatur dscribs th structur that an implmntation must hav to satisfy th associatd spcification; howvr, a signatur dos not spcify th smantics of th spcification. Th smantics ar addd latr via axiomatic dfinitions. Signatur. A signatur Σ = S, Ω, consists of a st S of sorts and a st Ω of opration symbols dfind ovr S. Associatd with ach opration symbol is a squnc of sorts calld its rank. For xampl, f:s 1,s 2,...,s n s indicats that f is th nam of an n-ary function, taking argumnts of sorts s 1, s 2,, s n and producing a rsult of sort s. A nullary opration symbol, c: s, is calld a constant of sort s. An xampl of a signatur is shown in Figur 1. In th signatur RING thr is on sort, ANY, and fiv oprations dfind on th sort. signatur Ring is sorts ANY oprations plus : ANY ANY ANY tims : ANY ANY ANY inv : ANY ANY zro : ANY on : ANY nd Figur 1. Ring Signatur In our rsarch, signaturs dfin th rquird structur for formally dscribing wavlt-basd modls. Signaturs provid th ability to dfin th intrnal structur of a spcification; howvr, thy do not provid a mthod to rason about rlationships btwn spcifications. To crat a thory of information fusion using algbraic spcifications, oprations to dfin rlations btwn spcifications must b availabl. Thr must b a wll-dfind thory about how to rason about th xtrnal structur of ths spcifications (i.., how thy rlat to on anothr). As might b xpctd, signaturs (as th C-objcts ) with th corrct C-arrows form a catgory that is of grat intrst in our rsarch. For signaturs, th C- arrows ar calld signatur morphisms [9]. Signaturs and thir associatd signatur morphisms form th catgory, Sign. Signatur Morphism. Givn two signaturs Σ = S, Ω and Σ ' = S ', Ω ', a signatur morphism σ : Σ Σ ' is a pair of functions σ S : S S', σ Ω : Ω Ω ', mapping sorts to sorts and oprations to oprations such that th sort map is compatibl with th ranks of th oprations, i.., for all opration symbols f:s 1,s 2,...,s n s in Ω, th opration symbol σ Ω (f):σ S (s 1 ), σ S (s 2 ),...,σ S (s n ) σ S (s) is in Ω'. Th composition of two signatur morphisms, obtaind by Pag 2 of 9

3 composing th functions comprising th signatur morphisms, is also a signatur morphism. Th idntity signatur morphism on a signatur maps ach sort and ach opration onto itslf. Signaturs and signatur morphisms form a catgory, Sign, whr th signaturs ar th C-objcts and th signatur morphisms ar th C- arrows. Givn th signaturs RING from Figur 1 and RINGINT from Figur 2, a signatur morphism σ : RING RINGINT, is shown in Figur 3. As rquird by th dfinition of a signatur morphism, σ consists of two functions, σ S and σ Ω as shown. σ S maps th sort ANY to Intgr whil σ Ω maps ach opration to an opration with a compatibl rank. Spc RingInt is sorts Intgr oprations + : Intgr Intgr Intgr : Intgr Intgr Intgr - : Intgr Intgr 0 : Intgr 1 : Intgr nd Figur 2. Intgr Ring Signatur σ S = {ANY Intgr} σ Ω = {plus +, tims, inv -, zro 0, on 1} Figur 3. Signatur Morphism Signatur morphisms map sorts and oprations from on signatur into anothr and allow th rstriction of sorts as wll as th rstriction of th domain and rang of oprations. Howvr, to build up mor complx signaturs, introduction of nw sorts and oprations into a signatur is rquird. This is accomplishd via a signatur xtnsion [1]. Extnsion. A signatur Σ 2 = S 2, Ω 2 xtnds a signatur Σ 1 = S 1, Ω 1 if S 1 S 2 and Ω 1 Ω 2. Signatur xtnsions allow th dfinition of ntirly nw signaturs and th growth of complx signaturs from xisting signaturs Th Catgory of Spcifications To modl smantics, signaturs ar xtndd with axioms that dfin th intndd smantics of th signatur oprations. A signatur with associatd axioms is calld a spcification [9]. Spcification. A spcification SP is a pair Σ, Φ consisting of a signatur Σ = S, Ω and a collction Φ of Σ-sntncs (axioms). Although a spcification includs smantics, it dos not implmnt a program nor dos it dfin an implmntation. A spcification only dfins th smantics rquird of a valid implmntation. In fact, for most spcifications, thr ar a numbr of implmntations that satisfy th spcification. Implmntations that satisfy all axioms of a spcification ar calld modls of th spcification [9]. To formally dfin a modl, w first dfin a Σ- algbra [9]. Σ-algbra or Σ-modl. Givn a signatur Σ = S, Ω, a Σ- algbra A = A S, F A consists of two familis: a collction of sts, calld th carrirs of th algbra, A S = {A s s S}; and a collction of total functions, F A = {f A f Ω} such that if th rank of f is s 1,s 2,..., s n s, thn f A is a function from A s1 A s2 A sn to A s. (Th symbol indicats th Cartsian product of sts hr.) Modl. A modl of a spcification SP = Σ, Φ is a Σ- algbra, M, such that M satisfis ach Σ-sntnc (axiom) in Φ. Th collction of all such modls M is dnotd by Mod[SP]. Th sub-catgory of Mod(Σ) inducd by Mod[SP] is also dnotd by Mod[SP]. An xampl of a spcification is shown in Figur 4. This spcification is th original RING signatur of Figur 1 nhancd with th axioms that dfin th smantics of th oprations. Valid modls of this spcification includ th st of all intgrs, Z, with addition and multiplication as wll as th st of intgrs modulo 2, Z 2 = {0, 1}, with th invrs opration (-) dfind to b th idntity opration. As signaturs hav signatur morphisms, spcifications also hav spcification morphisms. Spcification morphisms ar signatur morphisms that nsur that th axioms in th sourc spcification ar thorms (ar provabl from th axioms) in th targt spcification. Showing that th axioms of th sourc spcification ar thorms in th targt spcification is a proof obligation that must b shown for ach spcification morphism. Spcifications and spcification morphisms nabl th cration and modification of spcifications that corrspond to valid signaturs within th catgory Sign. Howvr, bfor w can formally dfin a spcification morphism, w must first dfin a rduct [9]. Pag 3 of 9

