Output Group Consensus for Heterogeneous Linear Multi-Agent Systems Communicating over Switching Topology

Size: px
Start display at page:

Download "Output Group Consensus for Heterogeneous Linear Multi-Agent Systems Communicating over Switching Topology"

Transcription

1 Output Group Consensus for Heterogeneous Lnear Mut-Agent Systems Communcatng over Swtchng Topoogy Jahu Qn Qchao Ma We Xng Zheng Department of Automaton Unversty of Scence and Technoogy of Chna Hefe 37 P R Chna E-ma: jhqn@ustceducn mqc4@maustceducn Schoo of Computng Engneerng and Mathematcs Western Sydney Unversty Sydney NSW 75 Austraa E-ma: wzheng@westernsydneyeduau Abstract: In ths paper we am to nvestgate the output group consensus probem for a swtchng network of heterogeneous near systems such that outputs of the agents synchronze wth each other n every custer From the nterna mode prncpe perspectve a necessary condton s frst derved n terms of the system dynamcs Wth ths necessary condton a dynamc controer s then desgned to sove the output group consensus probem n two steps namey consensus of reference generators and output trackng for each agent It s obtaned that f every possbe underyng topoogy of each custer contans a drected spannng tree then group consensus for the reference generators can be reazed wth suffcenty strong ntra-custer coupng strength An approprate controer s then desgned to force the output of each agent to track the output of the reference generators A smuaton exampe s gven at ast to vadate our theoretca fndngs Key Words: Output group consensus swtchng topoogy heterogeneous systems nterna mode prncpe Introducton Recenty nspred by the observaton that n the engneerng word a mut-agent system may consst of agents governng by dfferent system dynamcs especay wth dfferent dmensons the output consensus probem for heterogeneous mut-agent systems has drawn attenton of many researchers [4 3] As eaborated n [4 3] n achevng output synchronzaton there necessary exsts a reference generator whch generates the nontrva synchronzed trajectory In vew of ths to reaze the output consensus a- mong mutpe heterogeneous agents a dynamc controer s broady adopted Intutvey n eader-foowng consensus the dynamc controer drves the output of the foower systems to that of the exo-system [] Whe n eaderess consensus the dynamc controer generates the reference trajectory functon as exo-system for each system to track [4 3] Rea-word systems are usuay composed of severa nteractng custers of couped agents [] Then a more genera consensus probem termed group/custer consensus probem whch consders mutpe custers under genera coupng topoogy nvovng possbe negatve coupngs has aso receved growng attentons recenty [ ] It frequenty arses when agents wthn the same custer are cooperatve whe the agents from dfferent custers are repusve and/or cooperatve [7] In the group consensus probem the nvarance of consensus manfod a subspace n whch the states of agents wthn the same custer are dentca does not hod wth just dffusve coupngs For ths nvarance probem of neary couped nonnear systems [ 7] provde a necessary and suffcent common nter-custer coupng condton whch refers to the scenaro that the coupngs each agent n the same custer receves from any other custer sum up equay to guar- Ths work was supported n part by the Natona Natura Scence Foundaton of Chna under Grant the Youth Innovaton Promoton Assocaton of Chnese Academy of Scences and the Austraan Research Counc under Grant DP4986 antee the nvarance of the group consensus manfod Under ths condton ntensve research concernng group consensus probem for homogeneous mut-agent systems has been conducted [3 7] however for cooperatve networks Specfcay assumng that the coupngs each agent receves from any other custer sum up to zero whch naturay nvove repusve coupngs and s termed n-degree baanced condton group consensus for homogeneous mut-agent systems s nvestgated n [8 9 4] To date few research works have concentrated on group/custer consensus for heterogeneous mut-agent systems except for [6] where output custer consensus for heterogeneous near systems s studed under n-degree baanced condton based on the nterna mode prncpe Motvated by the above dscusson we am to further address the output group consensus probem for heterogeneous near mut-agent systems The contrbutons of ths paper are as foows The genera common nter-custer coupng condton whch aows for repusve coupngs between a- gents from dfferent custers s nvestgated From the vewpont of nterna mode prncpe a necessary condton concernng system dynamcs s derved A dstnct feature of such condton compared wth that n [3] es n that the nfuence brought by common nter-custer coupngs s expcty nvoved 3 We consder a genera framework such that the near mut-agent systems communcate over swtchng network topoogy n the presence of repusve coupngs 4 To address the consensus probem over swtchng topoogy a mutpe Lyapunov functon approach s apped and structura condtons wth respect to network structure and ntracuster coupng strength are provded An nterestng and consstent concuson wth those eaborated n [8 9] s fnay made that f each custer contans a drected spannng tree at each nstant and moreover the ntra-custer coupng strength s strong enough then the reference generators are synchronzed wthn each custer The remander of the paper s arranged nto fve sectons In Secton we ntroduce reevant graph notons and formu-

