Theories of Vowel Systems: Quantal Theory and Adaptive Dispersion
|
|
|
- Felix Lee
- 6 years ago
- Views:
Transcription
1 L105/205 Phontcs Scrborough Hndout 8 10/25/05 Rdng: Stvns, Lljncrnts & Lndblom (tody) Thors of Vowl Systms: Quntl Thory nd Adptv Dsprson 1. Thr r hug (vn nfnt) numbr of dffrnt rtcultons tht cn b md. Obvously, thy r not ll usd n ny lngug. But vn cross lngugs, crtn spch sounds r vry common, whl othrs r qut rr. Both Quntl Thory nd th Thory of Adptv Dsprson sk to xpln why crtn sounds nd crtn systms of sounds r fvord cross-lngustclly. Quntl Thory (Stvns 1972, 1989) 2. Th coustc thory of spch producton xplns th rlton btwn vocl trct confgurtons nd coustc output. In gnrl, whn you chng th confgurton of th vocl trct, you chng th coustc output. Howvr, th rlton btwn rtcultory prmtrs nd coustc output s not lnr. Thr s lrg coustc (nd udtory) dffrnc btwn rgons I nd III. Wthn rgons I nd III, howvr, th coustc prmtr s rltvly nsnstv to chng n th rtcultory prmtr. In othr words, chngs n rtculton don t hv much ffct on th spch output. 3. Stvns clm s tht lngustc contrsts nvolv dffrncs btwn quntl rgons (I nd III). All quntl rgons dfn contrstv sounds nd ll contrstv sounds dffr quntlly. Or t lst, quntl dstnctons r prfrrd. 4. Why do quntl rgons nflunc sound systms? Artcultons don t hv to b prcs to produc crtn output. And contnuous movmnt through th rgon wll yld n coustc stdy stt. Artcultory sloppnss won t ffct prcptblty.
2 Furthrmor, rtcultory spc s ncssrly contnuous, but dffrnt rtcultons cn produc qulttvly dffrnt coustc ffcts. Th pltu-lk rgons r th corrlts of dstnctv fturs. 5. Exmpls of quntl ctgors ovr n rtcultory contnuum: Dgr of glottl constrcton: complt opnng for voclss sounds to lss opnng for modl vocng to complt closur for glottl stop Dgr of vocl trct constrcton: vowl (low V md V hgh V) to glds to frctvs to stops Plc of rtculton for vowls (.., plc of constrcton) 6. Quntl thory ppld to vowls: Rcll tht nomogrms show us th coustc consquncs (n trms of formnt frquncs) of vryng sngl rtcultory prmtr (plc of constrcton). Thr r rgons of coustc stblty (quntl rgons) whr two formnts convrg. [] [] [u] [] s producd t th convrgnc of F1 nd F2, whr th front nd bck cvts of th vocl trct r of pproxmtly qul lngths.
3 [] s producd t th convrgnc of F2 nd F3, crtd by constrcton n th pltl rgon. (Rmmbr, F1 rsults from th Hlmholz rsontor.) [u] s producd t brod F2 mnmum, whr F2 s nr stbl F1. Ths thr vowls r quntl vowls. Thus, thy should b hghly prfrrd crosslngustclly, nd n fct thy r. 7. Th upshot of Quntl Thory s ths: Spkrs cn gt wy wth rtcultory sloppnss f lngugs mk us of quntl phontc ctgors. Nr-contnuous rtcultons yld dscrt coustc (prcptul) ctgors. Sgmnts tht xplot quntl rgons (rgons of stblty) wll b common cross lngugs. (Sgmnts tht dpnd of dstnctons wthn quntl rgon wll b rr.) Howvr, thr r sgnfcnt crtcsms of Quntl Thory. It prdcts grtr smlrty n coustc dtl cross lngugs thn s obsrvd. It dosn t prdct th rng of contrsts tht r ttstd cross-lngustclly. It dosn t ccount for dstnctons tht rly on multpl rtcultory prmtrs ( rgon of stblty for on my b unstbl for nothr). It s not ctully clr tht llowng for rtcultory sloppnss s so ncssry. A postultd dvntg of sounds whos coustcs r rltvly nsnstv to rtcultory vrton s tht ths llows mprcson n rtculton wthout dsstrous coustc consquncs. But lngugs do not sm to tk consstnt dvntg of ths. Thory of Adptv Dsprson (Lljncrnts & Lndblom 1972, Lndblom 1986, 1990) 8. Th thory of Adptv Dsprson offrs n ltrntv xplnton for th cross-lngustc prfrnc for th vowls [,, u]. Ths vowls r not only n potntlly stbl rtcultory rgons, but thy r t th xtrms of th physologclly possbl vowl spc. So thy r mxmlly coustclly dstnct nd r unlkly to b confusd by lstnr. Assumpton: Lstnrs blts to hr vowl dstnctons provd slctonl prssur on sgmnt nvntors (dchronclly). Th prspctv s shftd from xplorng prfrrd/dsprfrrd sounds to prfrrd/dsprfrrd systms of contrsts..g., crtn vowl nvntors r common: u u othrs r unttstd: (dptd from Flmmng nots) o ε u o u y u ø ə o ε œ æ