4 spc Ring is sorts ANY oprations As dfind in Figur 2 axioms a,b,c ANY a plus (b plus c) = (a plus b) plus c a plus b = b plus a a plus zro = a a plus(inv a) = zro a tims (b tims c) = (a tims b) tims c a tims on = a on tims a = a a tims (b plus c) = (a tims b) plus (a tims c) (a plus b) tims c = (a tims c) plus (b tims c) nd Figur 4. Ring Spcification Rduct. Givn a signatur morphism σ:σ Σ ' and a Σ '- algbra A', th σ-rduct of A', dnotd A' σ, is th Σ- algbra A = A S, F A dfind as follows (with Σ = S, Ω ): A S = A σ(s) ' for s S, and f A = (σ(f)) A', for f Ω A rduct dfins a nw Σ-algbra (or Σ-modl) from an xisting Σ'-algbra. It accomplishs this by slcting a st or functions for ach sort or opration in Σ basd on th signatur morphism from Σ to Σ '. Thus if w hav a signatur, Σ ', and a Σ '-modl, w can crat a Σ-modl for a scond signatur, Σ, by dfining a signatur morphism btwn thm and taking th rduct basd on that signatur morphism. A rduct is now usd to xtnd th concpt of a signatur morphism to form a spcification morphism [9]. Spcification Morphism. A spcification morphism from a spcification SP = Σ, Φ to a spcification SP' = Σ ', Φ' is a signatur morphism σ: Σ Σ ' such that for vry modl M Mod[SP'], M σ Mod[SP]. Th spcification morphism is also dnotd by th sam symbol, σ: Σ Σ '. W now turn to th dfinition of thoris and thory prsntations. Basically a thory is th st of all thorms that logically follow from a givn st of axioms [8]. A thory prsntation is a spcification whos axioms ar sufficint to prov all th thorms in a dsird thory but nothing mor. Put succinctly, a thory prsntation is a finit rprsntation of a possibly infinit thory. To formally dfin a thory and thory prsntation w must first dfin logical consqunc and closur [8]. Logical Consqunc. Givn a signatur Σ, a Σ-sntnc ϕ is said to b a logical consqunc of th Σ-sntncs ϕ 1,...,ϕ n, writtn ϕ 1,...,ϕ n = ϕ, if ach Σ-algbra that satisfis th sntncs ϕ 1,...,ϕ n also satisfis ϕ. Closur, Closd. Givn a signatur Σ, th closur, closur(φ), of a st of Σ-sntncs Φ is th st of all Σ- sntncs which ar th logical consqunc of Φ, i.., closur(φ) = {ϕ Φ = ϕ}. A st of Σ-sntncs Φ is said to b closd if and only if Φ = closur(φ). Thory, prsntation. A thory s a pair Σ, closur(φ) consisting of a signatur Σ and a closd st of Σ-sntncs, closur(φ). A spcification Σ, Φ is said to b a prsntation for a thory Σ, closur(φ). A modl of a thory is dfind just as for spcifications; th collction of all modls of a thory s dnotd Mod[T]. Thory morphisms ar dfind analogous to spcification morphisms. Spcification morphisms complt th basic tool st rquird for dfining and rfining spcifications. This tool st can now b xtndd to allow th combination, or composition, of xisting spcifications to crat nw spcifications. This is whr catgory thory is xtrmly usful in information fusion. Oftn two spcifications that wr originally xtnsions from th sam ancstor nd to b combind. Thrfor, th dsird combind spcification consists of th uniqu parts of two spcifications and som shard part that is common to both spcifications (th part dfind in th shard ancstor spcification). This combining opration is calld a colimit [8]. Th colimit opration crats a nw spcification from a st of xisting spcifications. This nw spcification has all th sorts and oprations of th original st of spcifications without duplicating th shard sorts and oprators. To formally dfin a colimit, w must first dfin a con (or cocon) [8]. Con. Givn a diagram D in a catgory C and a C-objct c, a con from th bas D to th vrtx c is a collction of C- arrows {f i : d i c d i D}, on for ach objct d i in th diagram D, such that for any arrow g: d i d j in D, th diagram shown in Figur 5 commuts i.., g f j = f i. Colimit. A colimit for a diagram D in a catgory C is a C- objct c along with a con {f i : d i c d i D} from D to c such that for any othr con {f i ': d i c' d i D} from D to a vrtx c', thr is a uniqu C-arrow f: c c' such that for vry objct d i in D, th diagram shown in Figur 6 commuts (i.., f f i = f i '). Pag 4 of 9

5 d i f i g c Figur 5. Con Diagram f i d i f c c f j f i Figur 6. Colimit Diagram Concptually, th colimit of a st of spcifications is th shard union of thos spcifications basd on th morphisms btwn th spcifications. Ths morphisms dfin quivalnc classs of sorts and oprations. For xampl, if a morphism for spcification A to spcification B maps sort α to sort β, thn α and β ar in th sam quivalnc class and thus is a singl sort in th colimit spcification of A, B, and th morphism btwn thm. Thrfor, th colimit opration crats a nw spcification, th colimit spcification, and a con morphism from ach spcification to th colimit spcification. Ths con morphisms satisfy th condition that th translation of any sort or opration along any of th morphisms in th diagram lading to th colimit spcification is quivalnt. An xampl of th colimit opration is shown in Figur 7 and Figur 8. Givn th BIN-REL, REFLEXIVE, and TRANSITIVE spcifications in Figur 7, th colimit spcification would b th PRE- ORDER spcification as shown in th diagram in Figur 8. Notic that th sorts E, X, and T blong to th sam quivalnc class in PRE-ORDER. Likwis, th oprations, =, and < also form an quivalnc class in PRE-ORDER. Thus PRE-ORDER dfins a spcification with on sort, {E, X, T} and on opration, {, =, <}, which is both transitiv and rflxiv. Th spcification BIN-REL dfins th shard parts of th colimit but adds nothing to th final spcification. d j spc Bin-Rl is sorts E oprations : E, E Boolan nd spc Rflxiv is sorts X oprations = : X, X Boolan axioms x X x = x nd spc Transitiv is sorts T oprations < : T, T Boolan axioms x, y, z T (x < y y < z) x < z nd spc Pr-Ordr is sorts {E, X, T} oprations {, =, <} : {E, X, T}, {E, X, T} Boolan axioms x, y, z {E, X, T} x {, =, <} x (x {, =, <} y y {, =, <} z) x {, =, <} z nd Figur 7. Spcification Colimit Exampl Rflxiv {E X, =} c Bin-Rl c Pr-Ordr {E T, <} c Transitiv Figur 8. Exampl Colimit Diagram A catgory in which th colimit of all possibl C- objcts and C-arrows xists is calld cocomplt. As shown by Gogun and Burstall [2, 3], th catgory Sign and Spc ar both cocomplt; thrfor, th colimit opration may b usd frly within th catgory Spc to dfin th construction of complx thoris from a group of simplr thoris. Using morphisms, xtnsions, and colimits as a basic tool st, thr ar a numbr of ways that spcifications can b constructd [9, 4]: Pag 5 of 9

6 1. Build a spcification from a signatur and a st of axioms; 2. Form th union of a collction of spcifications; 3. Translat a spcification via a signatur morphism; 4. Hid som dtails of a spcification whil prsrving its modls; 5. Constrain th modls of a spcification to b minimal; 6. Paramtriz a spcification; and 7. Implmnt a spcification using faturs providd by othrs. Many of ths mthods ar usful in spcifying and implmnting information fusion systms. For instanc, if w can dfin th shard part of two typs of data, w can formally combin thm using a colimit Functors Th prvious sctions dfind th basic catgoris and construction tchniqus usd to build larg-scal softwar spcifications. In this sction, w xtnd ths concpts furthr to dfin modls of spcifications and how thy ar rlatd to th construction tchniqus usd to crat thir spcifications. Bfor dscribing this rlationship, w dfin th concpt of a functor that maps C-objcts and C-arrows from on catgory to anothr in such a way that th idntity and composition proprtis ar prsrvd [7]. Functor. Givn two catgoris A and B, a functor F: A B is a pair of functions, an objct function and a mapping function. Th objct function assigns to ach objct X of catgory A an objct F(X) of B; th mapping function assigns to ach arrow f: X Y of catgory A an arrow F(f) : F(X) F(Y) of catgory B. Ths functions satisfy th two rquirmnts: F(1 X ) = 1 F(X) for ach idntity 1 x of A F(g f) = F(g) F(f) for ach composit g f dfind in A Basically a functor is a morphism of catgoris. Actually, w hav alrady prsntd two functors: th rduct functor that maps modls of on spcification (in th catgory Mod[X 1 ]) into modls of a scond spcification (in th catgory Mod[X 2 ]) and th modls functor that maps spcifications in th catgory Spc to thir catgory of modls, Mod[X], in Cat, th catgory of all sufficintly small catgoris. 3. Automatic Multisnsor Fatur-basd Rcognition Systm To show applicability of th catgory thortic notions dscribd abov to information fusion systms, w will discuss a cas study of Automatic Multisnsor Fatur-basd Rcognition Systm (AMFRS) [6], which was originally dvlopd using a modl-basd approach. In this cas study, w transform th AMFRS framwork into an quivalnt systm using a catgory thortic approach. First w will discuss th original systm and thn show its quivalnt structur using algbraic spcifications and catgory thory Modl-Thory Basd Framwork In th original modl-basd dvlopmnt approach, wavlt-basd modls wr dvlopd for intgration into th AMFRS to hlp rcogniz targts. AMFRS uss a modl-basd framwork to dscrib how to combin information containd in th wavlts for us in th systm. Within this framwork, modls wr dvlopd to hlp rcogniz targts basd on wavlt cofficints that could b intrprtd as maningful faturs of th targt. In this framwork, modls wr dvlopd basd on a languag and its associatd thory that dscribd th smantics of th languag. To combin languags and thoris, thr oprators ar usd: rduction, xpansion, and union. In gnral, th rduction oprator rmovs symbols from a languag along with all th sntncs in which it xists in its associatd thory. Expansion is th opposit. Expansion allows us to add symbols and nw sntncs about thos symbols to th languag. Finally, th union oprator combins th symbols and sntncs from two diffrnt languag/thory pairs into a singl languag and a singl thory. Using ths oprators, Korona cratd a framwork for combining languags and thoris about two diffrnt typs of snsor data into a singl fusd languag and thory. This framwork is shown in Figur 9. In Figur 9, w show only th languag composition procss. Th thory fusion procss is idntical. In this xampl, w assum thr ar two snsors whos data is dscribd by two languags L r and L i. Ths languags ar xtndd to th languags L r and L i by adding symbols dnoting oprations on a subst of th wavlt cofficints usd to dscrib th snsor data. Ths substs of cofficints rprsnt thos cofficints that will b Pag 6 of 9