2 ate the probem The man resuts concernng output group consensus are presented n Sectons 3 and 4 foowed by an ustratve exampe n Secton 5 The paper s fnay wrapped up wth concudng remarks n Secton 6 Notatons: Let I n be the dentty matrx and n n the zero matrx n R n n dag{a a q } denotes the dagona matrx wth a beng the -th dagona eement The spectrum of a square matrx A denoted by σa s the set of a egenvaues of A The magnary axs s denoted by jr Premnary Graph Notons The nteracton topoogy s represented by a drected graph G = V E A of order N wth a fnte nonempty set of nodes V = { N} a set of edges E V V and a weghted adjacency matrx A = [ ] a j R N N where a j s the weght aso caed coupng strength n ths work of the drected edge j satsfyng a j f j s an edge of G and a j = otherwse Moreover assume a = for a V to avod sef-oops Note that a j for nter-custer coupngs can be ether postve or negatve correspondng respectvey to the cooperatve and compettve nteractons The Lapacan matrx L of G = V E A s defned as L = dag{ N } A where = N j= a j = N [] A drected path s a sequence of edges n a drected graph of the form 3 q q A dgraph has a drected spannng tree f there exsts at east one node caed the root havng a drected path to every other node The nteracton graph G s swtchng among fnte gven dgraphs Gven an nfnte sequence of consecutve nonoverappng tme nterva [t k t k+ k N wth t = t k+ t k > τ where τ s caed the dwe tme and across whch the nteracton topoogy s fxed The tme sequence t t s caed the swtchng sequence at whch the nteracton topoogy changes Let G σt be the nteracton graph at tme t wth σt : [ + { p} Hence t s assumed that Gt swtches among p dfferent nteracton graphs { G G p} System Mode and Probem of Interest Consder a group of N agents governed by heterogeneous near system dynamcs: ẋ t = A x t + B u t y t = C x t = N where x = [x xn ] T R n u R m and y R p are respectvey the state nput and output of agent A R n n B R n m C R p n In what foows at no oss of generaty assume that the N nodes each representng a heterogeneous near system are dvded nto q q > dsjont custers namey V V q such that q = V = V and the number of nodes n a custer say V s N q These N nodes can be abeed n such a way that they are ndexed as j= N j + j= N j where N = e V = { j= N j + j= N j} Let ī denote the subscrpt of the custer whch node beongs to e V ī and G be the underyng topoogy of custer V = q e VG = V For ater use defne κ = κ = p= N p Output Group Consensus Probem: Desgn approprate contro aws u for = N as foows ζ = F ζ + O y + G e ζ + ey a u = K x t + K ζ t + G e ζ + ey b where ζ R m e ζ = N j= aσt j ζ j ζ e y = N j= aσt j y j y such that for any nta states of the heterogeneous system there hods m t y t y j t = ī = j j = N In ths paper our am s to ntroduce approprate controers and derve suffcent condtons to sove the above output group consensus probem To ths purpose a prerequste requrement s that the group consensus manfod S = { [x T xt N ]T : C x = C j x j ī = j } shoud be nvarant for heterogeneous system couped through a and b As eaborated n [] and [7] a necessary and suffcent condton for S to be nvarant through neary couped ordnary dfferenta equaton s that the common nter-custer coupng condton s satsfed e a σt j j V = d σt k V k k = q k 3 where d σt k s a constant rreevant to the choce of and j n custers V k and V respectvey Ths means for agents wthn the same custer the sums of the weght of the ncomng coupngs from any of the other custer are the same Throughout ths paper ths common nter-custer condton s adopted Under the common nter-custer coupng condton the Lapacan matrx L σt = [ σt j ] N N of G σt s wrtten as foows L σt + D σt L σt q L σt = L σt q L σt qq + D σt q where L σt k coupngs from custer V k to custer V D σt k = q k specfes the nter-custer = d σt I N = represents q j= j dσt j I N for = q Note that L σt the Lapacan matrx of G σt 3 Interna Mode Prncpe In ths secton we frst present a premnary resut whch s the fundamenta ngredent of our man resut Ths premnary resut extends that presented n [3] for compete consensus to the case where group consensus s taken nto consderaton Insertng a and b nto yeds ẋ t = A x + B K x + B K ζ + B G e ζ + ey 4a ζ t = F ζ + O y + G e ζ + ey 4b whch can be equvaenty transformed nto the foowng compact form { ˆx = Â ˆx + ˆBe ˆx 5a ŷ = Ĉ ˆx 5b

3 where ˆx = [ ˆx T ˆxT N ]T ˆx = [x T ζt ]T  ˆB and Ĉ are bock dagona matrces wth each bock beng [ ] [ ] A + B  = K B K B G ˆB O C F = Ĉ G = [ C ] In terms of group consensus for 5a and 5b the foowng resut extends the nterna mode prncpe proposed n [3] For the sake of brevty the network topoogy s assumed to be fxed n the next theorem e we use j nstead of σt j Theorem Consder N near state-space modes couped through dynamc controers a and b If y y j and ζ ζ j as t for ī = j j = N then there exst a scaar m matrces S R m m and R R p m = q where σs C + and S R s observabe and matrces Π R n m Γ R p m and Λ R m m such that A Π + B Γ + j Λ j = Π S 6a C Π = R j= 6b Furthermore there exsts z R m such that m y t R e S t z = 7 t V = q Proof Snce y y j and ζ ζ j as t system 5a has an attractve nvarant subspace M where C j x j = C x and ζ j = ζ for j V = q Reca that the common nter-custer coupng condton s mposed on M one hence has ˆx =  ˆB L I p+m C ˆx 8 where C = dag{ C C q } Foowng the anayss n [3] assume at no oss of generaty that M contans no exponentay stabe modes contans ony modes that are observabe at the output and 3 s non-trva wth dmenson m In vew of such assumpton there exsts a matrx S R m m such that  ˆB L I p+m C Φ = ΦS Partton Φ nto One then has  [Π T ΣT ]T ˆB Φ = [Π T ΣT ΠT N ΣT N ]T j C j Π j + Σ j = [Π T Σ T ]T S j= ths competng the frst part of the proof wth Γ = K Π + K Σ and Λ j = G C j Π j + Σ j Next we w prove that C Π = R V Snce y = y j one has C Π = C j Π j j V Then there exsts some matrx R such that C Π = R V for = q By the fact that modes n M are observabe at the output one has S R s observabe for = q It s aways [ possbe ] to fnd a transformaton matrx T = [Φ Σ] such S that T ÂT = where σs C H + and H s Hurwtz Remark The couped term N j= jλ j n 6a arses from the empoyment of e ζ and e y n 4a If the atter two terms e ζ and e y are removed n controer desgn then 6a reduces to the form obtaned n [3] 4 Output Group Consensus Usng Reatve Controer State In ths secton we w sove the output group consensus probem by desgnng approprate contro aws u = N To resove ths group consensus probem we frst ntroduce an assumpton whch s requred such that the probem s feasbe based on the necessary condton proposed n the precedng secton Smar condtons can aso be found n [5 3] Assumpton For each V = q there exst compatbe matrces Γ Π and Ψ such that A Π + B Γ = Π S C Π = R 9 B Ψ = Π where S R m m R R p m σs jr Remark The frst two condtons n Assumpton are broady used n the exstng terature concernng consensus of heterogeneous near systems [] Intutvey these two condtons requre that a the system matrces contan a common egen-space whch s refected by the matrx S The states of the agents n each custer are fnay controed nto the common egen-space The thrd condton s made to factate the controer desgn such that the nfuence from common nter-custer coupngs can be compensated Inspred by Remark we consder the foowng reference generator for each agent V = q ζ t = S ζ t where ζ R m These types of generators produce trajectores for agents n each custer to track To synchronze the above reference generators n each custer we consder the foowng dstrbuted contro protoco for agent V = q ζ t = S ζ t + j= H ī c j a σt j ζ j t ζ t where c j = c ī = j = otherwse c j = ; H ī s to be desgned ater In the seque we ca c the ntra-custer coupng strength whch s used to refect strong versus weak coupngs To track the trajectores of the reference generators for each agent the foowng feedback controer s expoted x t = A x t + B u t + H ỹ t y t a u t = K x t + K ζ t + Ψ j= c j σt j ζ j b for V = q where a s a Luenberger observer The feedback controer b uses the nformaton from the Luenberger observer and the reference generators