4 9. Th Thory of Adptv Dsprson posts tht th sounds n gvn lngug r slctd to bst stsfy functonl rqurmnt of mxml (or, n ltr vrsons, suffcnt) prcptul dstnctvnss. In prtculr, Adptv Dsprson dscrbs how th rqurmnt of prcptul contrst prdcts vowl nvntors. 10. In ordr to b tstbl, th Thory of Adptv Dsprson hs to quntfy th noton of contrst. A vowl spc s th coustc/udtory rng of vowls tht r rtcultorly possbl. L&L look t Ml-scld F1 by F2 vowl spc. Th ml scl s trnsformton of Hz frquncy bsd on udtory prcpton. So ths vowl spc s clos to n udtory spc. Prcptul contrst btwn two vowls s msurd s th lnr dstnc btwn thm n ml. To mxmz dstnctvnss, th rpulson btwn thm n mnmzd. For th vowl systm s whol, th rpulson for ll th prs of vowls s smultnously mnmzd. 11. Optml vowl nvntors of vrous szs r prdctd: (from Lljncrnts & Lndblom, 1972)
5 12. Essntlly corrct pttrns r prdctd for 3 to 6 vowl systms. For lrgr systms (7 +), vrous rrors occur (ncludng th prdcton of too mny hgh cntrl vowls), though gnrlly not mor thn on pr systm, ccordng to L&L. Prcptul dstnctvnss (contrst) plys n mportnt, but not xclusv, rol s dtrmnnt of th structur of vowl systms. Howvr, thr r wknsss of Adptv Dsprson Thory sd from crtn spcfc ncorrct prdctons. It dosn t ddrss th ssu of why lngugs hv nvntors of vrous sz nvntors, or why thy would hv lrg nvntors. It dosn t xpln why thr s cross-lngug vrton n th dstrbuton of th sm numbr of vowls (mnng som lngugs must hv sub-optml nvntors). And t dosn t consdr ny ssus rltd to rtculton (s of rtculton, tc). 13. Lndblom lso dscusss th rlvnc of phontcs to th study of lngug, wth rspct to thory lk hs (nd, lthough h dosn t sy so, lk Quntl Thory s wll). Bfor L&L nd Stvns, phontcs hd mnly plyd th rol of ntrprtng lngustc form nto rlzbl physcl output. It s focus ws spch, rthr thn lngug. But Adptv Dsprson Thory (lk QT) sks to drv lngustc form s consqunc of th vrous mchnsms of spch communcton. Quntttv modls show how ths mchnsms ffct hghr-lvl lngustc nd communctv structur.
Preview. Graph. Graph. Graph. Graph Representation. Graph Representation 12/3/2018. Graph Graph Representation Graph Search Algorithms
/3/0 Prvw Grph Grph Rprsntton Grph Srch Algorthms Brdth Frst Srch Corrctnss of BFS Dpth Frst Srch Mnmum Spnnng Tr Kruskl s lgorthm Grph Drctd grph (or dgrph) G = (V, E) V: St of vrt (nod) E: St of dgs
8. Linear Contracts under Risk Neutrality
8. Lnr Contrcts undr Rsk Nutrlty Lnr contrcts r th smplst form of contrcts nd thy r vry populr n pplctons. Thy offr smpl ncntv mchnsm. Exmpls of lnr contrcts r mny: contrctul jont vnturs, quty jont vnturs,
Chapter 6 Student Lecture Notes 6-1
Chaptr 6 Studnt Lctur Nots 6-1 Chaptr Goals QM353: Busnss Statstcs Chaptr 6 Goodnss-of-Ft Tsts and Contngncy Analyss Aftr compltng ths chaptr, you should b abl to: Us th ch-squar goodnss-of-ft tst to dtrmn
Lecture 11 Waves in Periodic Potentials Today: Questions you should be able to address after today s lecture:
Lctur 11 Wvs in Priodic Potntils Tody: 1. Invrs lttic dfinition in 1D.. rphicl rprsnttion of priodic nd -priodic functions using th -xis nd invrs lttic vctors. 3. Sris solutions to th priodic potntil Hmiltonin
Convergence Theorems for Two Iterative Methods. A stationary iterative method for solving the linear system: (1.1)
Conrgnc Thors for Two Itrt Mthods A sttonry trt thod for solng th lnr syst: Ax = b (.) ploys n trton trx B nd constnt ctor c so tht for gn strtng stt x of x for = 2... x Bx c + = +. (.2) For such n trton
Last time: introduced our first computational model the DFA.