7 part of th final fusd languag. Th cofficints ar slctd by th dsignr basd on knowldg of th wavlt cofficints and thir rlationship to faturs in targts of intrst. L r E L r R L r r U L ri L ri L f E R L i R L i r E L i E - xpansion R - rduction U - union Figur 9. Modl-Thory Basd Framwork Aftr th ncssary symbols hav bn addd to th languags, L r and L i ar rducd by rmoving all th symbols not rlatd to th cofficints slctd for us in th final fusd languag. Th nw rducd languags, L r r and L i r, ar thn combind into a singl languag, L ri, by th union opration. This languag contains all th symbols rprsnting th cofficints and oprations on thm rquird to construct th final fusd languag. Th last two stps in th procss crat our final fusd languag, L f. First, L ri is xtndd to L ri by adding symbols dnoting oprations that combin th cofficints from L r r and L i r. Thn, w crat L f by rmoving th symbols dnoting thos oprations that do not work on th fusd st of cofficints An Equivalnt Catgory Thortic Framwork Bfor convrting th AMFRS modl-basd framwork into a catgory thortic framwork, a fw obsrvations ar ncssary. First, th languag and thory combination usd in AMFRS is basically quivalnt to an algbraic spcification. An algbraic spcification dfins a st of sorts, oprations ovr thos sorts, and axioms that dfin th smantics of th oprations. Constants, rlations and functions dfind via languag symbols ar dfind as oprations in an algbraic spcification. Sntncs of a thory translat to axioms in an algbraic spcification. Algbraic sorts dfin a collction of valus usd in th oprations. Th modl-basd xpansion, rduction, and union oprators also hav countrparts in catgory thory. Th basic oprator in catgory thory is th morphism. In th catgory of Spc, which includs all possibl algbraic spcifications, ths morphisms ar spcification morphisms that dfin how on spcification is mbddd in a scond spcification. That is, it dfins a mapping from th sorts and oprations of th first spcification into th sorts and oprations of th scond spcification in such a way as to nsur th axioms of th first spcification ar thorms of th scond spcification (i.., th axioms hold in th scond spcification undr th dfind mapping of sorts and oprations). Thus a spcification morphism can b usd to dfin an xpansion as wll as a rduction (thy ar basically invrss of ach othr). If w hav an xpansion of spcification A into spcification B, in ffct w hav a morphism from A to B. Likwis, a rduction of spcification A to spcification B, indicats morphism from B to A. Th languag union oprator can also b modld asily using th catgory thory colimit opration. Th colimit opration combins two (or mor) spcifications, automatically crating a morphism btwn th original spcifications and th rsulting colimit spcification. If two spcifications bing combind using a colimit opration shar common parts (.g., thy both us intgrs), ths parts can b spcifid as common by dfining morphisms from th common, or shard, spcification to th individual spcifications. This shard spcification, along with th associatd morphisms, ar includd in th colimit opration. Th rsult of this is that th shard parts of th two spcifications ar not duplicatd. Th convrsion of th modl-basd framwork into a catgory thortic framwork is shown in Figur 10. In this framwork, th languags and thir associatd thoris ar convrtd to algbraic spcifications (or thory prsntations) and rductions and xtnsions ar convrtd to morphisms. Not that a rduction from A to B rsults in a morphism from B to A. Th union opration is convrtd to a colimit opration. Th S spcification dnots any shard part of r spcifications and i. In this cas it might includ domain information about wavlts, targts, tc. Figur 11 rprsnts a simplification of th catgory thortic stting shown in Figur 10. Basically, th morphisms σ 3, σ 4, and σ 8 from Figur 10 hav bn combind into morphism σ 15 of Figur 11. This is possibl sinc all th sorts, oprations, and axioms rmovd by σ 3 and σ 4 can b carrid along without changing th smantics. As w s whn w gt to th modl cration phas, carrying along ths xtra sorts, oprations, and axioms will bcom an advantag. Pag 7 of 9

8 σ 1 S σ 2 S σ 3 σ 4 r r σ 12 σ 13 σ 5 σ 6 σ 7 d σ 14 T f -as- T f Figur 10. Catgorical Framwork S σ 10 σ 11 σ 8 σ 12 σ 13 σ 14 σ 15 T f Figur 11. Simplifid Catgorical Stting Figur 12 is an vn furthr simplification of th catgory thortic stting of Figur 10. In Figur 12, th morphisms σ 1, σ 2 and σ 7 from Figur 10 hav bn combind into morphism σ 14. In this framwork, w combin th two basic spcifications togthr via th colimit opration bfor w insrt any knowldg about which wavlt cofficints corrspond to which intrprtabl faturs. Sinc all th oprations usd to xpand th basic spcifications hav a wll dfind intrprtation in th xpandd spcifications (cf. [6]), th morphism σ 14 bcoms a dfinitional xtnsion and th subdiagram containd in th dottd box bcoms an intrprtation. An intrprtation basically says that w can build a modl of T f from a modl of. This is a powrful construct in catgory thortic softwar dvlopmnt tools such as Spcwar [5]. T f σ 15 Intrprtation Figur 12. Thory Intrprtation Finally Figur 13 dscribs how w crat modls in our catgory thortic framwork. In Figur 13, rprsnts th modl functor, which taks spcifications from th catgory Spc and maps thm to a valid catgory of modls, dnotd [Spc], in th catgory Cat (th catgory of all sufficintly small catgoris). Th nic part about th catgory thortic framwork w hav com up with is that ach morphism, σ: Α Β, inducs a rduct functor, σ, that automatically maps modls of B to modls of A. Thrfor if w crat a valid modl for B, w automatically gt a valid modl for A! Following th flows of rduct functors in Figur 13, w now s that if w can crat a valid modl of T f -as- (M ri as pointd at by th larg arrow in Figur 13) w can automatically crat th valid, consistnt modls M r, M i, M ri, and M f for,,, and T f rspctivly. 4. Implications Thr ar many positiv implications of putting th AMFRS dsign into a catgory thortic stting. First, thr is no information loss in translating languags and thoris into algbraic spcifications. In fact, w gain modling ability by adding th notion of a sort. By using sorts, w can prcisly dfin opration signaturs. Also, th notions of morphisms, dfinitional xtnsions, colimits, and intrprtations giv us a wid varity of tools with wll-dfind manings. W can prov whn morphisms and dfinitional xtnsions xist as wll as construct th rsulting colimit spcification basd on a st of spcifications and morphisms. All in all, catgory thory provids us a much gratr capability to prov rlationships btwn spcifications. Finally, th catgorical stting allows us to construct, Pag 8 of 9

