Information Fusion Kalman Smoother for Time-Varying Systems
|
|
- Scarlett Tyler
- 5 years ago
- Views:
Transcription
1 Infoaon Fuon alan oohe fo Te-Vayng ye Xao-Jun un Z- Deng Abac-- Fo he lnea dcee e-ayng ochac conol ye wh uleno coloed eaueen noe hee dbued opal fuon alan oohe ae peened baed on he opal nfoaon fuon ule weghed by ace dagonal ace cala n he lnea nu aance ene. Copaed wh he cenalzed fue hey ae locally opal bu ae globally ubopal. The accuacy of he fue wh a wegh hghe han ha of he fue wh cala wegh he accuacy of he fue wh dagonal a wegh beween boh of he. The accuacy of all he hee fue hghe han ha of each local alan oohe. Fuhe he coepondng hee eady-ae fuon fed-lag alan oohe ae alo gen fo he lnea dcee e-naan ochac conol ye whch can educe he on-lne copuaonal buden. In ode o copue opal wegh he new foula of copung he co-coaance aong local oohng eo ae peened. Two Mone Calo ulaon eaple fo acng ye how he pefoance of he popoed fue. Inde Te Te-ayng ye coloed eaueen noe dbued fuon alan oohe uleno nfoaon fuon T I. ITODUCTIO nfoaon fuon o daa fuon fo eaon ha wdepead applcaon nce any paccal poble nole daa fo ulple ouce. In ecen yea he nfoaon fuon alan fleng heoy ha been fuhe uded wdely appled n any feld uch a gudance defence oboc negaed nagaon age acng G poonng councaon gnal poceng conol ec[]. Fo alan fleng-baed fuon wo bac fuon ehod ae cenalzed decenalzed o dbued fuon ehod dependng on whehe aw daa ae ued decly fo fuon o no [2]. The cenalzed fuon ehod can ge he globally opal ae eaon by decly cobnng local eaueen daa. Bu dadanage ae ha ay eque a lage copuaonal buden hgh daa ae fo councaon. The dbued fuon ehod can ge he globally opal o ubopal ae eaon by cobnng Th wo uppoed by aonal aual cence Foundaon of Chna unde Gan FC X. J. un wh Depaen of Auoaon elongang Uney 58 Z.. Deng wh Depaen of Auoaca elongang Uney 58 abn Chna coepondng auho phone: e-al: dzl@hlu.edu.cn. he local ae eao. Th ehod ha condeable adanage: can faclae faul deecon olaon oe conenenly can nceae he npu daa ae gnfcanly. Thee ae wo appoache o dbued fuon alan fleng whch ae he nfoaon a appoach [34] he weghed coaance appoach [5-9]. The dbued fuon alan fle wh feedbac whou feedbac by he nfoaon a appoach ae equalen o he cenalzed fuon alan fle ge he globally opal ae eaon [4] bu hey all wll eque eene calculaon of local global nee coaance. The weghed coaance appoach a coaance auo-coaance co-coaance-baed weghed fuon appoach wh aou weghed fuon ule. I can elnae epene copuaonal equeen bu geneally ge a globally ubopal ae eaon wh a lgh lo of accuacy. o fa hee hae been eeal opal weghed fuon ule whch ae he fuon ule weghed by ace n he lnea nu aance ene [9] he au lelhood M fuon ule wh an aupon of a noal deny funcon [] he fuon ule weghed by cala n he lnea nu aance ene [8] he weghed lea quae W fuon ule [59]. oe ha he opal fuon eae elaed o he pefoance nde of opzaon whn a eced local lnea pace. All hee fuon ule ge locally opal eao whch globally ubopal copaed wh he cenalzed fuon eao. o fa he uleno nfoaon fuon eaon anly focued on he fleng fuon [457] bu he oohng fuon eldo epoed [9] he eaueen noe of eno uually aued o be whe noe bu he fuon eaon fo uleno ye wh coloed eaueen noe eldo epoed [2]. ecenly a nfoaon fuon eady-ae alan eao wa peened [9] whch can hle he fued fleng pedcon oohng poble bu only uable fo he e-naan ye wh whe eaueen noe. Fo he e-ayng uleno ye wh whe eaueen noe un [] peened a dbued fuon fed-lag alan oohe wh he coponen fuon weghed by cala whch equalen o he fue weghed by dagonal ace [9] bu no uable fo uleno ye wh coloed eaueen noe he fued alan oohe weghed by ace cala wee no peened. A dbued opal fuon 655