Lctur 7 Homwork #7: 2.2.1, 2.2.2, 2.2.3 (hnd in c nd d), Misc: Givn: M, NFA Prov: (q,xy) * (p,y) iff (q,x) * (p,) (follow proof don in clss tody) Lst tim: introducd our first computtionl modl th DFA. Tody
ST 524 NCSU - Fall 2008 One way Analysis of variance Variances not homogeneous
ST 54 NCSU - Fall 008 On way Analyss of varanc Varancs not homognous On way Analyss of varanc Exampl (Yandll, 997) A plant scntst masurd th concntraton of a partcular vrus n plant sap usng ELISA (nzym-lnkd
Analyzing Frequencies
Frquncy (# ndvduals) Frquncy (# ndvduals) /3/16 H o : No dffrnc n obsrvd sz frquncs and that prdctd by growth modl How would you analyz ths data? 15 Obsrvd Numbr 15 Expctd Numbr from growth modl 1 1 5
Minimum Spanning Trees
Mnmum Spnnng Trs Spnnng Tr A tr (.., connctd, cyclc grph) whch contns ll th vrtcs of th grph Mnmum Spnnng Tr Spnnng tr wth th mnmum sum of wghts 1 1 Spnnng forst If grph s not connctd, thn thr s spnnng
10/7/14. Mixture Models. Comp 135 Introduction to Machine Learning and Data Mining. Maximum likelihood estimation. Mixture of Normals in 1D
Comp 35 Introducton to Machn Larnng and Data Mnng Fall 204 rofssor: Ron Khardon Mxtur Modls Motvatd by soft k-mans w dvlopd a gnratv modl for clustrng. Assum thr ar k clustrs Clustrs ar not rqurd to hav
Instructions for Section 1
Instructions for Sction 1 Choos th rspons tht is corrct for th qustion. A corrct nswr scors 1, n incorrct nswr scors 0. Mrks will not b dductd for incorrct nswrs. You should ttmpt vry qustion. No mrks
Multi-Section Coupled Line Couplers
/0/009 MultiSction Coupld Lin Couplrs /8 Multi-Sction Coupld Lin Couplrs W cn dd multipl coupld lins in sris to incrs couplr ndwidth. Figur 7.5 (p. 6) An N-sction coupld lin l W typiclly dsign th couplr
Walk Like a Mathematician Learning Task:
Gori Dprtmnt of Euction Wlk Lik Mthmticin Lrnin Tsk: Mtrics llow us to prform mny usful mthmticl tsks which orinrily rquir lr numbr of computtions. Som typs of problms which cn b on fficintly with mtrics
A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex.
Lnr lgr Vctors gnrl -dmnsonl ctor conssts of lus h cn rrngd s column or row nd cn rl or compl Rcll -dmnsonl ctor cn rprsnt poston, loct, or cclrton Lt & k,, unt ctors long,, & rspctl nd lt k h th componnts
The Theory of Small Reflections
Jim Stils Th Univ. of Knss Dt. of EECS 4//9 Th Thory of Smll Rflctions /9 Th Thory of Smll Rflctions Rcll tht w nlyzd qurtr-wv trnsformr usg th multil rflction viw ot. V ( z) = + β ( z + ) V ( z) = = R
Filter Design Techniques
Fltr Dsgn chnqus Fltr Fltr s systm tht psss crtn frquncy componnts n totlly rcts ll othrs Stgs of th sgn fltr Spcfcton of th sr proprts of th systm ppromton of th spcfcton usng cusl scrt-tm systm Rlzton
Fundamentals of Continuum Mechanics. Seoul National University Graphics & Media Lab
Fndmntls of Contnm Mchncs Sol Ntonl Unvrsty Grphcs & Md Lb Th Rodmp of Contnm Mchncs Strss Trnsformton Strn Trnsformton Strss Tnsor Strn T + T ++ T Strss-Strn Rltonshp Strn Enrgy FEM Formlton Lt s Stdy
Lecture 14. Relic neutrinos Temperature at neutrino decoupling and today Effective degeneracy factor Neutrino mass limits Saha equation
Lctur Rlc nutrnos mpratur at nutrno dcoupln and today Effctv dnracy factor Nutrno mass lmts Saha quaton Physcal Cosmoloy Lnt 005 Rlc Nutrnos Nutrnos ar wakly ntractn partcls (lptons),,,,,,, typcal ractons
1.9 Cartesian Tensors
Scton.9.9 Crtsn nsors s th th ctor, hghr ordr) tnsor s mthmtc obct hch rprsnts mny physc phnomn nd hch xsts ndpndnty of ny coordnt systm. In ht foos, Crtsn coordnt systm s sd to dscrb tnsors..9. Crtsn
CSE303 - Introduction to the Theory of Computing Sample Solutions for Exercises on Finite Automata
CSE303 - Introduction to th Thory of Computing Smpl Solutions for Exrciss on Finit Automt Exrcis 2.1.1 A dtrministic finit utomton M ccpts th mpty string (i.., L(M)) if nd only if its initil stt is finl
22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 2: Derivation of Ideal MHD Equation