9 in a provably corrct mannr, consistnt sts of modls rquird by th AMFRS systm. All w hav to do is construct on spcific modl and th modls rquird by AMFRS can b gnratd automatically. Th bottom lin is, you los nothing and gain a lot by using algbraic spcifications and catgory thory in th dvlopmnt of formal information fusion systms such as AMFRS. M r σ3 S σ 12 σ 13 d σ 14 M ri σ4 M i 6. Korona, Z. Modl-Thory Basd Fatur Slction for Multisnsor Rcognition. Ph.D. Thsis, Northastrn Univrsity, MacLan, Saundrs and Birkhoff. Algbra. Nw York, NY: Chlsa Publishing Company, Srinivas, Yllamraju V. Catgory Thory Dfinitions and Exampls. Tchnical Rport, Dpartmnt of Information and Computr Scinc, Univrsity of California, Irvin, Fbruary TR Srinivas, Yllamraju V. Algbraic Spcification: Syntax, Smantics, Structur. Tchnical Rport, Dpartmnt of Information and Computr Scinc, Univrsity of California, Irvin, Jun TR T f -as- σ 15 σ5 Mri T f σ6 M f Figur 13. Modl Cration using Thory Intrprtation 5. Rfrncs 1. Grkn, Mark J. Spcification and Dsign Thoris for Softwar Architcturs. PhD dissrtation, Graduat School of Enginring, Air Forc Institut of Tchnology (AU), Gogun, J. A. and R. M. Burstall. Som Fundamntal Algbraic Tools for th Smantics of Computation Part I: Comma Catgoris, Colimits, Signaturs and Thoris, Thortical Computr Scinc, 31: (1984). 3. Gogun, J. A. and R. M. Burstall. Som Fundamntal Algbraic Tools for th Smantics of Computation Part II: Signd and Abstract Thoris, Thortical Computr Scinc, 31: (1984). 4. Gogun, J. A. Rusing and Intrconncting Softwar Componnts, IEEE Computr, (Fbruary 1986). 5. Jullig, Richard and Yllamraju V. Srinivas. Diagrams for Softwar Synthsis. Procdings of th Knowldg Basd Softwar Enginring Confrnc. IEEE Pag 9 of 9

Higher order derivatives

Higher order derivatives Robrto s Nots on Diffrntial Calculus Chaptr 4: Basic diffrntiation ruls Sction 7 Highr ordr drivativs What you nd to know alrady: Basic diffrntiation ruls. What you can larn hr: How to rpat th procss of

More information

CS 361 Meeting 12 10/3/18

CS 361 Meeting 12 10/3/18 CS 36 Mting 2 /3/8 Announcmnts. Homwork 4 is du Friday. If Friday is Mountain Day, homwork should b turnd in at my offic or th dpartmnt offic bfor 4. 2. Homwork 5 will b availabl ovr th wknd. 3. Our midtrm

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018 Propositional Logic Combinatorial Problm Solving (CPS) Albrt Olivras Enric Rodríguz-Carbonll May 17, 2018 Ovrviw of th sssion Dfinition of Propositional Logic Gnral Concpts in Logic Rduction to SAT CNFs

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

COMPUTER GENERATED HOLOGRAMS Optical Sciences 627 W.J. Dallas (Monday, April 04, 2005, 8:35 AM) PART I: CHAPTER TWO COMB MATH.

COMPUTER GENERATED HOLOGRAMS Optical Sciences 627 W.J. Dallas (Monday, April 04, 2005, 8:35 AM) PART I: CHAPTER TWO COMB MATH. C:\Dallas\0_Courss\03A_OpSci_67\0 Cgh_Book\0_athmaticalPrliminaris\0_0 Combath.doc of 8 COPUTER GENERATED HOLOGRAS Optical Scincs 67 W.J. Dallas (onday, April 04, 005, 8:35 A) PART I: CHAPTER TWO COB ATH

More information

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation.

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation. Lur 7 Fourir Transforms and th Wav Euation Ovrviw and Motivation: W first discuss a fw faturs of th Fourir transform (FT), and thn w solv th initial-valu problm for th wav uation using th Fourir transform

More information

What are those βs anyway? Understanding Design Matrix & Odds ratios

What are those βs anyway? Understanding Design Matrix & Odds ratios Ral paramtr stimat WILD 750 - Wildlif Population Analysis of 6 What ar thos βs anyway? Undrsting Dsign Matrix & Odds ratios Rfrncs Hosmr D.W.. Lmshow. 000. Applid logistic rgrssion. John Wily & ons Inc.

More information

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013 18.782 Introduction to Arithmtic Gomtry Fall 2013 Lctur #20 11/14/2013 20.1 Dgr thorm for morphisms of curvs Lt us rstat th thorm givn at th nd of th last lctur, which w will now prov. Thorm 20.1. Lt φ:

More information

MATH 319, WEEK 15: The Fundamental Matrix, Non-Homogeneous Systems of Differential Equations

MATH 319, WEEK 15: The Fundamental Matrix, Non-Homogeneous Systems of Differential Equations MATH 39, WEEK 5: Th Fundamntal Matrix, Non-Homognous Systms of Diffrntial Equations Fundamntal Matrics Considr th problm of dtrmining th particular solution for an nsmbl of initial conditions For instanc,

More information

That is, we start with a general matrix: And end with a simpler matrix:

That is, we start with a general matrix: And end with a simpler matrix: DIAGON ALIZATION OF THE STR ESS TEN SOR INTRO DUCTIO N By th us of Cauchy s thorm w ar abl to rduc th numbr of strss componnts in th strss tnsor to only nin valus. An additional simplification of th strss

More information

Application of Vague Soft Sets in students evaluation

Application of Vague Soft Sets in students evaluation Availabl onlin at www.plagiarsarchlibrary.com Advancs in Applid Scinc Rsarch, 0, (6):48-43 ISSN: 0976-860 CODEN (USA): AASRFC Application of Vagu Soft Sts in studnts valuation B. Chtia*and P. K. Das Dpartmnt

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 0 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat th

More information

Derangements and Applications

Derangements and Applications 2 3 47 6 23 Journal of Intgr Squncs, Vol. 6 (2003), Articl 03..2 Drangmnts and Applications Mhdi Hassani Dpartmnt of Mathmatics Institut for Advancd Studis in Basic Scincs Zanjan, Iran mhassani@iasbs.ac.ir

More information

A Propagating Wave Packet Group Velocity Dispersion

A Propagating Wave Packet Group Velocity Dispersion Lctur 8 Phys 375 A Propagating Wav Packt Group Vlocity Disprsion Ovrviw and Motivation: In th last lctur w lookd at a localizd solution t) to th 1D fr-particl Schrödingr quation (SE) that corrsponds to

More information

(Upside-Down o Direct Rotation) β - Numbers

(Upside-Down o Direct Rotation) β - Numbers Amrican Journal of Mathmatics and Statistics 014, 4(): 58-64 DOI: 10593/jajms0140400 (Upsid-Down o Dirct Rotation) β - Numbrs Ammar Sddiq Mahmood 1, Shukriyah Sabir Ali,* 1 Dpartmnt of Mathmatics, Collg

More information

3 Finite Element Parametric Geometry

3 Finite Element Parametric Geometry 3 Finit Elmnt Paramtric Gomtry 3. Introduction Th intgral of a matrix is th matrix containing th intgral of ach and vry on of its original componnts. Practical finit lmnt analysis rquirs intgrating matrics,

More information

Construction of asymmetric orthogonal arrays of strength three via a replacement method

Construction of asymmetric orthogonal arrays of strength three via a replacement method isid/ms/26/2 Fbruary, 26 http://www.isid.ac.in/ statmath/indx.php?modul=prprint Construction of asymmtric orthogonal arrays of strngth thr via a rplacmnt mthod Tian-fang Zhang, Qiaoling Dng and Alok Dy

More information

Abstract Interpretation: concrete and abstract semantics

Abstract Interpretation: concrete and abstract semantics Abstract Intrprtation: concrt and abstract smantics Concrt smantics W considr a vry tiny languag that manags arithmtic oprations on intgrs valus. Th (concrt) smantics of th languags cab b dfind by th funzcion

More information

Content Skills Assessments Lessons. Identify, classify, and apply properties of negative and positive angles.