2 eady-ae alan fle wh a wegh wa peened fo ye wh coloed eaueen noe [2] bu he oohng fuon poble wa no oled n [2]. In ode o oecoe he aboe dawbac laon baed on he opal fuon ule weghed by ace dagonal ace cala n he lnea nu aance ene hee opal nfoaon fuon alan oohe ae peened fo he dcee e-aan lnea ochac conol ye wh uleno coloed eaueen noe n h pape. In ode o copue he opal wegh he foula copung he local eaon eo co-coaance ae peened whch ae dffeen fo he foula popoed by un []. Condeng he e-naan cae he hee nfoaon fuon eady-ae fed-lag alan oohe he foula copung he co coaance aong local eaon eo ae alo gen. Two Mone Calo ulaon eaple how he accuacy elaon of he popoed oohng fue. The ee of h pape oganzed a follow: The poble foulaon gen n econ 2. The hee dbued fuon alan oohe ae peened n econ 3. econ 4 ge he hee eady-ae fuon alan oohe. Two Mone Calo ulaon eaple ae gen n econ 5. The concluon peened n econ 6. II. OBM FOMUATIO Conde he dcee e-ayng lnea ochac conol ye wh eno Φ B u w z η 2 η A η ξ 3 whee dcee e ae he eaueen n he ae z p u he nown conol npu w ξ ae he whe noe η ae he coloed eaueen noe Φ ae e-ayng ace wh A copable denon. Aupon. w ξ ae ndependen whe noe wh zeo ean aance a ξ epecely. Aupon 2. The nal ae wh ean µ eo aance a ndependen of w ξ. The opal nfoaon fuon alan oohe poble o fnd he opal lnea nu aance fuon alan oohe ˆ > weghed by ace dagonal ace cala baed on he local alan oohe ˆ epecely. Inoducng new eaueen y z A z B u 4 ubung -3 no 4 we hae y Φ A w ξ 5 eng Φ A 6 w ξ 7 cobnng 5 we hae Φ B u w 8 y 9 The new ye 8 9 ae he lnea ochac conol ye wh coelaed whe noe w coelaed eaueen noe ha w [ w ] δ [ ] δ whee Ε he epecaon he upecp denoe he anpoe δ he onece dela funcon δ δ. III. DITIBUTD FUIO AMA MOOT ea [3]. Fo he uleno e-ayng ye -3 wh he aupon 2 he h eno ubye ha he local alan pedco ˆ ˆ B u y ξ p y ˆ 2 p f p Φ 3 p [ Φ ] 4 p 5 6 whee f ae he pedcon fleng p gan ace epecely. The pedcon eo aance a afe he cca equaon Φ Φ [ Φ ][ ] [ Φ ] 7 656
3 wh nal alue µ ˆ. oof. The poof of ea gen n [3] whch oed. Theoe. Fo he uleno e-ayng ye -3 wh he aupon 2 he co-coaance ace aong local pedcon eo ae gen a ] [ p p p p 8 o p p p p p p 9 wh he nal alue. oof. Fo [3] we hae he pedcon eo equaon w p p 2 whee w ndependen of. Ung 2 we hae 8. ea 2 [3]. Fo he uleno e-ayng ye -3 wh he aupon 2 he h eno ubye ha he local opal alan oohe ˆ ˆ 2 whee he oohng gan a gen a } { p 22 f 23 whee p f ˆ obaned fo ea he oohng eo aance a gen a 24 oof. The poof of ea 2 gen n [3] whch oed. Theoe 2. Fo he uleno e-ayng ye wh he aupon 2 he co-coaance ace aong local oohng eo a p p 25 whee > we defne p p p I n p 26 ] [ Ε 27 When n > we hae he followng equaon p p n p ] [ p p p δ 28 When n we hae p ] [ p p p ] [ p p 29 oof. Fo [3] we hae w p p 3 whch yeld p p ] [ w p 3 o we hae p p [ w p 32 whch yeld 28 ung 3 we oban 29. Theoe 3. Fo he uleno e-ayng ye -3 wh he aupon 2 hee dbued opal nfoaon fuon fed-lag alan oohe ae gen a Ω ˆ ˆ 33 Fo he fue wh a wegh we hae 657
4 [ Ω Ω ] e e e n n whee e I n I ] he fued eo aance a [ n gen a [ e e] 36 Fo he ue wh cala wegh Ω ω we hae [ ω ω ] e e e whee e [ ] denoe he ace of a he fue eo aance a gen a ω ω 39 Fo he fue wh dagonal a wegh we hae Ω dag ω ω 4 [ ω ω ] e e e 4 42 whee e [ ] ae he h dagonal eleen of. The ace of he fued eo aance a d gen a d [ e e] 43 Denong he cenalzed fuon eo aance a a c we hae he accuacy he elaon c 44 oof. Applyng he hee opal fuon foula weghed by ace dagonal ace cala n [9] we decely oban Theoe 3. IV. TADY-TAT FUIO AMA MOOT Fo he e-aan ye -3 wh conan ace Φ Φ B B A A ξ ξ we hae. If eey local eno ubye ha eady-ae alan eao we can oban he nfoaon fuon eady-ae fed-lag alan oohe whch can educe he on-lne couaon buden. Theoe 4. Fo uleno e-aan ye -3 wh aupon 2 he local eady-ae alan pedco gen a d whee ˆ ˆ Bu y 45 p y ˆ 46 p p Φ 47 [ p ΦΣ ] 48 f Σ 49 Σ p Σ afe he eady-ae cca equaon Σ Φ Σ Φ [ ΦΣ ][ Σ ] ] [ ΦΣ 53 he local eady-ae fed-lag alan oohe gen a ˆ ˆ 54 Whee he oohng gan a hown a follow Σ p 55 The eady-ae oohng eo aance a l gen a Σ 56 The eady-ae oohng eo co-coaance a Σ pσ Σ When n > we hae n p p 57 p [ p ] δ Σ p When n we hae p p Σ 58 p Σ p [ Σ p [ p ] p 58 oof. Fo he eady-ae alan fleng we hae ha p p p p Σ Σ a. Tang ea p ] 658