.65, MHD Thory of Fuson Systms Prof. Frdbrg Lctur : Drvton of Idl MHD Equton Rvw of th Drvton of th Momnt Equton. Strtng Pont: Boltzmnn Equton for lctrons, ons nd Mxwll Equtons. Momnts of Boltzmnn Equton:
Physics of Very High Frequency (VHF) Capacitively Coupled Plasma Discharges
Physcs of Vry Hgh Frquncy (VHF) Capactvly Coupld Plasma Dschargs Shahd Rauf, Kallol Bra, Stv Shannon, and Kn Collns Appld Matrals, Inc., Sunnyval, CA AVS 54 th Intrnatonal Symposum Sattl, WA Octobr 15-19,
Errata for Second Edition, First Printing
Errt for Scond Edition, First Printing pg 68, lin 1: z=.67 should b z=.44 pg 1: Eqution (.63) should rd B( R) = x= R = θ ( x R) p( x) R 1 x= [1 G( x)] = θp( R) + ( θ R)[1 G( R)] pg 15, problm 6: dmnd of
FSA. CmSc 365 Theory of Computation. Finite State Automata and Regular Expressions (Chapter 2, Section 2.3) ALPHABET operations: U, concatenation, *
CmSc 365 Thory of Computtion Finit Stt Automt nd Rgulr Exprssions (Chptr 2, Sction 2.3) ALPHABET oprtions: U, conctntion, * otin otin Strings Form Rgulr xprssions dscri Closd undr U, conctntion nd * (if
(A) the function is an eigenfunction with eigenvalue Physical Chemistry (I) First Quiz
96- Physcl Chmstry (I) Frst Quz lctron rst mss m 9.9 - klogrm, Plnck constnt h 6.66-4 oul scon Sp of lght c. 8 m/s, lctron volt V.6-9 oul. Th functon F() C[cos()+sn()] s n gnfuncton of /. Th gnvlu s (A)
Integration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals
Intgrtion Continud Intgrtion y Prts Solving Dinit Intgrls: Ar Undr Curv Impropr Intgrls Intgrtion y Prts Prticulrly usul whn you r trying to tk th intgrl o som unction tht is th product o n lgric prssion
Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1
CSC 00 Disrt Struturs : Introuon to Grph Thory Grphs Grphs CSC 00 Disrt Struturs Villnov Univrsity Grphs r isrt struturs onsisng o vrs n gs tht onnt ths vrs. Grphs n us to mol: omputr systms/ntworks mthml
Vowel package manual
Vwl pckg mnl FUKUI R Grdt Schl f Hmnts nd Sclgy Unvrsty f Tky 28 ctbr 2001 1 Drwng vwl dgrms 1.1 Th vwl nvrnmnt Th gnrl frmt f th vwl nvrnmnt s s fllws. [ptn(,ptn,)] cmmnds fr npttng vwls ptns nd cmmnds
Errata for Second Edition, First Printing
Errt for Scond Edition, First Printing pg 68, lin 1: z=.67 should b z=.44 pg 71: Eqution (.3) should rd B( R) = θ R 1 x= [1 G( x)] pg 1: Eqution (.63) should rd B( R) = x= R = θ ( x R) p( x) R 1 x= [1
Linear Algebra Existence of the determinant. Expansion according to a row.
Lir Algbr 2270 1 Existc of th dtrmit. Expsio ccordig to row. W dfi th dtrmit for 1 1 mtrics s dt([]) = (1) It is sy chck tht it stisfis D1)-D3). For y othr w dfi th dtrmit s follows. Assumig th dtrmit
More Foundations. Undirected Graphs. Degree. A Theorem. Graphs, Products, & Relations
Mr Funtins Grphs, Pruts, & Rltins Unirt Grphs An unirt grph is pir f 1. A st f ns 2. A st f gs (whr n g is st f tw ns*) Friy, Sptmr 2, 2011 Ring: Sipsr 0.2 ginning f 0.4; Stughtn 1.1.5 ({,,,,}, {{,}, {,},
This Week. Computer Graphics. Introduction. Introduction. Graphics Maths by Example. Graphics Maths by Example
This Wk Computr Grphics Vctors nd Oprtions Vctor Arithmtic Gomtric Concpts Points, Lins nd Plns Eploiting Dot Products CSC 470 Computr Grphics 1 CSC 470 Computr Grphics 2 Introduction Introduction Wh do
Chem 104A, Fall 2016, Midterm 1 Key
hm 104A, ll 2016, Mitrm 1 Ky 1) onstruct microstt tl for p 4 configurtion. Pls numrt th ms n ml for ch lctron in ch microstt in th tl. (Us th formt ml m s. Tht is spin -½ lctron in n s oritl woul writtn
Graphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari
Grphs CSC 1300 Disrt Struturs Villnov Univrsity Grphs Grphs r isrt struturs onsis?ng of vr?s n gs tht onnt ths vr?s. Grphs n us to mol: omputr systms/ntworks mthm?l rl?ons logi iruit lyout jos/prosss f
ERDOS-SMARANDACHE NUMBERS. Sabin Tabirca* Tatiana Tabirca**
ERDO-MARANDACHE NUMBER b Tbrc* Tt Tbrc** *Trslv Uvrsty of Brsov, Computr cc Dprtmt **Uvrsty of Mchstr, Computr cc Dprtmt Th strtg pot of ths rtcl s rprstd by rct work of Fch []. Bsd o two symptotc rsults
1. Stefan-Boltzmann law states that the power emitted per unit area of the surface of a black