Content Skills Assessments Lessons. Identify, classify, and apply properties of negative and positive angles. Tachr: CORE TRIGONOMETRY Yar: 2012-13 Cours: TRIGONOMETRY Month: All Months S p t m b r Angls Essntial Qustions Can I idntify draw ngativ positiv angls in stard position? Do I hav a working knowldg of

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 07 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat

More information

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN

International Journal of Scientific & Engineering Research, Volume 6, Issue 7, July ISSN Intrnational Journal of Scintific & Enginring Rsarch, Volum 6, Issu 7, July-25 64 ISSN 2229-558 HARATERISTIS OF EDGE UTSET MATRIX OF PETERSON GRAPH WITH ALGEBRAI GRAPH THEORY Dr. G. Nirmala M. Murugan

More information

Einstein Equations for Tetrad Fields

Einstein Equations for Tetrad Fields Apiron, Vol 13, No, Octobr 006 6 Einstin Equations for Ttrad Filds Ali Rıza ŞAHİN, R T L Istanbul (Turky) Evry mtric tnsor can b xprssd by th innr product of ttrad filds W prov that Einstin quations for

More information

Estimation of apparent fraction defective: A mathematical approach

Estimation of apparent fraction defective: A mathematical approach Availabl onlin at www.plagiarsarchlibrary.com Plagia Rsarch Library Advancs in Applid Scinc Rsarch, 011, (): 84-89 ISSN: 0976-8610 CODEN (USA): AASRFC Estimation of apparnt fraction dfctiv: A mathmatical

More information

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES DONALD M. DAVIS Abstract. If p is a prim (implicit in notation and n a positiv intgr, lt ν(n dnot th xponnt of p in n, and U(n n/p ν(n, th unit

More information

Numerical considerations regarding the simulation of an aircraft in the approaching phase for landing

Numerical considerations regarding the simulation of an aircraft in the approaching phase for landing INCAS BULLETIN, Volum, Numbr 1/ 1 Numrical considrations rgarding th simulation of an aircraft in th approaching phas for landing Ionl Cristinl IORGA ionliorga@yahoo.com Univrsity of Craiova, Alxandru

More information

What is a hereditary algebra?

What is a hereditary algebra? What is a hrditary algbra? (On Ext 2 and th vanishing of Ext 2 ) Claus Michal Ringl At th Münstr workshop 2011, thr short lcturs wr arrangd in th styl of th rgular column in th Notics of th AMS: What is?

More information

Computing and Communications -- Network Coding

Computing and Communications -- Network Coding 89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc

More information

Week 3: Connected Subgraphs

Week 3: Connected Subgraphs Wk 3: Connctd Subgraphs Sptmbr 19, 2016 1 Connctd Graphs Path, Distanc: A path from a vrtx x to a vrtx y in a graph G is rfrrd to an xy-path. Lt X, Y V (G). An (X, Y )-path is an xy-path with x X and y

More information

Sundials and Linear Algebra

Sundials and Linear Algebra Sundials and Linar Algbra M. Scot Swan July 2, 25 Most txts on crating sundials ar dirctd towards thos who ar solly intrstd in making and using sundials and usually assums minimal mathmatical background.

More information

Quasi-Classical States of the Simple Harmonic Oscillator

Quasi-Classical States of the Simple Harmonic Oscillator Quasi-Classical Stats of th Simpl Harmonic Oscillator (Draft Vrsion) Introduction: Why Look for Eignstats of th Annihilation Oprator? Excpt for th ground stat, th corrspondnc btwn th quantum nrgy ignstats

More information

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES. 1. Statement of results

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES. 1. Statement of results BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES DONALD M. DAVIS Abstract. If p is a prim and n a positiv intgr, lt ν p (n dnot th xponnt of p in n, and u p (n n/p νp(n th unit part of n. If α

More information

2.3 Matrix Formulation

2.3 Matrix Formulation 23 Matrix Formulation 43 A mor complicatd xampl ariss for a nonlinar systm of diffrntial quations Considr th following xampl Exampl 23 x y + x( x 2 y 2 y x + y( x 2 y 2 (233 Transforming to polar coordinats,

More information

Properties of Phase Space Wavefunctions and Eigenvalue Equation of Momentum Dispersion Operator

Properties of Phase Space Wavefunctions and Eigenvalue Equation of Momentum Dispersion Operator Proprtis of Phas Spac Wavfunctions and Eignvalu Equation of Momntum Disprsion Oprator Ravo Tokiniaina Ranaivoson 1, Raolina Andriambololona 2, Hanitriarivo Rakotoson 3 raolinasp@yahoo.fr 1 ;jacqulinraolina@hotmail.com

More information

Mutually Independent Hamiltonian Cycles of Pancake Networks

Mutually Independent Hamiltonian Cycles of Pancake Networks Mutually Indpndnt Hamiltonian Cycls of Pancak Ntworks Chng-Kuan Lin Dpartmnt of Mathmatics National Cntral Univrsity, Chung-Li, Taiwan 00, R O C discipl@ms0urlcomtw Hua-Min Huang Dpartmnt of Mathmatics

More information

CPSC 665 : An Algorithmist s Toolkit Lecture 4 : 21 Jan Linear Programming

CPSC 665 : An Algorithmist s Toolkit Lecture 4 : 21 Jan Linear Programming CPSC 665 : An Algorithmist s Toolkit Lctur 4 : 21 Jan 2015 Lcturr: Sushant Sachdva Linar Programming Scrib: Rasmus Kyng 1. Introduction An optimization problm rquirs us to find th minimum or maximum) of

More information

Section 6.1. Question: 2. Let H be a subgroup of a group G. Then H operates on G by left multiplication. Describe the orbits for this operation.

Section 6.1. Question: 2. Let H be a subgroup of a group G. Then H operates on G by left multiplication. Describe the orbits for this operation. MAT 444 H Barclo Spring 004 Homwork 6 Solutions Sction 6 Lt H b a subgroup of a group G Thn H oprats on G by lft multiplication Dscrib th orbits for this opration Th orbits of G ar th right costs of H

More information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Procssing Prof. Mark Fowlr Dtails of th ot St #19 Rading Assignmnt: Sct. 7.1.2, 7.1.3, & 7.2 of Proakis & Manolakis Dfinition of th So Givn signal data points x[n] for n = 0,, -1

More information

LINEAR DELAY DIFFERENTIAL EQUATION WITH A POSITIVE AND A NEGATIVE TERM

LINEAR DELAY DIFFERENTIAL EQUATION WITH A POSITIVE AND A NEGATIVE TERM Elctronic Journal of Diffrntial Equations, Vol. 2003(2003), No. 92, pp. 1 6. ISSN: 1072-6691. URL: http://jd.math.swt.du or http://jd.math.unt.du ftp jd.math.swt.du (login: ftp) LINEAR DELAY DIFFERENTIAL

More information

5.80 Small-Molecule Spectroscopy and Dynamics

5.80 Small-Molecule Spectroscopy and Dynamics MIT OpnCoursWar http://ocw.mit.du 5.80 Small-Molcul Spctroscopy and Dynamics Fall 008 For information about citing ths matrials or our Trms of Us, visit: http://ocw.mit.du/trms. Lctur # 3 Supplmnt Contnts

More information

A Sub-Optimal Log-Domain Decoding Algorithm for Non-Binary LDPC Codes

A Sub-Optimal Log-Domain Decoding Algorithm for Non-Binary LDPC Codes Procdings of th 9th WSEAS Intrnational Confrnc on APPLICATIONS of COMPUTER ENGINEERING A Sub-Optimal Log-Domain Dcoding Algorithm for Non-Binary LDPC Cods CHIRAG DADLANI and RANJAN BOSE Dpartmnt of Elctrical

More information

ECE602 Exam 1 April 5, You must show ALL of your work for full credit.