4 The controer of the above form can be seen as extenson of those proposed n [3] In ths paper we choose K as K and K = K Π + Γ where K s to be determned Next we w prove that output group consensus for heterogeneous system can be acheved va a and b In what foows we frst prove that the reference generators couped as n can reaze group consensus exponentay fast Then by dynamc controer a b we w show that the output of each agent tracks that of ts correspondng reference generator thereby eadng to output group consensus 4 Group Consensus for Couped Reference Generators In ths subsecton we w show that the couped reference generators acheve group consensus n an exponenta manner To ths purpose we transform the group consensus probem nto a stabty probem by ntroducng proper error varabes Then the stabty anayss s performed wth respect to the error system dynamcs Frst we ntroduce some notatons Let Lσt k k = q k be the sub-matrx of the foowng matrx [ ] L σt k dk k = N Lσt k [ ] N where = dag{ q } = N I N Suppose that the underyng topoogy of each custer contans a drected spannng tree durng each nterva [t k t k+ k = a postve defnte matrx say σt k correspondng to Lσt k exsts such that Lσt k T σt k σt k L σt k < Let N σt k = dag{c σt k L σt k + Lσt k T σt k c q σt k q L σt k qq + L σt kt qq σt k q } N σt k = Lσt k T σtk + σt k Lσt k N σtk where σtk = dag{ σt k σt k q } Now we are ready to present our resut Lemma Suppose that the common nter-custer coupng condton 3 s satsfed If for each t k = the underyng graph G σt k of each custer contans a drected s- pannng tree and ntra-custer coupng strength c = q satsfes c > γλ max P + λ max PS + S T P φλ mn P ηλ mn P 3 then group consensus for the couped generators can be acheved exponentay fast wth γ > satsfyng the foowng nequates { PS + S T P c η + φ PP γp nκ γτ < where P s symmetrc postve defnte κ satsfes λ max σt k+ P < κλ mn σt k P for t k = φ and η > are defned such that λ mn N σt k φλ max σt k σt k L σt k + Lσt k T σt k η σt k = q Proof See Appendx for the detaed proof Remark 3 In the statement of Lemma the varabes φ κ and η are we defned n ght of that there are fnte dfferent topooges for the communcaton network to take 4 Output Group Consensus va Dynamc Controer Based on the resut estabshed n the precedng subsecton n what foows we sha prove that the output group consensus s asymptotcay acheved for heterogeneous systems Especay we w show that each heterogeneous near system tracks the trajectory of the correspondng reference generator Theorem Under Assumpton suppose that the condtons stated n Lemma hod Then the output group consensus for mut-agent system can be acheved through dynamc controer a and b where K and H are desgned such that A + B K and A + H C are Hurwtz for = N Proof Defne error varabes ɛ = x Π ζ and ν = x x One has ɛ =A + B K ɛ B K ν ν =A + H C ν for = N Snce A + H s Hurwtz ν tends to zero as tme approaches nfnty at an exponenta rate Reca that K s desgned such that A + B K s Hurwtz t s therefore concuded that ɛ reaches zero exponentay fast for = N Next we w verfy output consensus Bearng the above concuson n mnd t can be obtaned that x Π ζ and x x exponentay fast as tme tends to nfnty Recang the fact that y = C x by Assumpton one has y C Π ζ = R ζ exponentay fast Snce ζ ζ j ī = j = accordng to Lemma y y j ī = j = the resut s vad 5 An Iustratve Exampe In ths secton we present an exampe to ustrate our theoretca fndngs Exampe : Consder the fve near systems movng on the pane wth two possbe network topooges shown n Fg The communcaton graph swtches from graph a to graph b perodcay wth a perod T = s Two custers are consdered n ths exampe such that V = { } V = {3 4 5} The systems dynamcs are chosen such that 3 A = B = C = 3 5 A = B = C 9 = A 3 = B = C 3 = A 4 = B 4 = C 4 = [ ] [ ] 3 5 A 5 = B 4 5 = C +3 5 = 5 [ ] 3 3

5 e t y t y t y t y t a b Fg : Two dfferent nteracton topooges among fve heterogeneous agents Underyng topoogy of each custer contans a drected spannng tree The nter-custer coupngs satsfy n-degree baanced condton wth d = d = S = By computaton one has [ ] 3 R = [ ] S = 4 4 [ ] 3 5 R 3 3 = [ ] The nta vaues of the agents are randomy chosen from nterva [ ] [ ] R The output trajectores of the fve agents are shown n Fg Whe the output trackng error s depcted n Fg 3 It s observed obvousy that group consensus s acheved asymptotcay - custer custer Tme 3 custer custer Tme a D pot of the output trajectores of the fve agents - custer T=s T=5s T=s y t - custer T=s T=s T=5s y t b D pot of the output trajectores of the fve agents Fg : The output trajectores of y T = [y y ] = 5 It s observed that group consensus s asymptotcay acheved 6 Concuson 8 custer custer In ths paper we have nvestgated the output group consensus contro for a network of heterogeneous near systems communcatng over swtchng topoogy A necessary condton has been derved n terms of the system dynamcs wth whch a dynamc controer s then desgned to sove the output group consensus probem n two separatve steps: consensus of reference generators; and output trackng for each agent An approprate controer s then proposed n order to track the output of the reference generators to reaze group consensus The smuaton has vadated the effectveness of our theoretca fndngs Future works nvove further dscussons on how ntercuster coupngs nfuence the evouton of the reference generators and reaxaton of the assumpton mposed on system dynamcs Tme Fg 3: The trackng error trajectores of e = y R ī ζ = 5 It s cear that the trackng error asymptotcay vanshes