5 3 Theoe -3 we decly oban Theoe 4. Theoe 5. Fo uleno e-aan ye -3 wh aupon 3 he hee dbued fuon eady-ae fed-lag oohe gen by ˆ Ω ˆ 59 Whee ˆ ae copued a Theoe 4. The wegh Ω ae copued a Theoe 3 whee Ω ω ω ae eplaced by Ω ω ω elaon epecely. We hae he eady-ae accuacy d c 6 whee d denoe he eady-ae eo aance ace fo fue wh a wegh dagonal a cala wegh epecely denoe he eady-ae eo aance a of cenalzed fue. oof. Tang n Theoe 3 we aghfowad oban Theoe 5. c V. IMUATIO XAM aple. Conde he 3-eno dcee e-ayng acng ye wh coloed eaueen noe Φ B u w 6 z η 62 η A η ξ T.5T 2.5T 2.5T Φ T B T T..9co 2π.2.n.5 2π ξ. ξ 2 2π.2.8co..9n 2π ξ 3 c ρ n 2π. A.2 c. ρ Whee T he apled peod we ae T. 5 [ ] he ae. ae 2 3 he poon elocy acceleaon of age a e T 2 3 epecely. η ae he coloed eaueen whe noe w 2 2 w 2 d 2 c w ξ ae ndependen whe noe wh zeo ean aance ace ξ epecely. The conol u nown we [25] [575] aeu. The poble o copae [265] [76] he accuacy of local alan oohe ˆ 2 fued alan oohe ˆ θ 2 θ d cenalzed fue ˆ 2. The ulaon eul ae hown n c Fg.-Fg.3 Table. In Fg. Table we can ee ha he accuacy of fuon oohe hghe han ha of each local oohe he heoecal accuacy elaon 44 hold. 5 Mone Calo un ae caed ou he ean quae eo M cue hown n he Fg.2 Fg.3 whee he M alue a defned a M whee 2 ˆ 2 23 c ˆ 2 he h aple of he ochac poce ˆ 2 3 he apled nube. Fo Fg.2 Fg.3 we ee ha he accuacy of he fue hghe han ha of each local oohe he accuacy of he cenalzed fuon hghe han ha of hee weghed fue no obou becaue he M cue ae a ndnguhable /ep Fg. Copaon of ace 2 θ 2 θ d c of local fued oohng eo aance ace eno eno2 eno3 fuon weghed by cala fuon weghed by dagonal ace fuon weghed by ace cenalzed fuon aple 2. Conde he e-naan acng ye wh 3-eno coloed eaueen noe Φ w
6 z η 67 η a η ξ Φ.2. [ ] [] 3 [ ] M M /ep Fg. 2 The ean quae eo M cue od local fued oohe n 5 Mone Calo un eno eno2 eno3 fuon weghed by ace fuon weghed by cala fuon weghed by dagonal ace cenalzed fuon /ep Fg. 4 The ean quae eo M cue of local fued oohe n 3 Mone Calo un eno eno2 eno3 fuon weghed by ace fuon weghed by cala fuon weghed by dagonal ace cenalzed fuon M /ep Fg. 3 The ean quae eo M cue of he hee dbued fued cenalzed fued oohe n 5 Mone Calo un fuon weghed by ace fuon weghed by cala fuon weghed by dagonal ace cenalzed fuon M /ep Fg. 5 The ean quae eo M cue of he hee dbued fued cenalzed fued oohe n 3 Mone Calo un whee T he apled peod [ 2 3 ] he ae ae he poon elocy 2 fuon weghed by ace fuon weghed by cala fuon weghed by dagonal ace cenalzed fuon acceleaon of age a e T epecely. w ξ ndependen Gauan whe noe wh zeo ean 3 66
7 aance ace σ. 36 σ σ 2 2 w ξ ξ 2 σ ξ 3 7 epecely a. a 2. 3 a 3. 6.The poble o copue he accuacy of local fued eady-ae alan oohe. 5 Mone Calo un ae caed ou he ean quae eo M cue hown n he Fg.4 Fg.5 Table 2 whee we can oban he ae concluon a he eaple. Table. Copaon of local ace 2 fued ace 2 θ d c d c θ Table 2. Copaon of local ace 2 fued ace 2 θ d c ace d 2 2 c 2 alue I. OCUIO Fo he dcee e-ayng lnea ochac conol ye wh uleno wh coloed eaueen noe hee opal nfoaon fuon alan oohe hae been peened baed on he opal fuon ule weghed by ace dagonal ace cala n he lnea nu aance ene he coepondng hee eady-ae fuon alan oohe hae been peened fo he naan ye. In ode o copue he opal wegh he new foula of copung he co-coaance aong local oohng eo hae been peened. They ae locally opal ae globally ubopal. Two Mone Calo ulaon eaple hown he accuacy dncon of hee alan fue no obou o ha eployng he alan fue wh cala wegh o dagonal ace uable fo eal e applcaon. The popoed eul oecoe he laon dawbac n oe efeence. ACOWDGMT Th wo wa uppoed by aonal aual cence Foundaon of Chna unde Gan FC The auho wh o han he eewe fo he conuce coen. θ [4] Y. M. Zhu Z.. You J. Zhao.. Zhang X.. The opaly fo he dbued alan fleng fuon wh feedbac Auoaca ol. 37 pp [5]. A. Calon Fedeaed quae oo fle fo decenalzed paallel poce I Tanacon on Aeopace leconc ye ol. 34 pp [6]. X. aha. C. Chang ffcen algoh fo uleno ac fuon I Tanacon on Aeopace leconc ye ol. 34 pp [7].. un Z.. Deng Mul-eno opal nfoaon fuon alan fle Auoaca ol. 4 pp [8].. un Muleno nfoaon fuon whe noe fle weghed by cala baed alan pedco Auoaca ol. 4 pp [9] Z.. Deng Y. Gao. Mao Y. G. ao ew appoach o nfoaon fuon eady-ae alan fleng Auoaca ol. 4 no. pp [].. Deelopen of ac o ac fuon algoh oceedng of Aecan conol confeence Mayl June pp [].. un Dbued opal coponen fuon weghed by cala fo fed-lag alan oohe Auoaca ol. 4 pp [2].. un Z.. Deng Dbued opal fuon eady-ae alan fle fo ye wh coloed eaueen noe Inenaonal Joual of ye cence ol. 36 pp [3] Z.. Deng Opal aon Theoy wh Applcaon- Mondelng Fleng Infoaon Fuon aon abn: abn Inue of Technology e pp FC [] Y. Ba halon X.. Muleno Tacng: ncple Techngue. o CT: YB ublhng 995. [2] X.. Y. M. Zhu J. Wang C. Z. an Opal lnea eaon fuon-pa :Unfed fuon ule I Tanacon on Infoaon Theoy ol. 49 pp [3]. C. Chang T. Zh.. aha efoance ealuaon of ac fuon wh nfoaon a fle I Tanacon. Aeopace leconc ye ol. 38 no. 2 pp