ECE602 Exam 1 April 5, You must show ALL of your work for full credit. ECE62 Exam April 5, 27 Nam: Solution Scor: / This xam is closd-book. You must show ALL of your work for full crdit. Plas rad th qustions carfully. Plas chck your answrs carfully. Calculators may NOT b

More information

Recall that by Theorems 10.3 and 10.4 together provide us the estimate o(n2 ), S(q) q 9, q=1

Recall that by Theorems 10.3 and 10.4 together provide us the estimate o(n2 ), S(q) q 9, q=1 Chaptr 11 Th singular sris Rcall that by Thorms 10 and 104 togthr provid us th stimat 9 4 n 2 111 Rn = SnΓ 2 + on2, whr th singular sris Sn was dfind in Chaptr 10 as Sn = q=1 Sq q 9, with Sq = 1 a q gcda,q=1

More information

Thus, because if either [G : H] or [H : K] is infinite, then [G : K] is infinite, then [G : K] = [G : H][H : K] for all infinite cases.

Thus, because if either [G : H] or [H : K] is infinite, then [G : K] is infinite, then [G : K] = [G : H][H : K] for all infinite cases. Homwork 5 M 373K Solutions Mark Lindbrg and Travis Schdlr 1. Prov that th ring Z/mZ (for m 0) is a fild if and only if m is prim. ( ) Proof by Contrapositiv: Hr, thr ar thr cass for m not prim. m 0: Whn

More information

On spanning trees and cycles of multicolored point sets with few intersections

On spanning trees and cycles of multicolored point sets with few intersections On spanning trs and cycls of multicolord point sts with fw intrsctions M. Kano, C. Mrino, and J. Urrutia April, 00 Abstract Lt P 1,..., P k b a collction of disjoint point sts in R in gnral position. W

More information

Evaluating Reliability Systems by Using Weibull & New Weibull Extension Distributions Mushtak A.K. Shiker

Evaluating Reliability Systems by Using Weibull & New Weibull Extension Distributions Mushtak A.K. Shiker Evaluating Rliability Systms by Using Wibull & Nw Wibull Extnsion Distributions Mushtak A.K. Shikr مشتاق عبذ الغني شخير Univrsity of Babylon, Collg of Education (Ibn Hayan), Dpt. of Mathmatics Abstract

More information

Brief Introduction to Statistical Mechanics

Brief Introduction to Statistical Mechanics Brif Introduction to Statistical Mchanics. Purpos: Ths nots ar intndd to provid a vry quick introduction to Statistical Mchanics. Th fild is of cours far mor vast than could b containd in ths fw pags.

More information

GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES. Eduard N. Klenov* Rostov-on-Don, Russia

GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES. Eduard N. Klenov* Rostov-on-Don, Russia GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES Eduard N. Klnov* Rostov-on-Don, Russia Th articl considrs phnomnal gomtry figurs bing th carrirs of valu spctra for th pairs of th rmaining additiv

More information

Two Products Manufacturer s Production Decisions with Carbon Constraint

Two Products Manufacturer s Production Decisions with Carbon Constraint Managmnt Scinc and Enginring Vol 7 No 3 pp 3-34 DOI:3968/jms9335X374 ISSN 93-34 [Print] ISSN 93-35X [Onlin] wwwcscanadant wwwcscanadaorg Two Products Manufacturr s Production Dcisions with Carbon Constraint

More information

u x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula

u x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula 7. Intgration by Parts Each drivativ formula givs ris to a corrsponding intgral formula, as w v sn many tims. Th drivativ product rul yilds a vry usful intgration tchniqu calld intgration by parts. Starting

More information

Lecture 37 (Schrödinger Equation) Physics Spring 2018 Douglas Fields

Lecture 37 (Schrödinger Equation) Physics Spring 2018 Douglas Fields Lctur 37 (Schrödingr Equation) Physics 6-01 Spring 018 Douglas Filds Rducd Mass OK, so th Bohr modl of th atom givs nrgy lvls: E n 1 k m n 4 But, this has on problm it was dvlopd assuming th acclration

More information

The graph of y = x (or y = ) consists of two branches, As x 0, y + ; as x 0, y +. x = 0 is the

The graph of y = x (or y = ) consists of two branches, As x 0, y + ; as x 0, y +. x = 0 is the Copyright itutcom 005 Fr download & print from wwwitutcom Do not rproduc by othr mans Functions and graphs Powr functions Th graph of n y, for n Q (st of rational numbrs) y is a straight lin through th

More information

First derivative analysis

First derivative analysis Robrto s Nots on Dirntial Calculus Chaptr 8: Graphical analysis Sction First drivativ analysis What you nd to know alrady: How to us drivativs to idntiy th critical valus o a unction and its trm points

More information

The Equitable Dominating Graph

The Equitable Dominating Graph Intrnational Journal of Enginring Rsarch and Tchnology. ISSN 0974-3154 Volum 8, Numbr 1 (015), pp. 35-4 Intrnational Rsarch Publication Hous http://www.irphous.com Th Equitabl Dominating Graph P.N. Vinay

More information

Cramér-Rao Inequality: Let f(x; θ) be a probability density function with continuous parameter

Cramér-Rao Inequality: Let f(x; θ) be a probability density function with continuous parameter WHEN THE CRAMÉR-RAO INEQUALITY PROVIDES NO INFORMATION STEVEN J. MILLER Abstract. W invstigat a on-paramtr family of probability dnsitis (rlatd to th Parto distribution, which dscribs many natural phnomna)

More information

Introduction to the Fourier transform. Computer Vision & Digital Image Processing. The Fourier transform (continued) The Fourier transform (continued)

Introduction to the Fourier transform. Computer Vision & Digital Image Processing. The Fourier transform (continued) The Fourier transform (continued) Introduction to th Fourir transform Computr Vision & Digital Imag Procssing Fourir Transform Lt f(x) b a continuous function of a ral variabl x Th Fourir transform of f(x), dnotd by I {f(x)} is givn by:

More information

Problem Set 6 Solutions

Problem Set 6 Solutions 6.04/18.06J Mathmatics for Computr Scinc March 15, 005 Srini Dvadas and Eric Lhman Problm St 6 Solutions Du: Monday, March 8 at 9 PM in Room 3-044 Problm 1. Sammy th Shark is a financial srvic providr

More information

SCHUR S THEOREM REU SUMMER 2005

SCHUR S THEOREM REU SUMMER 2005 SCHUR S THEOREM REU SUMMER 2005 1. Combinatorial aroach Prhas th first rsult in th subjct blongs to I. Schur and dats back to 1916. On of his motivation was to study th local vrsion of th famous quation

More information

Elements of Statistical Thermodynamics

Elements of Statistical Thermodynamics 24 Elmnts of Statistical Thrmodynamics Statistical thrmodynamics is a branch of knowldg that has its own postulats and tchniqus. W do not attmpt to giv hr vn an introduction to th fild. In this chaptr,

More information

COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM

COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM COUNTING TAMELY RAMIFIED EXTENSIONS OF LOCAL FIELDS UP TO ISOMORPHISM Jim Brown Dpartmnt of Mathmatical Scincs, Clmson Univrsity, Clmson, SC 9634, USA jimlb@g.clmson.du Robrt Cass Dpartmnt of Mathmatics,