Stf-Boltzm lw stts tht th powr mttd pr ut r of th surfc of blck body s proportol to th fourth powr of th bsolut tmprtur: 4 S T whr T s th bsolut tmprtur d th Stf-Boltzm costt= 5 4 k B 3 5c h ( Clcult 5
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
8-node quadrilateral element. Numerical integration
Fnt Elmnt Mthod lctur nots _nod quadrlatral lmnt Pag of 0 -nod quadrlatral lmnt. Numrcal ntgraton h tchnqu usd for th formulaton of th lnar trangl can b formall tndd to construct quadrlatral lmnts as wll
1 Introduction to Modulo 7 Arithmetic
1 Introution to Moulo 7 Arithmti Bor w try our hn t solvin som hr Moulr KnKns, lt s tk los look t on moulr rithmti, mo 7 rithmti. You ll s in this sminr tht rithmti moulo prim is quit irnt rom th ons w
ELEG 413 Lecture #6. Mark Mirotznik, Ph.D. Professor The University of Delaware
LG 43 Lctur #6 Mrk Mirtnik, Ph.D. Prfssr Th Univrsity f Dlwr mil: mirtni@c.udl.du Wv Prpgtin nd Plritin TM: Trnsvrs lctrmgntic Wvs A md is prticulr fild cnfigurtin. Fr givn lctrmgntic bundry vlu prblm,
Lecture contents. Bloch theorem k-vector Brillouin zone Almost free-electron model Bands Effective mass Holes. NNSE 508 EM Lecture #9
Lctur contnts Bloch thorm -vctor Brillouin zon Almost fr-lctron modl Bnds ffctiv mss Hols Trnsltionl symmtry: Bloch thorm On-lctron Schrödingr qution ch stt cn ccommo up to lctrons: If Vr is priodic function:
HIGHER ORDER DIFFERENTIAL EQUATIONS
Prof Enriqu Mtus Nivs PhD in Mthmtis Edution IGER ORDER DIFFERENTIAL EQUATIONS omognous linr qutions with onstnt offiints of ordr two highr Appl rdution mthod to dtrmin solution of th nonhomognous qution
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
Review - Probabilistic Classification
Mmoral Unvrsty of wfoundland Pattrn Rcognton Lctur 8 May 5, 6 http://www.ngr.mun.ca/~charlsr Offc Hours: Tusdays Thursdays 8:3-9:3 PM E- (untl furthr notc) Gvn lablld sampls { ɛc,,,..., } {. Estmat Rvw
CONTINUITY AND DIFFERENTIABILITY
MCD CONTINUITY AND DIFFERENTIABILITY NCERT Solvd mpls upto th sction 5 (Introduction) nd 5 (Continuity) : Empl : Chck th continuity of th function f givn by f() = + t = Empl : Emin whthr th function f
EECE 301 Signals & Systems Prof. Mark Fowler
EECE 301 Signals & Systms Prof. Mark Fowlr ot St #21 D-T Signals: Rlation btwn DFT, DTFT, & CTFT 1/16 W can us th DFT to implmnt numrical FT procssing This nabls us to numrically analyz a signal to find
The Hyperelastic material is examined in this section.
4. Hyprlastcty h Hyprlastc matral s xad n ths scton. 4..1 Consttutv Equatons h rat of chang of ntrnal nrgy W pr unt rfrnc volum s gvn by th strss powr, whch can b xprssd n a numbr of dffrnt ways (s 3.7.6):
Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari
snbrg Modl Sad Mohammad Mahd Sadrnhaad Survsor: Prof. bdollah Langar bstract: n ths rsarch w tr to calculat analtcall gnvalus and gnvctors of fnt chan wth ½-sn artcls snbrg modl. W drov gnfuctons for closd
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.
Chapter 16. 1) is a particular point on the graph of the function. 1. y, where x y 1
Prctic qustions W now tht th prmtr p is dirctl rltd to th mplitud; thrfor, w cn find tht p. cos d [ sin ] sin sin Not: Evn though ou might not now how to find th prmtr in prt, it is lws dvisl to procd
Spanning Tree. Preview. Minimum Spanning Tree. Minimum Spanning Tree. Minimum Spanning Tree. Minimum Spanning Tree 10/17/2017.
0//0 Prvw Spnnng Tr Spnnng Tr Mnmum Spnnng Tr Kruskl s Algorthm Prm s Algorthm Corrctnss of Kruskl s Algorthm A spnnng tr T of connctd, undrctd grph G s tr composd of ll th vrtcs nd som (or prhps ll) of
Minimum Spanning Trees
Minimum Spnning Trs Minimum Spnning Trs Problm A town hs st of houss nd st of rods A rod conncts nd only houss A rod conncting houss u nd v hs rpir cost w(u, v) Gol: Rpir nough (nd no mor) rods such tht:
Grand Canonical Ensemble
Th nsmbl of systms mmrsd n a partcl-hat rsrvor at constant tmpratur T, prssur P, and chmcal potntal. Consdr an nsmbl of M dntcal systms (M =,, 3,...M).. Thy ar mutually sharng th total numbr of partcls
Paths. Connectivity. Euler and Hamilton Paths. Planar graphs.