6 7 Appendx: Proof of Lemma In ths proof we consder a genera system dynamcs for every V ζ t = S ζ t + j= H ī c j a σt j ζ j t ζ t 5 Pre-mutpyng the above system wth I m and notng that = I N for = q one then arrves at δ =dag { I N S I Nq S q } δ [ Lσt I m ] dag { IN H I Nq H q } δ 6 where δ = [ζ κ + ζ κ + T ζ κ + ζ κ T ] T δ = [ δ T δ T q ] T Lσt takes the foowng form L σt = c Lσt + D σt Lσt q L σt q c Lσt q qq + D σt q 7 σt k P δ t [t k t k+ Evdenty group consensus s asymptotcay acheved f system 6 s asymptotcay stabe Now consder the foowng Lyapunov functon canddate for the error system dynamcs 6: Vt = q = δt Choosng H ī = P for V and takng the dervatve of Vt aong the trajectory of error system dynamcs 6 gves Vt = = = δ T δ T σt k P S δ [ c σt k L σt k + σt k δ T = j= j σt k L σt k j P P j δ j ] D σt k P P δ Let us frst consder the ast two terms n the dervatve of Vt Defne y t = I N P δ then one has δ T = j= j + = δ T σt k =y T [ N σt k I m ] y σt k L σt k j P P j δ j D σt k φy T σt k I m y = φ P P δ = Therefore one obtans the foowng nequaty V = γ δ T = δ T σt k P P δ 8 σt k [ P S + S T P c η + φ P ] δ δ T where t s assumed that σt k P δ = γv 9 Hence Vt e γt t k Vt k for t [t k t k+ For any t > t s aways possbe to fnd an nteger s such that t s t < t s+ Therefore one has Vt exp γt ts Vt s exp γt ts exp nκ γt s t s Vt s s exp γt t s + nκ γt j t j Vt If nκ γτ < hods then one has δt as t + exponentay fast Ths competes the proof References [] V N Beykh I V Beykh and E Mosekde Custer synchronzaton modes n an ensembe of couped chaotc oscators Phys Rev E 633: [] C Gods and G Doye Agebrac Graph Theory New York: Sprnger [3] Y Han W Lu and T Chen Achevng custer consensus n contnuous-tme networks of mut-agents wth ntercuster non-dentca nputs IEEE Trans Autom Contro 63: [4] A Isdor L Marcon and G Casade Robust output synchronzaton of a network of heterogeneous nonnear agents va nonnear reguaton theory IEEE Trans Autom Contro 59: [5] M Ja Enhancng synchronzabty of dffusvey couped dynamca networks: a survey IEEE Trans Neura Netw Learn Syst 47: 9 3 [6] Z Lu and W S Wong Output custer synchronzaton of heterogeneous near mut-agent systems n Proc 54th IEEE Conf Decson Contro Osaka Japan 5 pp [7] W Lu B Lu and T Chen Custer synchronzaton n networks of couped nondentca dynamca systems Chaos : 3 [8] J Qn H Gao and W X Zheng Exponenta synchronzaton of compex networks of near systems and nonnear oscators: a unfed anayss IEEE Trans Neura Netw Learn Syst 63: [9] J Qn and C Yu Custer consensus contro of generc near mut-agent systems under drected topoogy wth acycc partton Automatca 499: [] J Qn C Yu and B D O Anderson On eaderess and eader-foowng consensus for nteractng custers of doubentegrator mut-agent systems Automatca 74: 4 6 [] Y Su and J Huang Cooperatve output reguaton of near mut-agent systems IEEE Trans Autom Contro 574: 6 66 [] A T Wnfree The Geometry of Boogca Tme Sprnger- Verag New York 98 [3] P Weand R Sepuchre and F Agöwer An nterna mode prncpe s necessary and suffcent for output synchronzaton Automatca 475: [4] J Yu and L Wang Group consensus n mut-agent systems wth swtchng topooges and communcaton deays Syst Contro Lett 596: [5] H Hu W Yu G Wen Q Xuan and J Cao Reverse group consensus of mut-agent systems n the cooperatoncompetton network IEEE Trans Crcut Syst-II: Exp Bref 63: j= P S + S T P c η + φ P < γp

Research on Complex Networks Control Based on Fuzzy Integral Sliding Theory

Research on Complex Networks Control Based on Fuzzy Integral Sliding Theory Advanced Scence and Technoogy Letters Vo.83 (ISA 205), pp.60-65 http://dx.do.org/0.4257/ast.205.83.2 Research on Compex etworks Contro Based on Fuzzy Integra Sdng Theory Dongsheng Yang, Bngqng L, 2, He

More information

A finite difference method for heat equation in the unbounded domain

A finite difference method for heat equation in the unbounded domain Internatona Conerence on Advanced ectronc Scence and Technoogy (AST 6) A nte derence method or heat equaton n the unbounded doman a Quan Zheng and Xn Zhao Coege o Scence North Chna nversty o Technoogy

More information

Optimal Guaranteed Cost Control of Linear Uncertain Systems with Input Constraints

Optimal Guaranteed Cost Control of Linear Uncertain Systems with Input Constraints Internatona Journa Optma of Contro, Guaranteed Automaton, Cost Contro and Systems, of Lnear vo Uncertan 3, no Systems 3, pp 397-4, wth Input September Constrants 5 397 Optma Guaranteed Cost Contro of Lnear

More information

Note 2. Ling fong Li. 1 Klein Gordon Equation Probablity interpretation Solutions to Klein-Gordon Equation... 2

Note 2. Ling fong Li. 1 Klein Gordon Equation Probablity interpretation Solutions to Klein-Gordon Equation... 2 Note 2 Lng fong L Contents Ken Gordon Equaton. Probabty nterpretaton......................................2 Soutons to Ken-Gordon Equaton............................... 2 2 Drac Equaton 3 2. Probabty nterpretaton.....................................

More information

Networked Cooperative Distributed Model Predictive Control Based on State Observer

Networked Cooperative Distributed Model Predictive Control Based on State Observer Apped Mathematcs, 6, 7, 48-64 ubshed Onne June 6 n ScRes. http://www.scrp.org/journa/am http://dx.do.org/.436/am.6.73 Networed Cooperatve Dstrbuted Mode redctve Contro Based on State Observer Ba Su, Yanan

More information

Dynamic Systems on Graphs

Dynamic Systems on Graphs Prepared by F.L. Lews Updated: Saturday, February 06, 200 Dynamc Systems on Graphs Control Graphs and Consensus A network s a set of nodes that collaborates to acheve what each cannot acheve alone. A network,

More information

Delay tomography for large scale networks

Delay tomography for large scale networks Deay tomography for arge scae networks MENG-FU SHIH ALFRED O. HERO III Communcatons and Sgna Processng Laboratory Eectrca Engneerng and Computer Scence Department Unversty of Mchgan, 30 Bea. Ave., Ann

More information

Changing Topology and Communication Delays

Changing Topology and Communication Delays Prepared by F.L. Lews Updated: Saturday, February 3, 00 Changng Topology and Communcaton Delays Changng Topology The graph connectvty or topology may change over tme. Let G { G, G,, G M } wth M fnte be

More information

Distributed Moving Horizon State Estimation of Nonlinear Systems. Jing Zhang

Distributed Moving Horizon State Estimation of Nonlinear Systems. Jing Zhang Dstrbuted Movng Horzon State Estmaton of Nonnear Systems by Jng Zhang A thess submtted n parta fufment of the requrements for the degree of Master of Scence n Chemca Engneerng Department of Chemca and

More information

L-Edge Chromatic Number Of A Graph

L-Edge Chromatic Number Of A Graph IJISET - Internatona Journa of Innovatve Scence Engneerng & Technoogy Vo. 3 Issue 3 March 06. ISSN 348 7968 L-Edge Chromatc Number Of A Graph Dr.R.B.Gnana Joth Assocate Professor of Mathematcs V.V.Vannaperuma

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

Interference Alignment and Degrees of Freedom Region of Cellular Sigma Channel

Interference Alignment and Degrees of Freedom Region of Cellular Sigma Channel 2011 IEEE Internatona Symposum on Informaton Theory Proceedngs Interference Agnment and Degrees of Freedom Regon of Ceuar Sgma Channe Huaru Yn 1 Le Ke 2 Zhengdao Wang 2 1 WINLAB Dept of EEIS Unv. of Sc.