More information

Observer Bias and Reliability By Xunchi Pu

Observer Bias and Reliability By Xunchi Pu Obsrvr Bias and Rliability By Xunchi Pu Introduction Clarly all masurmnts or obsrvations nd to b mad as accuratly as possibl and invstigators nd to pay carful attntion to chcking th rliability of thir

More information

Abstract Interpretation. Lecture 5. Profs. Aiken, Barrett & Dill CS 357 Lecture 5 1

Abstract Interpretation. Lecture 5. Profs. Aiken, Barrett & Dill CS 357 Lecture 5 1 Abstract Intrprtation 1 History On brakthrough papr Cousot & Cousot 77 (?) Inspird by Dataflow analysis Dnotational smantics Enthusiastically mbracd by th community At last th functional community... At

More information

ON RIGHT(LEFT) DUO PO-SEMIGROUPS. S. K. Lee and K. Y. Park

ON RIGHT(LEFT) DUO PO-SEMIGROUPS. S. K. Lee and K. Y. Park Kangwon-Kyungki Math. Jour. 11 (2003), No. 2, pp. 147 153 ON RIGHT(LEFT) DUO PO-SEMIGROUPS S. K. L and K. Y. Park Abstract. W invstigat som proprtis on right(rsp. lft) duo po-smigroups. 1. Introduction

More information

UNTYPED LAMBDA CALCULUS (II)

UNTYPED LAMBDA CALCULUS (II) 1 UNTYPED LAMBDA CALCULUS (II) RECALL: CALL-BY-VALUE O.S. Basic rul Sarch ruls: (\x.) v [v/x] 1 1 1 1 v v CALL-BY-VALUE EVALUATION EXAMPLE (\x. x x) (\y. y) x x [\y. y / x] = (\y. y) (\y. y) y [\y. y /

More information

A. Limits and Horizontal Asymptotes ( ) f x f x. f x. x "±# ( ).

A. Limits and Horizontal Asymptotes ( ) f x f x. f x. x ±# ( ). A. Limits and Horizontal Asymptots What you ar finding: You can b askd to find lim x "a H.A.) problm is asking you find lim x "# and lim x "$#. or lim x "±#. Typically, a horizontal asymptot algbraically,

More information

Homotopy perturbation technique

Homotopy perturbation technique Comput. Mthods Appl. Mch. Engrg. 178 (1999) 257±262 www.lsvir.com/locat/cma Homotopy prturbation tchniqu Ji-Huan H 1 Shanghai Univrsity, Shanghai Institut of Applid Mathmatics and Mchanics, Shanghai 272,

More information

u 3 = u 3 (x 1, x 2, x 3 )

u 3 = u 3 (x 1, x 2, x 3 ) Lctur 23: Curvilinar Coordinats (RHB 8.0 It is oftn convnint to work with variabls othr than th Cartsian coordinats x i ( = x, y, z. For xampl in Lctur 5 w mt sphrical polar and cylindrical polar coordinats.

More information

EXST Regression Techniques Page 1

EXST Regression Techniques Page 1 EXST704 - Rgrssion Tchniqus Pag 1 Masurmnt rrors in X W hav assumd that all variation is in Y. Masurmnt rror in this variabl will not ffct th rsults, as long as thy ar uncorrlatd and unbiasd, sinc thy

More information

perm4 A cnt 0 for for if A i 1 A i cnt cnt 1 cnt i j. j k. k l. i k. j l. i l

perm4 A cnt 0 for for if A i 1 A i cnt cnt 1 cnt i j. j k. k l. i k. j l. i l h 4D, 4th Rank, Antisytric nsor and th 4D Equivalnt to th Cross Product or Mor Fun with nsors!!! Richard R Shiffan Digital Graphics Assoc 8 Dunkirk Av LA, Ca 95 rrs@isidu his docunt dscribs th four dinsional

More information

Estimation of odds ratios in Logistic Regression models under different parameterizations and Design matrices

Estimation of odds ratios in Logistic Regression models under different parameterizations and Design matrices Advancs in Computational Intllignc, Man-Machin Systms and Cybrntics Estimation of odds ratios in Logistic Rgrssion modls undr diffrnt paramtrizations and Dsign matrics SURENDRA PRASAD SINHA*, LUIS NAVA

More information

ph People Grade Level: basic Duration: minutes Setting: classroom or field site

ph People Grade Level: basic Duration: minutes Setting: classroom or field site ph Popl Adaptd from: Whr Ar th Frogs? in Projct WET: Curriculum & Activity Guid. Bozman: Th Watrcours and th Council for Environmntal Education, 1995. ph Grad Lvl: basic Duration: 10 15 minuts Stting:

More information

The second condition says that a node α of the tree has exactly n children if the arity of its label is n.

The second condition says that a node α of the tree has exactly n children if the arity of its label is n. CS 6110 S14 Hanout 2 Proof of Conflunc 27 January 2014 In this supplmntary lctur w prov that th λ-calculus is conflunt. This is rsult is u to lonzo Church (1903 1995) an J. arkly Rossr (1907 1989) an is

More information

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS Slid DIGITAL SIGAL PROCESSIG UIT I DISCRETE TIME SIGALS AD SYSTEM Slid Rviw of discrt-tim signals & systms Signal:- A signal is dfind as any physical quantity that varis with tim, spac or any othr indpndnt

More information

10. The Discrete-Time Fourier Transform (DTFT)

10. The Discrete-Time Fourier Transform (DTFT) Th Discrt-Tim Fourir Transform (DTFT Dfinition of th discrt-tim Fourir transform Th Fourir rprsntation of signals plays an important rol in both continuous and discrt signal procssing In this sction w

More information

Symmetric centrosymmetric matrix vector multiplication

Symmetric centrosymmetric matrix vector multiplication Linar Algbra and its Applications 320 (2000) 193 198 www.lsvir.com/locat/laa Symmtric cntrosymmtric matrix vctor multiplication A. Mlman 1 Dpartmnt of Mathmatics, Univrsity of San Francisco, San Francisco,

More information

SOME PARAMETERS ON EQUITABLE COLORING OF PRISM AND CIRCULANT GRAPH.

SOME PARAMETERS ON EQUITABLE COLORING OF PRISM AND CIRCULANT GRAPH. SOME PARAMETERS ON EQUITABLE COLORING OF PRISM AND CIRCULANT GRAPH. K VASUDEVAN, K. SWATHY AND K. MANIKANDAN 1 Dpartmnt of Mathmatics, Prsidncy Collg, Chnnai-05, India. E-Mail:vasu k dvan@yahoo.com. 2,

More information

CS 6353 Compiler Construction, Homework #1. 1. Write regular expressions for the following informally described languages:

CS 6353 Compiler Construction, Homework #1. 1. Write regular expressions for the following informally described languages: CS 6353 Compilr Construction, Homwork #1 1. Writ rgular xprssions for th following informally dscribd languags: a. All strings of 0 s and 1 s with th substring 01*1. Answr: (0 1)*01*1(0 1)* b. All strings

More information

cycle that does not cross any edges (including its own), then it has at least

cycle that does not cross any edges (including its own), then it has at least W prov th following thorm: Thorm If a K n is drawn in th plan in such a way that it has a hamiltonian cycl that dos not cross any dgs (including its own, thn it has at last n ( 4 48 π + O(n crossings Th

More information

Middle East Technical University Department of Mechanical Engineering ME 413 Introduction to Finite Element Analysis

Middle East Technical University Department of Mechanical Engineering ME 413 Introduction to Finite Element Analysis Middl East Tchnical Univrsity Dpartmnt of Mchanical Enginring ME 43 Introduction to Finit Elmnt Analysis Chaptr 3 Computr Implmntation of D FEM Ths nots ar prpard by Dr. Cünyt Srt http://www.m.mtu.du.tr/popl/cunyt

More information

Ch. 24 Molecular Reaction Dynamics 1. Collision Theory

Ch. 24 Molecular Reaction Dynamics 1. Collision Theory Ch. 4 Molcular Raction Dynamics 1. Collision Thory Lctur 16. Diffusion-Controlld Raction 3. Th Matrial Balanc Equation 4. Transition Stat Thory: Th Eyring Equation 5. Transition Stat Thory: Thrmodynamic

More information

There is an arbitrary overall complex phase that could be added to A, but since this makes no difference we set it to zero and choose A real.