Maximum Likelihood Estimation
Mau Lkelhood aon Beln Chen Depaen of Copue Scence & Infoaon ngneeng aonal Tawan oal Unvey Refeence:. he Alpaydn, Inoducon o Machne Leanng, Chape 4, MIT Pe, 4 Saple Sac and Populaon Paaee A Scheac Depcon
More informationESS 265 Spring Quarter 2005 Kinetic Simulations
SS 65 Spng Quae 5 Knec Sulaon Lecue une 9 5 An aple of an lecoagnec Pacle Code A an eaple of a knec ulaon we wll ue a one denonal elecoagnec ulaon code called KMPO deeloped b Yohhau Oua and Hoh Mauoo.
More informationNumerical Study of Large-area Anti-Resonant Reflecting Optical Waveguide (ARROW) Vertical-Cavity Semiconductor Optical Amplifiers (VCSOAs)
USOD 005 uecal Sudy of Lage-aea An-Reonan Reflecng Opcal Wavegude (ARROW Vecal-Cavy Seconduco Opcal Aplfe (VCSOA anhu Chen Su Fung Yu School of Eleccal and Eleconc Engneeng Conen Inoducon Vecal Cavy Seconduco
More informationChapter 6 Plane Motion of Rigid Bodies
Chpe 6 Pne oon of Rd ode 6. Equon of oon fo Rd bod. 6., 6., 6.3 Conde d bod ced upon b ee een foce,, 3,. We cn ume h he bod mde of e numbe n of pce of m Δm (,,, n). Conden f he moon of he m cene of he
More informationMemorandum COSOR 97-??, 1997, Eindhoven University of Technology
Meoandu COSOR 97-??, 1997, Endhoven Unvey of Technology The pobably geneang funcon of he Feund-Ana-Badley ac M.A. van de Wel 1 Depaen of Maheac and Copung Scence, Endhoven Unvey of Technology, Endhoven,
More informationChapter 3: Vectors and Two-Dimensional Motion
Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon
More information1 Constant Real Rate C 1
Consan Real Rae. Real Rae of Inees Suppose you ae equally happy wh uns of he consumpon good oday o 5 uns of he consumpon good n peod s me. C 5 Tha means you ll be pepaed o gve up uns oday n eun fo 5 uns
More information5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )
5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma
More informationPhysics 201 Lecture 15
Phscs 0 Lecue 5 l Goals Lecue 5 v Elo consevaon of oenu n D & D v Inouce oenu an Iulse Coens on oenu Consevaon l oe geneal han consevaon of echancal eneg l oenu Consevaon occus n sses wh no ne eenal foces
More informationRobust Centralized Fusion Kalman Filters with Uncertain Noise Variances
ELKOMNIKA Indonean Jounal of Eleal Engneeng Vol., No.6, June 04, pp. 4705 ~ 476 DOI: 0.59/elkomnka.v6.5490 4705 Robu Cenalzed Fuon Kalman Fle wh Unean Noe Vaane Wen-juan Q, Peng Zhang, Z-l Deng* Depamen
More information( ) ( ) ( ) ( ) ( ) ( ) j ( ) A. b) Theorem
b) Theoe The u of he eco pojecon of eco n ll uull pependcul (n he ene of he cl poduc) decon equl o he eco. ( ) n e e o The pojecon conue he eco coponen of he eco. poof. n e ( ) ( ) ( ) e e e e e e e e
More information2 shear strain / L for small angle
Sac quaons F F M al Sess omal sess foce coss-seconal aea eage Shea Sess shea sess shea foce coss-seconal aea llowable Sess Faco of Safe F. S San falue Shea San falue san change n lengh ognal lengh Hooke
More informationChapter 2: Descriptive Statistics
Chapte : Decptve Stattc Peequte: Chapte. Revew of Uvaate Stattc The cetal teecy of a oe o le yetc tbuto of a et of teval, o hghe, cale coe, ofte uaze by the athetc ea, whch efe a We ca ue the ea to ceate
More informationClustering Web Access Patterns based on Learning Automata and Fuzzy Logic
The Thd Ian Daa Mnng Confeence/IDMC 009 5-6 Dec.009, Tehan,Ian Pape ID: 4....... weghed fuzzy c-ean... Clueng Web Acce Paen baed on eanng Auoaa and Fuzzy ogc Z. Ana Copue Engneeng Depaen Ilac Azad Unvey
More informationCHAPTER 10: LINEAR DISCRIMINATION
HAPER : LINEAR DISRIMINAION Dscmnan-based lassfcaon 3 In classfcaon h K classes ( k ) We defned dsmnan funcon g () = K hen gven an es eample e chose (pedced) s class label as f g () as he mamum among g
More informationInformation Fusion White Noise Deconvolution Smoother for Time-Varying Systems
Informaon Fuson Whe ose Deconoluon mooher for Tme-Varyng ysems Xao-Jun un Yuan Gao and Z- Deng Absrac Whe nose deconoluon or npu he nose esmaon problem has mporan applcaon bacground n ol sesmc eploraon.