More information

Decentralized Adaptive Control for a Class of Large-Scale Nonlinear Systems with Unknown Interactions

Decentralized Adaptive Control for a Class of Large-Scale Nonlinear Systems with Unknown Interactions Decentrazed Adaptve Contro for a Cass of Large-Scae onnear Systems wth Unknown Interactons Bahram Karm 1, Fatemeh Jahangr, Mohammad B. Menhaj 3, Iman Saboor 4 1. Center of Advanced Computatona Integence,

More information

NP-Completeness : Proofs

NP-Completeness : Proofs NP-Completeness : Proofs Proof Methods A method to show a decson problem Π NP-complete s as follows. (1) Show Π NP. (2) Choose an NP-complete problem Π. (3) Show Π Π. A method to show an optmzaton problem

More information

G : Statistical Mechanics

G : Statistical Mechanics G25.2651: Statstca Mechancs Notes for Lecture 11 I. PRINCIPLES OF QUANTUM STATISTICAL MECHANICS The probem of quantum statstca mechancs s the quantum mechanca treatment of an N-partce system. Suppose the

More information

MARKOV CHAIN AND HIDDEN MARKOV MODEL

MARKOV CHAIN AND HIDDEN MARKOV MODEL MARKOV CHAIN AND HIDDEN MARKOV MODEL JIAN ZHANG JIANZHAN@STAT.PURDUE.EDU Markov chan and hdden Markov mode are probaby the smpest modes whch can be used to mode sequenta data,.e. data sampes whch are not

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

3. Stress-strain relationships of a composite layer

3. Stress-strain relationships of a composite layer OM PO I O U P U N I V I Y O F W N ompostes ourse 8-9 Unversty of wente ng. &ech... tress-stran reatonshps of a composte ayer - Laurent Warnet & emo Aerman.. tress-stran reatonshps of a composte ayer Introducton

More information

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016 U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and

More information

DIOPHANTINE EQUATIONS WITH BINOMIAL COEFFICIENTS AND PERTURBATIONS OF SYMMETRIC BOOLEAN FUNCTIONS

DIOPHANTINE EQUATIONS WITH BINOMIAL COEFFICIENTS AND PERTURBATIONS OF SYMMETRIC BOOLEAN FUNCTIONS DIOPHANTINE EQUATIONS WITH BINOMIAL COEFFICIENTS AND PERTURBATIONS OF SYMMETRIC BOOLEAN FUNCTIONS FRANCIS N CASTRO, OSCAR E GONZÁLEZ, AND LUIS A MEDINA Abstract Ths work presents a study of perturbatons

More information

Andre Schneider P622

Andre Schneider P622 Andre Schneder P6 Probem Set #0 March, 00 Srednc 7. Suppose that we have a theory wth Negectng the hgher order terms, show that Souton Knowng β(α and γ m (α we can wrte β(α =b α O(α 3 (. γ m (α =c α O(α

More information

Example: Suppose we want to build a classifier that recognizes WebPages of graduate students.

Example: Suppose we want to build a classifier that recognizes WebPages of graduate students. Exampe: Suppose we want to bud a cassfer that recognzes WebPages of graduate students. How can we fnd tranng data? We can browse the web and coect a sampe of WebPages of graduate students of varous unverstes.

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

The lower and upper bounds on Perron root of nonnegative irreducible matrices

The lower and upper bounds on Perron root of nonnegative irreducible matrices Journal of Computatonal Appled Mathematcs 217 (2008) 259 267 wwwelsevercom/locate/cam The lower upper bounds on Perron root of nonnegatve rreducble matrces Guang-Xn Huang a,, Feng Yn b,keguo a a College

More information

Games of Threats. Elon Kohlberg Abraham Neyman. Working Paper

Games of Threats. Elon Kohlberg Abraham Neyman. Working Paper Games of Threats Elon Kohlberg Abraham Neyman Workng Paper 18-023 Games of Threats Elon Kohlberg Harvard Busness School Abraham Neyman The Hebrew Unversty of Jerusalem Workng Paper 18-023 Copyrght 2017

More information

Perron Vectors of an Irreducible Nonnegative Interval Matrix

Perron Vectors of an Irreducible Nonnegative Interval Matrix Perron Vectors of an Irreducble Nonnegatve Interval Matrx Jr Rohn August 4 2005 Abstract As s well known an rreducble nonnegatve matrx possesses a unquely determned Perron vector. As the man result of

More information

5 The Rational Canonical Form

5 The Rational Canonical Form 5 The Ratonal Canoncal Form Here p s a monc rreducble factor of the mnmum polynomal m T and s not necessarly of degree one Let F p denote the feld constructed earler n the course, consstng of all matrces

More information

ON AUTOMATIC CONTINUITY OF DERIVATIONS FOR BANACH ALGEBRAS WITH INVOLUTION

ON AUTOMATIC CONTINUITY OF DERIVATIONS FOR BANACH ALGEBRAS WITH INVOLUTION European Journa of Mathematcs and Computer Scence Vo. No. 1, 2017 ON AUTOMATC CONTNUTY OF DERVATONS FOR BANACH ALGEBRAS WTH NVOLUTON Mohamed BELAM & Youssef T DL MATC Laboratory Hassan Unversty MORO CCO

More information

Supplementary Material: Learning Structured Weight Uncertainty in Bayesian Neural Networks

Supplementary Material: Learning Structured Weight Uncertainty in Bayesian Neural Networks Shengyang Sun, Changyou Chen, Lawrence Carn Suppementary Matera: Learnng Structured Weght Uncertanty n Bayesan Neura Networks Shengyang Sun Changyou Chen Lawrence Carn Tsnghua Unversty Duke Unversty Duke

More information

Containment Control for First-Order Multi-Agent Systems with Time-Varying Delays and Uncertain Topologies

Containment Control for First-Order Multi-Agent Systems with Time-Varying Delays and Uncertain Topologies Commun. heor. Phys. 66 (06) 49 55 Vol. 66, No., August, 06 Contanment Control for Frst-Order Mult-Agent Systems wth me-varyng Delays and Uncertan opologes Fu-Yong Wang ( ), Hong-Yong Yang ( ), Shu-Nng

More information

Adaptive Consensus Control of Multi-Agent Systems with Large Uncertainty and Time Delays *

Adaptive Consensus Control of Multi-Agent Systems with Large Uncertainty and Time Delays * Journal of Robotcs, etworkng and Artfcal Lfe, Vol., o. (September 04), 5-9 Adaptve Consensus Control of Mult-Agent Systems wth Large Uncertanty and me Delays * L Lu School of Mechancal Engneerng Unversty