Pths.. Eulr n Hmilton Pths.. Pth D. A pth rom s to t is squn o gs {x 0, x 1 }, {x 1, x 2 },... {x n 1, x n }, whr x 0 = s, n x n = t. D. Th lngth o pth is th numr o gs in it. {, } {, } {, } {, } {, } {,
:2;$-$(01*%<*=,-./-*=0;"%/;"-*
!"#$%'()%"*#%*+,-./-*+01.2(.*3+456789*!"#$%"'()'*+,-."/0.%+1'23"45'46'7.89:89'/' ;8-,"$4351415,8:+#9' Dr. Ptr T. Gallaghr Astrphyscs Rsarch Grup Trnty Cllg Dubln :2;$-$(01*%
GUC (Dr. Hany Hammad) 9/28/2016
U (r. Hny Hd) 9/8/06 ctur # 3 ignl flow grphs (cont.): ignl-flow grph rprsnttion of : ssiv sgl-port dvic. owr g qutions rnsducr powr g. Oprtg powr g. vill powr g. ppliction to Ntwork nlyzr lirtion. Nois
TOPIC 5: INTEGRATION
TOPIC 5: INTEGRATION. Th indfinit intgrl In mny rspcts, th oprtion of intgrtion tht w r studying hr is th invrs oprtion of drivtion. Dfinition.. Th function F is n ntidrivtiv (or primitiv) of th function
Ch 1.2: Solutions of Some Differential Equations
Ch 1.2: Solutions of Som Diffrntil Equtions Rcll th fr fll nd owl/mic diffrntil qutions: v 9.8.2v, p.5 p 45 Ths qutions hv th gnrl form y' = y - b W cn us mthods of clculus to solv diffrntil qutions of
INF5820/INF9820 LANGUAGE TECHNOLOGICAL APPLICATIONS. Jan Tore Lønning, Lecture 4, 14 Sep
INF5820/INF9820 LANGUAGE TECHNOLOGICAL ALICATIONS Jn Tor Lønning Lctur 4 4 Sp. 206 tl@ii.uio.no Tody 2 Sttisticl chin trnsltion: Th noisy chnnl odl Word-bsd Trining IBM odl 3 SMT xpl 4 En kokk lgd n rtt
A Note on Estimability in Linear Models
Intrnatonal Journal of Statstcs and Applcatons 2014, 4(4): 212-216 DOI: 10.5923/j.statstcs.20140404.06 A Not on Estmablty n Lnar Modls S. O. Adymo 1,*, F. N. Nwob 2 1 Dpartmnt of Mathmatcs and Statstcs,
The van der Waals interaction 1 D. E. Soper 2 University of Oregon 20 April 2012
Th van dr Waals intraction D. E. Sopr 2 Univrsity of Orgon 20 pril 202 Th van dr Waals intraction is discussd in Chaptr 5 of J. J. Sakurai, Modrn Quantum Mchanics. Hr I tak a look at it in a littl mor
Soft k-means Clustering. Comp 135 Machine Learning Computer Science Tufts University. Mixture Models. Mixture of Normals in 1D
Comp 35 Machn Larnng Computr Scnc Tufts Unvrsty Fall 207 Ron Khardon Th EM Algorthm Mxtur Modls Sm-Suprvsd Larnng Soft k-mans Clustrng ck k clustr cntrs : Assocat xampls wth cntrs p,j ~~ smlarty b/w cntr
MASSACHUSETTS INSTITUTE OF TECHNOLOGY HAYSTACK OBSERVATORY WESTFORD, MASSACHUSETTS
VSRT MEMO #05 MASSACHUSETTS INSTITUTE OF TECHNOLOGY HAYSTACK OBSERVATORY WESTFORD, MASSACHUSETTS 01886 Fbrury 3, 009 Tlphon: 781-981-507 Fx: 781-981-0590 To: VSRT Group From: Aln E.E. Rogrs Subjct: Simplifid
More Statistics tutorial at 1. Introduction to mathematical Statistics
Mor Sttstcs tutorl t wwwdumblttldoctorcom Itroducto to mthmtcl Sttstcs Fl Soluto A Gllup survy portrys US trprurs s " th mvrcks, drmrs, d lors whos rough dgs d ucompromsg d to do t thr ow wy st thm shrp
Theoretical Study on the While Drilling Electromagnetic Signal Transmission of Horizontal Well
7 nd ntrntionl Confrnc on Softwr, Multimdi nd Communiction Enginring (SMCE 7) SBN: 978--6595-458-5 Thorticl Study on th Whil Drilling Elctromgntic Signl Trnsmission of Horizontl Wll Y-huo FAN,,*, Zi-ping
Study of Dynamic Aperture for PETRA III Ring K. Balewski, W. Brefeld, W. Decking, Y. Li DESY
Stud of Dnamc Aprtur for PETRA III Rng K. Balws, W. Brfld, W. Dcng, Y. L DESY FLS6 Hamburg PETRA III Yong-Jun L t al. Ovrvw Introducton Dnamcs of dampng wgglrs hoc of machn tuns, and optmzaton of stupol
(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely
. DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,
Lecture 12 Quantum chromodynamics (QCD) WS2010/11: Introduction to Nuclear and Particle Physics
Lctur Quntum chromodynmics (QCD) WS/: Introduction to Nuclr nd Prticl Physics QCD Quntum chromodynmics (QCD) is thory of th strong intrction - bsd on color forc, fundmntl forc dscribing th intrctions of
Section 5.1/5.2: Areas and Distances the Definite Integral
Scto./.: Ars d Dstcs th Dt Itgrl Sgm Notto Prctc HW rom Stwrt Ttook ot to hd p. #,, 9 p. 6 #,, 9- odd, - odd Th sum o trms,,, s wrtt s, whr th d o summto Empl : Fd th sum. Soluto: Th Dt Itgrl Suppos w
Page 1. Question 19.1b Electric Charge II Question 19.2a Conductors I. ConcepTest Clicker Questions Chapter 19. Physics, 4 th Edition James S.