More informationOn Probability Density Function of the Quotient of Generalized Order Statistics from the Weibull Distribution
ISSN 684-843 Joua of Sac Voue 5 8 pp. 7-5 O Pobaby Dey Fuco of he Quoe of Geeaed Ode Sac fo he Webu Dbuo Abac The pobaby dey fuco of Muhaad Aee X k Y k Z whee k X ad Y k ae h ad h geeaed ode ac fo Webu
More informationPhysics 120 Spring 2007 Exam #1 April 20, Name
Phc 0 Spng 007 E # pl 0, 007 Ne P Mulple Choce / 0 Poble # / 0 Poble # / 0 Poble # / 0 ol / 00 In eepng wh he Unon College polc on cdec hone, ued h ou wll nehe ccep no pode unuhozed nce n he copleon o
More informationOutline. GW approximation. Electrons in solids. The Green Function. Total energy---well solved Single particle excitation---under developing
Peenaon fo Theoecal Condened Mae Phyc n TU Beln Geen-Funcon and GW appoxmaon Xnzheng L Theoy Depamen FHI May.8h 2005 Elecon n old Oulne Toal enegy---well olved Sngle pacle excaon---unde developng The Geen
More informationNormal Random Variable and its discriminant functions
Noral Rando Varable and s dscrnan funcons Oulne Noral Rando Varable Properes Dscrnan funcons Why Noral Rando Varables? Analycally racable Works well when observaon coes for a corruped snle prooype 3 The
More informationChebyshev Polynomial Solution of Nonlinear Fredholm-Volterra Integro- Differential Equations
Çny Ünvee Fen-Edeby Füle Jounl of A nd Scence Sy : 5 y 6 Chebyhev Polynol Soluon of onlne Fedhol-Vole Inego- Dffeenl Equon Hndn ÇERDİK-YASA nd Ayşegül AKYÜZ-DAŞCIOĞU Abc In h ppe Chebyhev collocon ehod
More informationMATRIX COMPUTATIONS ON PROJECTIVE MODULES USING NONCOMMUTATIVE GRÖBNER BASES
Jounal of lgeba Numbe heo: dance and pplcaon Volume 5 Numbe 6 Page -9 alable a hp://cenfcadance.co.n DOI: hp://d.do.og/.86/janaa_7686 MRIX COMPUIONS ON PROJCIV MODULS USING NONCOMMUIV GRÖBNR BSS CLUDI
More informationELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University
ecre Noe Prepared b r G. ghda EE 64 ETUE NTE WEE r. r G. ghda ocorda Uer eceraled orol e - Whe corol heor appled o a e ha co of geographcall eparaed copoe or a e cog of a large ber of p-op ao ofe dered
More information(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function
MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,
More informationÖRNEK 1: THE LINEAR IMPULSE-MOMENTUM RELATION Calculate the linear momentum of a particle of mass m=10 kg which has a. kg m s
MÜHENDİSLİK MEKANİĞİ. HAFTA İMPULS- MMENTUM-ÇARPIŞMA Linea oenu of a paicle: The sybol L denoes he linea oenu and is defined as he ass ies he elociy of a paicle. L ÖRNEK : THE LINEAR IMPULSE-MMENTUM RELATIN
More information2/20/2013. EE 101 Midterm 2 Review
//3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance
More informationStability Analysis of a Sliding-Mode Speed Observer during Transient State
Poceedng of he 5h WA In. Conf. on Inuenaon Meaueen Ccu and ye Hangzhou Chna Apl 6-8 006 (pp35-40 ably Analy of a ldng-mode peed Obeve dung anen ae WIO ANGUNGONG AAWU UJIJON chool of leccal ngneeng Inue
More informationCHAPTER II AC POWER CALCULATIONS
CHAE AC OWE CACUAON Conens nroducon nsananeous and Aerage ower Effece or M alue Apparen ower Coplex ower Conseraon of AC ower ower Facor and ower Facor Correcon Maxu Aerage ower ransfer Applcaons 3 nroducon
More information( ) Physics 1401 Homework Solutions - Walker, Chapter 9
Phyic 40 Conceptual Quetion CQ No Fo exaple, ey likely thee will be oe peanent deoation o the ca In thi cae, oe o the kinetic enegy that the two ca had beoe the colliion goe into wok that each ca doe on
More informationTHIS PAGE DECLASSIFIED IAW E
THS PAGE DECLASSFED AW E0 2958 BL K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW E0 2958 B L K THS PAGE DECLASSFED AW E0 2958 THS PAGE DECLASSFED AW EO 2958 THS PAGE DECLASSFED AW EO 2958 THS
More informationA. Inventory model. Why are we interested in it? What do we really study in such cases.