More information

SL n (F ) Equals its Own Derived Group

SL n (F ) Equals its Own Derived Group Internatonal Journal of Algebra, Vol. 2, 2008, no. 12, 585-594 SL n (F ) Equals ts Own Derved Group Jorge Macel BMCC-The Cty Unversty of New York, CUNY 199 Chambers street, New York, NY 10007, USA macel@cms.nyu.edu

More information

Monica Purcaru and Nicoleta Aldea. Abstract

Monica Purcaru and Nicoleta Aldea. Abstract FILOMAT (Nš) 16 (22), 7 17 GENERAL CONFORMAL ALMOST SYMPLECTIC N-LINEAR CONNECTIONS IN THE BUNDLE OF ACCELERATIONS Monca Purcaru and Ncoeta Adea Abstract The am of ths paper 1 s to fnd the transformaton

More information

arxiv: v2 [cs.sy] 19 Sep 2018

arxiv: v2 [cs.sy] 19 Sep 2018 Synchronzaton of Kuramoto oscators n a bdrectona frequency-dependent tree network Matn Jafaran, Xne Y, Mohammad Pran, Henrk Sandberg, Kar Henrk Johansson arxv:189.6331v [cs.sy] 19 Sep 18 Abstract Ths paper

More information

Formation Control and Collision Avoidance for Multi-Agent Systems and a Connection between Formation Infeasibility and Flocking Behavior

Formation Control and Collision Avoidance for Multi-Agent Systems and a Connection between Formation Infeasibility and Flocking Behavior Formaton Contro and Coson Avodance for Mut-Agent Systems and a Connecton between Formaton Infeasbty and Focng Behavor Dmos V Dmarogonas and Kostas J Kyraopouos Abstract A feedbac contro strategy that acheves

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS

THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS Dscussones Mathematcae Graph Theory 27 (2007) 401 407 THE CHVÁTAL-ERDŐS CONDITION AND 2-FACTORS WITH A SPECIFIED NUMBER OF COMPONENTS Guantao Chen Department of Mathematcs and Statstcs Georga State Unversty,

More information

Predicting Model of Traffic Volume Based on Grey-Markov

Predicting Model of Traffic Volume Based on Grey-Markov Vo. No. Modern Apped Scence Predctng Mode of Traffc Voume Based on Grey-Marov Ynpeng Zhang Zhengzhou Muncpa Engneerng Desgn & Research Insttute Zhengzhou 5005 Chna Abstract Grey-marov forecastng mode of

More information

Refined Coding Bounds for Network Error Correction

Refined Coding Bounds for Network Error Correction Refned Codng Bounds for Network Error Correcton Shenghao Yang Department of Informaton Engneerng The Chnese Unversty of Hong Kong Shatn, N.T., Hong Kong shyang5@e.cuhk.edu.hk Raymond W. Yeung Department

More information

On the Power Function of the Likelihood Ratio Test for MANOVA

On the Power Function of the Likelihood Ratio Test for MANOVA Journa of Mutvarate Anayss 8, 416 41 (00) do:10.1006/jmva.001.036 On the Power Functon of the Lkehood Rato Test for MANOVA Dua Kumar Bhaumk Unversty of South Aabama and Unversty of Inos at Chcago and Sanat

More information

ISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 3, Issue 1, July 2013

ISSN: ISO 9001:2008 Certified International Journal of Engineering and Innovative Technology (IJEIT) Volume 3, Issue 1, July 2013 ISSN: 2277-375 Constructon of Trend Free Run Orders for Orthogonal rrays Usng Codes bstract: Sometmes when the expermental runs are carred out n a tme order sequence, the response can depend on the run

More information

Time-Varying Systems and Computations Lecture 6

Time-Varying Systems and Computations Lecture 6 Tme-Varyng Systems and Computatons Lecture 6 Klaus Depold 14. Januar 2014 The Kalman Flter The Kalman estmaton flter attempts to estmate the actual state of an unknown dscrete dynamcal system, gven nosy

More information

MMA and GCMMA two methods for nonlinear optimization

MMA and GCMMA two methods for nonlinear optimization MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons

More information

Cooperative Output Regulation of Linear Multi-agent Systems with Communication Constraints

Cooperative Output Regulation of Linear Multi-agent Systems with Communication Constraints 2016 IEEE 55th Conference on Decson and Control (CDC) ARIA Resort & Casno December 12-14, 2016, Las Vegas, USA Cooperatve Output Regulaton of Lnear Mult-agent Systems wth Communcaton Constrants Abdelkader

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

Convexity preserving interpolation by splines of arbitrary degree

Convexity preserving interpolation by splines of arbitrary degree Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete

More information

Lower bounds for the Crossing Number of the Cartesian Product of a Vertex-transitive Graph with a Cycle

Lower bounds for the Crossing Number of the Cartesian Product of a Vertex-transitive Graph with a Cycle Lower bounds for the Crossng Number of the Cartesan Product of a Vertex-transtve Graph wth a Cyce Junho Won MIT-PRIMES December 4, 013 Abstract. The mnmum number of crossngs for a drawngs of a gven graph

More information

Uniqueness of Weak Solutions to the 3D Ginzburg- Landau Model for Superconductivity

Uniqueness of Weak Solutions to the 3D Ginzburg- Landau Model for Superconductivity Int. Journal of Math. Analyss, Vol. 6, 212, no. 22, 195-114 Unqueness of Weak Solutons to the 3D Gnzburg- Landau Model for Superconductvty Jshan Fan Department of Appled Mathematcs Nanjng Forestry Unversty

More information

Randić Energy and Randić Estrada Index of a Graph

Randić Energy and Randić Estrada Index of a Graph EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 5, No., 202, 88-96 ISSN 307-5543 www.ejpam.com SPECIAL ISSUE FOR THE INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND ALGEBRA 29 JUNE -02JULY 20, ISTANBUL

More information

Subgradient Methods and Consensus Algorithms for Solving Convex Optimization Problems

Subgradient Methods and Consensus Algorithms for Solving Convex Optimization Problems Proceedngs of the 47th IEEE Conference on Decson and Contro Cancun, Mexco, Dec. 9-11, 2008 Subgradent Methods and Consensus Agorthms for Sovng Convex Optmzaton Probems Björn Johansson, Tamás Kevczy, Mae

More information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

Linear Approximation with Regularization and Moving Least Squares

Linear Approximation with Regularization and Moving Least Squares Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...

More information

Genericity of Critical Types

Genericity of Critical Types Genercty of Crtcal Types Y-Chun Chen Alfredo D Tllo Eduardo Fangold Syang Xong September 2008 Abstract Ely and Pesk 2008 offers an nsghtful characterzaton of crtcal types: a type s crtcal f and only f

More information

DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED.

DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED. EE 539 Homeworks Sprng 08 Updated: Tuesday, Aprl 7, 08 DO NOT DO HOMEWORK UNTIL IT IS ASSIGNED. THE ASSIGNMENTS MAY CHANGE UNTIL ANNOUNCED. For full credt, show all work. Some problems requre hand calculatons.

More information

On simultaneous parameter identification and state estimation for cascade state affine systems

On simultaneous parameter identification and state estimation for cascade state affine systems Amercan Control Conference Westn Seattle Hotel, Seattle, Washngton, USA June 11-13, WeAI1.9 On smultaneous parameter dentfcaton and state estmaton for cascade state affne systems M. GHANES, G. ZHENG and

More information

Maximizing the number of nonnegative subsets

Maximizing the number of nonnegative subsets Maxmzng the number of nonnegatve subsets Noga Alon Hao Huang December 1, 213 Abstract Gven a set of n real numbers, f the sum of elements of every subset of sze larger than k s negatve, what s the maxmum

More information

Solutions to exam in SF1811 Optimization, Jan 14, 2015

Solutions to exam in SF1811 Optimization, Jan 14, 2015 Solutons to exam n SF8 Optmzaton, Jan 4, 25 3 3 O------O -4 \ / \ / The network: \/ where all lnks go from left to rght. /\ / \ / \ 6 O------O -5 2 4.(a) Let x = ( x 3, x 4, x 23, x 24 ) T, where the varable

More information

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 )

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 ) Kangweon-Kyungk Math. Jour. 4 1996), No. 1, pp. 7 16 AN ITERATIVE ROW-ACTION METHOD FOR MULTICOMMODITY TRANSPORTATION PROBLEMS Yong Joon Ryang Abstract. The optmzaton problems wth quadratc constrants often

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

Research Article H Estimates for Discrete-Time Markovian Jump Linear Systems

Research Article H Estimates for Discrete-Time Markovian Jump Linear Systems Mathematca Probems n Engneerng Voume 213 Artce ID 945342 7 pages http://dxdoorg/11155/213/945342 Research Artce H Estmates for Dscrete-Tme Markovan Jump Lnear Systems Marco H Terra 1 Gdson Jesus 2 and

More information

Solution of a nonsymmetric algebraic Riccati equation from a one-dimensional multistate transport model

Solution of a nonsymmetric algebraic Riccati equation from a one-dimensional multistate transport model IMA Journa of Numerca Anayss (2011) 1, 145 1467 do:10.109/manum/drq04 Advance Access pubcaton on May 0, 2011 Souton of a nonsymmetrc agebrac Rccat equaton from a one-dmensona mutstate transport mode TIEXIANG

More information

LECTURE 9 CANONICAL CORRELATION ANALYSIS

LECTURE 9 CANONICAL CORRELATION ANALYSIS LECURE 9 CANONICAL CORRELAION ANALYSIS Introducton he concept of canoncal correlaton arses when we want to quantfy the assocatons between two sets of varables. For example, suppose that the frst set of

More information

Random Walks on Digraphs

Random Walks on Digraphs Random Walks on Dgraphs J. J. P. Veerman October 23, 27 Introducton Let V = {, n} be a vertex set and S a non-negatve row-stochastc matrx (.e. rows sum to ). V and S defne a dgraph G = G(V, S) and a drected

More information

Associative Memories

Associative Memories Assocatve Memores We consder now modes for unsupervsed earnng probems, caed auto-assocaton probems. Assocaton s the task of mappng patterns to patterns. In an assocatve memory the stmuus of an ncompete

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

A RELAXED SUFFICIENT CONDITION FOR ROBUST STABILITY OF AFFINE SYSTEMS

A RELAXED SUFFICIENT CONDITION FOR ROBUST STABILITY OF AFFINE SYSTEMS Доклади на Българската академия на науките Comptes rendus de l Académe bulgare des Scences Tome 60 No 9 2007 SCIENCES ET INGENIERIE Théore des systèmes A RELAXED SUFFICIENT CONDITION FOR ROBUST STABILITY

More information

COXREG. Estimation (1)

COXREG. Estimation (1) COXREG Cox (972) frst suggested the modes n whch factors reated to fetme have a mutpcatve effect on the hazard functon. These modes are caed proportona hazards (PH) modes. Under the proportona hazards

More information

Neural network-based athletics performance prediction optimization model applied research

Neural network-based athletics performance prediction optimization model applied research Avaabe onne www.jocpr.com Journa of Chemca and Pharmaceutca Research, 04, 6(6):8-5 Research Artce ISSN : 0975-784 CODEN(USA) : JCPRC5 Neura networ-based athetcs performance predcton optmzaton mode apped

More information

CHAPTER III Neural Networks as Associative Memory

CHAPTER III Neural Networks as Associative Memory CHAPTER III Neural Networs as Assocatve Memory Introducton One of the prmary functons of the bran s assocatve memory. We assocate the faces wth names, letters wth sounds, or we can recognze the people

More information

Zeros and Zero Dynamics for Linear, Time-delay System

Zeros and Zero Dynamics for Linear, Time-delay System UNIVERSITA POLITECNICA DELLE MARCHE - FACOLTA DI INGEGNERIA Dpartmento d Ingegnerua Informatca, Gestonale e dell Automazone LabMACS Laboratory of Modelng, Analyss and Control of Dynamcal System Zeros and

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

Multispectral Remote Sensing Image Classification Algorithm Based on Rough Set Theory

Multispectral Remote Sensing Image Classification Algorithm Based on Rough Set Theory Proceedngs of the 2009 IEEE Internatona Conference on Systems Man and Cybernetcs San Antono TX USA - October 2009 Mutspectra Remote Sensng Image Cassfcaton Agorthm Based on Rough Set Theory Yng Wang Xaoyun

More information

Outline. Communication. Bellman Ford Algorithm. Bellman Ford Example. Bellman Ford Shortest Path [1]

Outline. Communication. Bellman Ford Algorithm. Bellman Ford Example. Bellman Ford Shortest Path [1] DYNAMIC SHORTEST PATH SEARCH AND SYNCHRONIZED TASK SWITCHING Jay Wagenpfel, Adran Trachte 2 Outlne Shortest Communcaton Path Searchng Bellmann Ford algorthm Algorthm for dynamc case Modfcatons to our algorthm

More information

2.3 Nilpotent endomorphisms

2.3 Nilpotent endomorphisms s a block dagonal matrx, wth A Mat dm U (C) In fact, we can assume that B = B 1 B k, wth B an ordered bass of U, and that A = [f U ] B, where f U : U U s the restrcton of f to U 40 23 Nlpotent endomorphsms

More information

Anti-van der Waerden numbers of 3-term arithmetic progressions.