ConTst Clikr ustions Chtr 19 Physis, 4 th Eition Jms S. Wlkr ustion 19.1 Two hrg blls r rlling h othr s thy hng from th iling. Wht n you sy bout thir hrgs? Eltri Chrg I on is ositiv, th othr is ngtiv both
Physics 256: Lecture 2. Physics
Physcs 56: Lctur Intro to Quantum Physcs Agnda for Today Complx Numbrs Intrfrnc of lght Intrfrnc Two slt ntrfrnc Dffracton Sngl slt dffracton Physcs 01: Lctur 1, Pg 1 Constructv Intrfrnc Ths wll occur
, between the vertical lines x a and x b. Given a demand curve, having price as a function of quantity, p f (x) at height k is the curve f ( x,
Clculus for Businss nd Socil Scincs - Prof D Yun Finl Em Rviw vrsion 5/9/7 Chck wbsit for ny postd typos nd updts Pls rport ny typos This rviw sht contins summris of nw topics only (This rviw sht dos hv
ME 522 PRINCIPLES OF ROBOTICS. FIRST MIDTERM EXAMINATION April 19, M. Kemal Özgören
ME 522 PINCIPLES OF OBOTICS FIST MIDTEM EXAMINATION April 9, 202 Nm Lst Nm M. Kml Özgörn 2 4 60 40 40 0 80 250 USEFUL FOMULAS cos( ) cos cos sin sin sin( ) sin cos cos sin sin y/ r, cos x/ r, r 0 tn 2(
Fractions. Mathletics Instant Workbooks. Simplify. Copyright
Frctons Stunt Book - Srs H- Smplfy + Mthltcs Instnt Workbooks Copyrht Frctons Stunt Book - Srs H Contnts Topcs Topc - Equvlnt frctons Topc - Smplfyn frctons Topc - Propr frctons, mpropr frctons n mx numbrs
a b c cat CAT A B C Aa Bb Cc cat cat Lesson 1 (Part 1) Verbal lesson: Capital Letters Make The Same Sound Lesson 1 (Part 1) continued...
Progrssiv Printing T.M. CPITLS g 4½+ Th sy, fun (n FR!) wy to tch cpitl lttrs. ook : C o - For Kinrgrtn or First Gr (not for pr-school). - Tchs tht cpitl lttrs mk th sm souns s th littl lttrs. - Tchs th
orbiting electron turns out to be wrong even though it Unfortunately, the classical visualization of the
Lctur 22-1 Byond Bohr Modl Unfortunatly, th classical visualization of th orbiting lctron turns out to b wrong vn though it still givs us a simpl way to think of th atom. Quantum Mchanics is ndd to truly
, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management
nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o
PH427/PH527: Periodic systems Spring Overview of the PH427 website (syllabus, assignments etc.) 2. Coupled oscillations.
Dy : Mondy 5 inuts. Ovrviw of th PH47 wsit (syllus, ssignnts tc.). Coupld oscilltions W gin with sss coupld y Hook's Lw springs nd find th possil longitudinl) otion of such syst. W ll xtnd this to finit
# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths.
How os it work? Pl vlu o imls rprsnt prts o whol numr or ojt # 0 000 Tns o thousns # 000 # 00 Thousns Hunrs Tns Ons # 0 Diml point st iml pl: ' 0 # 0 on tnth n iml pl: ' 0 # 00 on hunrth r iml pl: ' 0
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
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
Oppgavesett kap. 6 (1 av..)