Some general yem model.. Inenory model. Why are we nereed n? Wha do we really udy n uch cae. General raegy of machng wo dmlar procee, ay, machng a fa proce wh a low one. We need an nenory or a buffer or
More informationX-Ray Notes, Part III
oll 6 X-y oe 3: Pe X-Ry oe, P III oe Deeo Coe oupu o x-y ye h look lke h: We efe ue of que lhly ffee efo h ue y ovk: Co: C ΔS S Sl o oe Ro: SR S Co o oe Ro: CR ΔS C SR Pevouly, we ee he SR fo ye hv pxel
More information-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL
UPB Sc B See A Vo 72 I 3 2 ISSN 223-727 MUTIPE -HYBRID APACE TRANSORM AND APPICATIONS TO MUTIDIMENSIONA HYBRID SYSTEMS PART II: DETERMININ THE ORIINA Ve PREPEIŢĂ Te VASIACHE 2 Ace co copeeă oă - pce he
More informationTHE EQUIVALENCE OF GRAM-SCHMIDT AND QR FACTORIZATION (page 227) Gram-Schmidt provides another way to compute a QR decomposition: n
HE EQUIVAENCE OF GRA-SCHID AND QR FACORIZAION (page 7 Ga-Schdt podes anothe way to copute a QR decoposton: n gen ectos,, K, R, Ga-Schdt detenes scalas j such that o + + + [ ] [ ] hs s a QR factozaton of
More informationTHIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.
T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson
More informationResponse of MDOF systems
Response of MDOF syses Degree of freedo DOF: he nu nuber of ndependen coordnaes requred o deerne copleely he posons of all pars of a syse a any nsan of e. wo DOF syses hree DOF syses he noral ode analyss
More informationHomework Set 4 Physics 319 Classical Mechanics. m m k. x, x, x, x T U x x x x l 2. x x x x. x x x x
Poble 78 a) The agangian i Hoewok Set 4 Phyic 319 Claical Mechanic k b) In te of the cente of a cooinate an x x1 x x1 x xc x x x x x1 xc x xc x x x x x1 xc x xc x, x, x, x T U x x x x l 1 1 1 1 1 1 1 1
More informationChapters 2 Kinematics. Position, Distance, Displacement
Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen
More informationThe Non-Truncated Bulk Arrival Queue M x /M/1 with Reneging, Balking, State-Dependent and an Additional Server for Longer Queues
Alied Maheaical Sciece Vol. 8 o. 5 747-75 The No-Tucaed Bul Aival Queue M x /M/ wih Reei Bali Sae-Deede ad a Addiioal Seve fo Loe Queue A. A. EL Shebiy aculy of Sciece Meofia Uiveiy Ey elhebiy@yahoo.co
More informationPhysics 15 Second Hour Exam
hc 5 Second Hou e nwe e Mulle hoce / ole / ole /6 ole / ------------------------------- ol / I ee eone ole lee how ll wo n ode o ecee l ced. I ou oluon e llegle no ced wll e gen.. onde he collon o wo 7.
More informationP a g e 5 1 of R e p o r t P B 4 / 0 9
P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e
More information( ) ( )) ' j, k. These restrictions in turn imply a corresponding set of sample moment conditions:
esng he Random Walk Hypohess If changes n a sees P ae uncoelaed, hen he followng escons hold: va + va ( cov, 0 k 0 whee P P. k hese escons n un mply a coespondng se of sample momen condons: g µ + µ (,,
More informationβ A Constant-G m Biasing
p 2002 EE 532 Anal IC Des II Pae 73 Cnsan-G Bas ecall ha us a PTAT cuen efeence (see p f p. 66 he nes) bas a bpla anss pes cnsan anscnucance e epeaue (an als epenen f supply lae an pcess). Hw h we achee
More informationI-POLYA PROCESS AND APPLICATIONS Leda D. Minkova
The XIII Inenaonal Confeence Appled Sochasc Models and Daa Analyss (ASMDA-009) Jne 30-Jly 3, 009, Vlns, LITHUANIA ISBN 978-9955-8-463-5 L Sakalaskas, C Skadas and E K Zavadskas (Eds): ASMDA-009 Seleced
More informationGENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS
#A39 INTEGERS 9 (009), 497-513 GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS Mohaad Faokh D. G. Depatent of Matheatcs, Fedows Unvesty of Mashhad, Mashhad,
More informationReliability Analysis. Basic Reliability Measures
elably /6/ elably Aaly Perae faul Œ elably decay Teporary faul Œ Ofe Seady ae characerzao Deg faul Œ elably growh durg eg & debuggg A pace hule Challeger Lauch, 986 Ocober 6, Bac elably Meaure elably:
More informationL4:4. motion from the accelerometer. to recover the simple flutter. Later, we will work out how. readings L4:3
elave moon L4:1 To appl Newon's laws we need measuemens made fom a 'fed,' neal efeence fame (unacceleaed, non-oang) n man applcaons, measuemens ae made moe smpl fom movng efeence fames We hen need a wa
More informationPHYSICS 151 Notes for Online Lecture #4
PHYSICS 5 Noe for Online Lecure #4 Acceleraion The ga pedal in a car i alo called an acceleraor becaue preing i allow you o change your elociy. Acceleraion i how fa he elociy change. So if you ar fro re
More information6. Introduction to Transistor Amplifiers: Concepts and Small-Signal Model
6. ntoucton to anssto mples: oncepts an Small-Sgnal Moel Lectue notes: Sec. 5 Sea & Smth 6 th E: Sec. 5.4, 5.6 & 6.3-6.4 Sea & Smth 5 th E: Sec. 4.4, 4.6 & 5.3-5.4 EE 65, Wnte203, F. Najmaba Founaton o
More informationCourse Outline. 1. MATLAB tutorial 2. Motion of systems that can be idealized as particles
Couse Oulne. MATLAB uoal. Moon of syses ha can be dealzed as pacles Descpon of oon, coodnae syses; Newon s laws; Calculang foces equed o nduce pescbed oon; Deng and solng equaons of oon 3. Conseaon laws
More informationdm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v
Mg: Pcess Aalyss: Reac ae s defed as whee eac ae elcy lue M les ( ccea) e. dm he ube f les ay lue s M, whee ccea M/L les. he he eac ae beces f a hgeeus eac, ( ) d Usually s csa aqueus eeal pcesses eac,
More informationTest 2 phy a) How is the velocity of a particle defined? b) What is an inertial reference frame? c) Describe friction.