There is an arbitrary overall complex phase that could be added to A, but since this makes no difference we set it to zero and choose A real. Midtrm #, Physics 37A, Spring 07. Writ your rsponss blow or on xtra pags. Show your work, and tak car to xplain what you ar doing; partial crdit will b givn for incomplt answrs that dmonstrat som concptual

More information

Basic Polyhedral theory

Basic Polyhedral theory Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist

More information

Hydrogen Atom and One Electron Ions

Hydrogen Atom and One Electron Ions Hydrogn Atom and On Elctron Ions Th Schrödingr quation for this two-body problm starts out th sam as th gnral two-body Schrödingr quation. First w sparat out th motion of th cntr of mass. Th intrnal potntial

More information

Transitional Probability Model for a Serial Phases in Production

Transitional Probability Model for a Serial Phases in Production Jurnal Karya Asli Lorkan Ahli Matmatik Vol. 3 No. 2 (2010) pag 49-54. Jurnal Karya Asli Lorkan Ahli Matmatik Transitional Probability Modl for a Srial Phass in Production Adam Baharum School of Mathmatical

More information

On systems of complex numbers and their application to the theory of transformation groups.

On systems of complex numbers and their application to the theory of transformation groups. Übr Systm complxr Zahln und ihr Anwndung in dr Thori dr Transformationsgruppn Monatsth. f. Math. u. Physik (89), 8-54. On systms of complx numbrs and thir application to th thory of transformation groups.

More information

Chapter 6 Folding. Folding

Chapter 6 Folding. Folding Chaptr 6 Folding Wintr 1 Mokhtar Abolaz Folding Th folding transformation is usd to systmatically dtrmin th control circuits in DSP architctur whr multipl algorithm oprations ar tim-multiplxd to a singl

More information

General Notes About 2007 AP Physics Scoring Guidelines

General Notes About 2007 AP Physics Scoring Guidelines AP PHYSICS C: ELECTRICITY AND MAGNETISM 2007 SCORING GUIDELINES Gnral Nots About 2007 AP Physics Scoring Guidlins 1. Th solutions contain th most common mthod of solving th fr-rspons qustions and th allocation

More information

Background: We have discussed the PIB, HO, and the energy of the RR model. In this chapter, the H-atom, and atomic orbitals.

Background: We have discussed the PIB, HO, and the energy of the RR model. In this chapter, the H-atom, and atomic orbitals. Chaptr 7 Th Hydrogn Atom Background: W hav discussd th PIB HO and th nrgy of th RR modl. In this chaptr th H-atom and atomic orbitals. * A singl particl moving undr a cntral forc adoptd from Scott Kirby

More information

(1) Then we could wave our hands over this and it would become:

(1) Then we could wave our hands over this and it would become: MAT* K285 Spring 28 Anthony Bnoit 4/17/28 Wk 12: Laplac Tranform Rading: Kohlr & Johnon, Chaptr 5 to p. 35 HW: 5.1: 3, 7, 1*, 19 5.2: 1, 5*, 13*, 19, 45* 5.3: 1, 11*, 19 * Pla writ-up th problm natly and

More information

Another view for a posteriori error estimates for variational inequalities of the second kind

Another view for a posteriori error estimates for variational inequalities of the second kind Accptd by Applid Numrical Mathmatics in July 2013 Anothr viw for a postriori rror stimats for variational inqualitis of th scond kind Fi Wang 1 and Wimin Han 2 Abstract. In this papr, w giv anothr viw

More information

CHAPTER 1. Introductory Concepts Elements of Vector Analysis Newton s Laws Units The basis of Newtonian Mechanics D Alembert s Principle

CHAPTER 1. Introductory Concepts Elements of Vector Analysis Newton s Laws Units The basis of Newtonian Mechanics D Alembert s Principle CHPTER 1 Introductory Concpts Elmnts of Vctor nalysis Nwton s Laws Units Th basis of Nwtonian Mchanics D lmbrt s Principl 1 Scinc of Mchanics: It is concrnd with th motion of matrial bodis. odis hav diffrnt

More information

ANALYSIS IN THE FREQUENCY DOMAIN

ANALYSIS IN THE FREQUENCY DOMAIN ANALYSIS IN THE FREQUENCY DOMAIN SPECTRAL DENSITY Dfinition Th spctral dnsit of a S.S.P. t also calld th spctrum of t is dfind as: + { γ }. jτ γ τ F τ τ In othr words, of th covarianc function. is dfind

More information

What is the product of an integer multiplied by zero? and divided by zero?

What is the product of an integer multiplied by zero? and divided by zero? IMP007 Introductory Math Cours 3. ARITHMETICS AND FUNCTIONS 3.. BASIC ARITHMETICS REVIEW (from GRE) Which numbrs form th st of th Intgrs? What is th product of an intgr multiplid by zro? and dividd by

More information

On the Hamiltonian of a Multi-Electron Atom

On the Hamiltonian of a Multi-Electron Atom On th Hamiltonian of a Multi-Elctron Atom Austn Gronr Drxl Univrsity Philadlphia, PA Octobr 29, 2010 1 Introduction In this papr, w will xhibit th procss of achiving th Hamiltonian for an lctron gas. Making

More information

1 Minimum Cut Problem

1 Minimum Cut Problem CS 6 Lctur 6 Min Cut and argr s Algorithm Scribs: Png Hui How (05), Virginia Dat: May 4, 06 Minimum Cut Problm Today, w introduc th minimum cut problm. This problm has many motivations, on of which coms

More information

MCE503: Modeling and Simulation of Mechatronic Systems Discussion on Bond Graph Sign Conventions for Electrical Systems

MCE503: Modeling and Simulation of Mechatronic Systems Discussion on Bond Graph Sign Conventions for Electrical Systems MCE503: Modling and Simulation o Mchatronic Systms Discussion on Bond Graph Sign Convntions or Elctrical Systms Hanz ichtr, PhD Clvland Stat Univrsity, Dpt o Mchanical Enginring 1 Basic Assumption In a

More information

Problem Set #2 Due: Friday April 20, 2018 at 5 PM.

Problem Set #2 Due: Friday April 20, 2018 at 5 PM. 1 EE102B Spring 2018 Signal Procssing and Linar Systms II Goldsmith Problm St #2 Du: Friday April 20, 2018 at 5 PM. 1. Non-idal sampling and rcovry of idal sampls by discrt-tim filtring 30 pts) Considr

More information

surface of a dielectric-metal interface. It is commonly used today for discovering the ways in

surface of a dielectric-metal interface. It is commonly used today for discovering the ways in Surfac plasmon rsonanc is snsitiv mchanism for obsrving slight changs nar th surfac of a dilctric-mtal intrfac. It is commonl usd toda for discovring th was in which protins intract with thir nvironmnt,

More information

Types of Transfer Functions. Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters

Types of Transfer Functions. Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters Typs of Transfr Typs of Transfr x[n] X( LTI h[n] H( y[n] Y( y [ n] h[ k] x[ n k] k Y ( H ( X ( Th tim-domain classification of an LTI digital transfr function is basd on th lngth of its impuls rspons h[n]:

More information

Finding low cost TSP and 2-matching solutions using certain half integer subtour vertices

Finding low cost TSP and 2-matching solutions using certain half integer subtour vertices Finding low cost TSP and 2-matching solutions using crtain half intgr subtour vrtics Sylvia Boyd and Robrt Carr Novmbr 996 Introduction Givn th complt graph K n = (V, E) on n nods with dg costs c R E,

More information