Oppgvstt kp. 6 (1 v..) hns.brnn@go.uio.no Problm 1 () Wht is homognous nucltion? Why dos Figur 6.2 in th book show tht w won't gt homognous nucltion in th tmosphr? ˆ Homognous nucltion crts cloud droplts
Introduction to Condensed Matter Physics
Introduction to Condnsd Mattr Physics pcific hat M.P. Vaughan Ovrviw Ovrviw of spcific hat Hat capacity Dulong-Ptit Law Einstin modl Dby modl h Hat Capacity Hat capacity h hat capacity of a systm hld at
A Solution for multi-evaluator AHP
ISAHP Honoll Hw Jly 8- A Solton for lt-vltor AHP Ms Shnohr Kch Osw Yo Hd Nhon Unvrsty Nhon Unvrsty Nhon Unvrsty Iz-cho Nrshno Iz-cho Nrshno Iz-cho Nrshno hb 7-87 Jpn hb 7-87 Jpn M7snoh@ct.nhon-.c.p 7oosw@ct.nhon-.c.p
Section 3: Antiderivatives of Formulas
Chptr Th Intgrl Appli Clculus 96 Sction : Antirivtivs of Formuls Now w cn put th is of rs n ntirivtivs togthr to gt wy of vluting finit intgrls tht is ct n oftn sy. To vlut finit intgrl f(t) t, w cn fin
Present state Next state Q + M N
Qustion 1. An M-N lip-lop works s ollows: I MN=00, th nxt stt o th lip lop is 0. I MN=01, th nxt stt o th lip-lop is th sm s th prsnt stt I MN=10, th nxt stt o th lip-lop is th omplmnt o th prsnt stt I
Search sequence databases 3 10/25/2016
Sarch squnc databass 3 10/25/2016 Etrm valu distribution Ø Suppos X is a random variabl with probability dnsity function p(, w sampl a larg numbr S of indpndnt valus of X from this distribution for an
CIVL 8/ D Boundary Value Problems - Rectangular Elements 1/7
CIVL / -D Boundr Vlu Prolms - Rctngulr Elmnts / RECANGULAR ELEMENS - In som pplictions, it m mor dsirl to us n lmntl rprsnttion of th domin tht hs four sids, ithr rctngulr or qudriltrl in shp. Considr
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
h Summary Chapter 7.
Summry Chptr 7. In Chptr 7 w dscussd byond th fr lctron modl of chptr 6. In prtculrly w focusd on th nflunc of th prodc potntl of th on cors on th nrgy lvl dgrm of th outr lctrons of th toms. It wll hlp
SER/BER in a Fading Channel
SER/BER in a Fading Channl Major points for a fading channl: * SNR is a R.V. or R.P. * SER(BER) dpnds on th SNR conditional SER(BER). * Two prformanc masurs: outag probability and avrag SER(BER). * Ovrall,
Formal Concept Analysis
Forml Conpt Anlysis Conpt intnts s losd sts Closur Systms nd Implitions 4 Closur Systms 0.06.005 Nxt-Closur ws dvlopd y B. Gntr (984). Lt M = {,..., n}. A M is ltilly smllr thn B M, if B A if th smllst
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
Invariance and variability in articulation and acoustics of natural perturbed speech
Forschungsbrcht ds Insttuts für Phontk und Sprchlch Kommunkton dr Unvrstät Münchn (FIPKM) 38 (2001) 265-393 Invrnc nd vrblty n rtculton nd coustcs of nturl prturbd spch Anj Gumnn Insttut für Phontk und
6.1 Integration by Parts and Present Value. Copyright Cengage Learning. All rights reserved.
6.1 Intgration by Parts and Prsnt Valu Copyright Cngag Larning. All rights rsrvd. Warm-Up: Find f () 1. F() = ln(+1). F() = 3 3. F() =. F() = ln ( 1) 5. F() = 6. F() = - Objctivs, Day #1 Studnts will b
12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem)
12/3/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 Ciruits Cyl 2 Eulr
5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs
Prt 10. Grphs CS 200 Algorithms n Dt Struturs 1 Introution Trminology Implmnting Grphs Outlin Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 2 Ciruits Cyl A spil yl
INTEGRALS. Chapter 7. d dx. 7.1 Overview Let d dx F (x) = f (x). Then, we write f ( x)
Chptr 7 INTEGRALS 7. Ovrviw 7.. Lt d d F () f (). Thn, w writ f ( ) d F () + C. Ths intgrls r clld indfinit intgrls or gnrl intgrls, C is clld constnt of intgrtion. All ths intgrls diffr y constnt. 7..
22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.
Subjct Chmistry Papr No and Titl Modul No and Titl Modul Tag 8/ Physical Spctroscopy / Brakdown of th Born-Oppnhimr approximation. Slction ruls for rotational-vibrational transitions. P, R branchs. CHE_P8_M
However, many atoms can combine to form particular molecules, e.g. Chlorine (Cl) and Sodium (Na) atoms form NaCl molecules.
Lctur 6 Titl: Fundmntls of th Quntum Thory of molcul formtion Pg- In th lst modul, w hv discussd out th tomic structur nd tomic physics to undrstnd th spctrum of toms. Howvr, mny toms cn comin to form