Tet phy 40 1. a) How i the velocity of a paticle defined? b) What i an inetial efeence fae? c) Decibe fiction. phyic dealt otly with falling bodie. d) Copae the acceleation of a paticle in efeence fae
More informationChapter 8. Linear Momentum, Impulse, and Collisions
Chapte 8 Lnea oentu, Ipulse, and Collsons 8. Lnea oentu and Ipulse The lnea oentu p of a patcle of ass ovng wth velocty v s defned as: p " v ote that p s a vecto that ponts n the sae decton as the velocty
More informationA GENERALIZATION OF A CONJECTURE OF MELHAM. 1. Introduction The Fibonomial coefficient is, for n m 1, defined by
A GENERALIZATION OF A CONJECTURE OF MELHAM EMRAH KILIC 1, ILKER AKKUS, AND HELMUT PRODINGER 3 Abstact A genealization of one of Melha s conectues is pesented Afte witing it in tes of Gaussian binoial coefficients,
More informationABSOLUTE INDEXED SUMMABILITY FACTOR OF AN INFINITE SERIES USING QUASI-F-POWER INCREASING SEQUENCES
Available olie a h://sciog Egieeig Maheaics Lees 2 (23) No 56-66 ISSN 249-9337 ABSLUE INDEED SUMMABILIY FACR F AN INFINIE SERIES USING QUASI-F-WER INCREASING SEQUENCES SKAIKRAY * RKJAI 2 UKMISRA 3 NCSAH
More informationCptS 570 Machine Learning School of EECS Washington State University. CptS Machine Learning 1
ps 57 Machne Leann School of EES Washnon Sae Unves ps 57 - Machne Leann Assume nsances of classes ae lneal sepaable Esmae paamees of lnea dscmnan If ( - -) > hen + Else - ps 57 - Machne Leann lassfcaon
More informationPHY2053 Summer C 2013 Exam 1 Solutions
PHY053 Sue C 03 E Soluon. The foce G on o G G The onl cobnon h e '/ = doubln.. The peed of lh le 8fulon c 86,8 le 60 n 60n h 4h d 4d fonh.80 fulon/ fonh 3. The dnce eled fo he ene p,, 36 (75n h 45 The
More informationThe Backpropagation Algorithm
The Backpopagaton Algothm Achtectue of Feedfowad Netwok Sgmodal Thehold Functon Contuctng an Obectve Functon Tanng a one-laye netwok by teepet decent Tanng a two-laye netwok by teepet decent Copyght Robet
More information2/24/2014. The point mass. Impulse for a single collision The impulse of a force is a vector. The Center of Mass. System of particles
/4/04 Chapte 7 Lnea oentu Lnea oentu of a Sngle Patcle Lnea oentu: p υ It s a easue of the patcle s oton It s a vecto, sla to the veloct p υ p υ p υ z z p It also depends on the ass of the object, sla
More informationChapter 7 AC Power and Three-Phase Circuits
Chaper 7 AC ower and Three-hae Crcu Chaper 7: Oulne eance eacance eal power eacve power ower n AC Crcu ower and Energy Gven nananeou power p, he oal energy w ranferred o a load beween and : w p d The average
More informationSolution in semi infinite diffusion couples (error function analysis)
Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of
More informationField due to a collection of N discrete point charges: r is in the direction from
Physcs 46 Fomula Shee Exam Coulomb s Law qq Felec = k ˆ (Fo example, f F s he elecc foce ha q exes on q, hen ˆ s a un veco n he decon fom q o q.) Elecc Feld elaed o he elecc foce by: Felec = qe (elecc
More informationSTABILITY CRITERIA FOR A CLASS OF NEUTRAL SYSTEMS VIA THE LMI APPROACH
Asan Jounal of Conol, Vol. 6, No., pp. 3-9, Mach 00 3 Bef Pape SABILIY CRIERIA FOR A CLASS OF NEURAL SYSEMS VIA HE LMI APPROACH Chang-Hua Len and Jen-De Chen ABSRAC In hs pape, he asypoc sably fo a class
More informationA L A BA M A L A W R E V IE W
A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N
More informationModern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr.