Anti-van der Waerden numbers of 3-term arithmetic progressions. Ant-van der Waerden numbers of 3-term arthmetc progressons. Zhanar Berkkyzy, Alex Schulte, and Mchael Young Aprl 24, 2016 Abstract The ant-van der Waerden number, denoted by aw([n], k), s the smallest

More information

10-801: Advanced Optimization and Randomized Methods Lecture 2: Convex functions (Jan 15, 2014)

10-801: Advanced Optimization and Randomized Methods Lecture 2: Convex functions (Jan 15, 2014) 0-80: Advanced Optmzaton and Randomzed Methods Lecture : Convex functons (Jan 5, 04) Lecturer: Suvrt Sra Addr: Carnege Mellon Unversty, Sprng 04 Scrbes: Avnava Dubey, Ahmed Hefny Dsclamer: These notes

More information

6. Stochastic processes (2)

6. Stochastic processes (2) Contents Markov processes Brth-death processes Lect6.ppt S-38.45 - Introducton to Teletraffc Theory Sprng 5 Markov process Consder a contnuous-tme and dscrete-state stochastc process X(t) wth state space

More information

Solutions Homework 4 March 5, 2018

Solutions Homework 4 March 5, 2018 1 Solutons Homework 4 March 5, 018 Soluton to Exercse 5.1.8: Let a IR be a translaton and c > 0 be a re-scalng. ˆb1 (cx + a) cx n + a (cx 1 + a) c x n x 1 cˆb 1 (x), whch shows ˆb 1 s locaton nvarant and

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP C O L L O Q U I U M M A T H E M A T I C U M VOL. 80 1999 NO. 1 FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP BY FLORIAN K A I N R A T H (GRAZ) Abstract. Let H be a Krull monod wth nfnte class

More information

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation Nonl. Analyss and Dfferental Equatons, ol., 4, no., 5 - HIKARI Ltd, www.m-har.com http://dx.do.org/.988/nade.4.456 Asymptotcs of the Soluton of a Boundary alue Problem for One-Characterstc Dfferental Equaton

More information

6. Stochastic processes (2)

6. Stochastic processes (2) 6. Stochastc processes () Lect6.ppt S-38.45 - Introducton to Teletraffc Theory Sprng 5 6. Stochastc processes () Contents Markov processes Brth-death processes 6. Stochastc processes () Markov process

More information

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification

2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification E395 - Pattern Recognton Solutons to Introducton to Pattern Recognton, Chapter : Bayesan pattern classfcaton Preface Ths document s a soluton manual for selected exercses from Introducton to Pattern Recognton

More information

1 Matrix representations of canonical matrices

1 Matrix representations of canonical matrices 1 Matrx representatons of canoncal matrces 2-d rotaton around the orgn: ( ) cos θ sn θ R 0 = sn θ cos θ 3-d rotaton around the x-axs: R x = 1 0 0 0 cos θ sn θ 0 sn θ cos θ 3-d rotaton around the y-axs:

More information

( ) r! t. Equation (1.1) is the result of the following two definitions. First, the bracket is by definition a scalar product.

( ) r! t. Equation (1.1) is the result of the following two definitions. First, the bracket is by definition a scalar product. Chapter. Quantum Mechancs Notes: Most of the matera presented n ths chapter s taken from Cohen-Tannoudj, Du, and Laoë, Chap. 3, and from Bunker and Jensen 5), Chap... The Postuates of Quantum Mechancs..

More information

n-step cycle inequalities: facets for continuous n-mixing set and strong cuts for multi-module capacitated lot-sizing problem

n-step cycle inequalities: facets for continuous n-mixing set and strong cuts for multi-module capacitated lot-sizing problem n-step cyce nequates: facets for contnuous n-mxng set and strong cuts for mut-modue capactated ot-szng probem Mansh Bansa and Kavash Kanfar Department of Industra and Systems Engneerng, Texas A&M Unversty,

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force.

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force. The fundamental prncples of classcal mechancs were lad down by Galleo and Newton n the 16th and 17th centures. In 1686, Newton wrote the Prncpa where he gave us three laws of moton, one law of gravty,

More information

Linear Algebra and its Applications

Linear Algebra and its Applications Lnear Algebra and ts Applcatons 4 (00) 5 56 Contents lsts avalable at ScenceDrect Lnear Algebra and ts Applcatons journal homepage: wwwelsevercom/locate/laa Notes on Hlbert and Cauchy matrces Mroslav Fedler

More information

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

Some results on a cross-section in the tensor bundle

Some results on a cross-section in the tensor bundle Hacettepe Journa of Matematcs and Statstcs Voume 43 3 214, 391 397 Some resuts on a cross-secton n te tensor bunde ydın Gezer and Murat tunbas bstract Te present paper s devoted to some resuts concernng

More information

Price Competition under Linear Demand and Finite Inventories: Contraction and Approximate Equilibria

Price Competition under Linear Demand and Finite Inventories: Contraction and Approximate Equilibria Prce Competton under Lnear Demand and Fnte Inventores: Contracton and Approxmate Equbra Jayang Gao, Krshnamurthy Iyer, Huseyn Topaogu 1 Abstract We consder a compettve prcng probem where there are mutpe

More information

Composite Hypotheses testing

Composite Hypotheses testing Composte ypotheses testng In many hypothess testng problems there are many possble dstrbutons that can occur under each of the hypotheses. The output of the source s a set of parameters (ponts n a parameter

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

Supplementary material: Margin based PU Learning. Matrix Concentration Inequalities

Supplementary material: Margin based PU Learning. Matrix Concentration Inequalities Supplementary materal: Margn based PU Learnng We gve the complete proofs of Theorem and n Secton We frst ntroduce the well-known concentraton nequalty, so the covarance estmator can be bounded Then we

More information

7. Products and matrix elements

7. Products and matrix elements 7. Products and matrx elements 1 7. Products and matrx elements Based on the propertes of group representatons, a number of useful results can be derved. Consder a vector space V wth an nner product ψ

More information

A Local Variational Problem of Second Order for a Class of Optimal Control Problems with Nonsmooth Objective Function

A Local Variational Problem of Second Order for a Class of Optimal Control Problems with Nonsmooth Objective Function A Local Varatonal Problem of Second Order for a Class of Optmal Control Problems wth Nonsmooth Objectve Functon Alexander P. Afanasev Insttute for Informaton Transmsson Problems, Russan Academy of Scences,

More information

Appendix for An Efficient Ascending-Bid Auction for Multiple Objects: Comment For Online Publication

Appendix for An Efficient Ascending-Bid Auction for Multiple Objects: Comment For Online Publication Appendx for An Effcent Ascendng-Bd Aucton for Mutpe Objects: Comment For Onne Pubcaton Norak Okamoto The foowng counterexampe shows that sncere bddng by a bdders s not aways an ex post perfect equbrum

More information