Moden Enegy Funconal fo Nucle and Nuclea Mae By: lbeo noosa Teas &M Unvesy REU Cycloon 008 Meno: D. Shalom Shlomo Oulne. Inoducon.. The many-body poblem and he aee-fock mehod. 3. Skyme neacon. 4. aee-fock
More informationSuppose we have observed values t 1, t 2, t n of a random variable T.
Sppose we have obseved vales, 2, of a adom vaable T. The dsbo of T s ow o belog o a cea ype (e.g., expoeal, omal, ec.) b he veco θ ( θ, θ2, θp ) of ow paamees assocaed wh s ow (whee p s he mbe of ow paamees).
More informationIn the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!
ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal
More informationCentral limit theorem for functions of weakly dependent variables
Int. Statistical Inst.: Poc. 58th Wold Statistical Congess, 2011, Dublin (Session CPS058 p.5362 Cental liit theoe fo functions of weakly dependent vaiables Jensen, Jens Ledet Aahus Univesity, Depatent
More informationGravity. David Barwacz 7778 Thornapple Bayou SE, Grand Rapids, MI David Barwacz 12/03/2003
avity David Bawacz 7778 Thonapple Bayou, and Rapid, MI 495 David Bawacz /3/3 http://membe.titon.net/daveb Uing the concept dicued in the peceding pape ( http://membe.titon.net/daveb ), I will now deive
More informationActive Load. Reading S&S (5ed): Sec. 7.2 S&S (6ed): Sec. 8.2
cte La ean S&S (5e: Sec. 7. S&S (6e: Sec. 8. In nteate ccuts, t s ffcult t fabcate essts. Instea, aplfe cnfuatns typcally use acte las (.e. las ae w acte eces. Ths can be ne usn a cuent suce cnfuatn,.e.
More informationOn Fractional Operational Calculus pertaining to the product of H- functions
nenonl eh ounl of Enneen n ehnolo RE e-ssn: 2395-56 Volume: 2 ue: 3 une-25 wwwene -SSN: 2395-72 On Fonl Oeonl Clulu enn o he ou of - funon D VBL Chu, C A 2 Demen of hem, Unve of Rhn, u-3255, n E-ml : vl@hooom
More informationAPPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS
Joa of Aed Mahema ad Comaoa Meha 4 3( 6-73 APPLCATON OF A Z-TRANSFORMS METHOD FOR NVESTGATON OF MARKOV G-NETWORKS Mha Maay Vo Nameo e of Mahema Ceohowa Uey of Tehoogy Cęohowa Poad Fay of Mahema ad Come
More informationMotion in Two Dimensions
Phys 1 Chaper 4 Moon n Two Dmensons adzyubenko@csub.edu hp://www.csub.edu/~adzyubenko 005, 014 A. Dzyubenko 004 Brooks/Cole 1 Dsplacemen as a Vecor The poson of an objec s descrbed by s poson ecor, r The
More informationCoupled Mass Transport and Reaction in LPCVD Reactors
ople Ma Tanpo an eaion in LPV eao ile A in B e.g., SiH 4 in H Sepaae eao ino o egion, inaafe & annla b - oniniy Eqn: : onveion-iffion iffion-eaion Eqn Ampion! ile peie i in majo aie ga e.g., H isih 4!
More informationA PATRA CONFERINŢĂ A HIDROENERGETICIENILOR DIN ROMÂNIA,
A PATRA ONFERINŢĂ A HIDROENERGETIIENILOR DIN ROMÂNIA, Do Pael MODELLING OF SEDIMENTATION PROESS IN LONGITUDINAL HORIZONTAL TANK MODELAREA PROESELOR DE SEPARARE A FAZELOR ÎN DEANTOARE LONGITUDINALE Da ROBESU,
More informationChapter 5. Circuit Theorems
Chaper 5 Crcu Theorems Source Transformaons eplace a olage source and seres ressor by a curren and parallel ressor Fgure 5.-1 (a) A nondeal olage source. (b) A nondeal curren source. (c) Crcu B-conneced
More informationJohn Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany
Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy
More informationCalculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( )
Clculu 4, econ Lm/Connuy & Devve/Inel noe y Tm Plchow, wh domn o el Wh we hve o : veco-vlued uncon, ( ) ( ) ( ) j ( ) nume nd ne o veco The uncon, nd A w done wh eul uncon ( x) nd connuy e he componen
More informationCollege of Engineering Department of Electronics and Communication Engineering. Test 2 MODEL ANSWERS
Nae: tudet Nube: ect: ectue: z at Fazea zlee Jehaa y Jaalud able Nube: llee f ee eatet f lectcs ad ucat ee est O N, Y 050 ubject de : B73 use tle : lectcs alyss & es ate : uust 05 e llwed : hu 5 utes stucts
More informationDQ Modeling and Dynamic Characteristics of a Three-Phase Induction Machine
Aecan Jounal of Engneeng Reeach AJER 7 Aecan Jounal of Engneeng Reeach AJER e-issn: -847 p-issn : -96 olue-6, Iue-9, pp-7-5 www.aje.og Reeach Pape Open Acce DQ oelng an Dynac Chaacec of a Thee-Phae Inucon
More informationDetection and Estimation Theory
ESE 54 Detecton and Etmaton Theoy Joeph A. O Sullvan Samuel C. Sach Pofeo Electonc Sytem and Sgnal Reeach Laboatoy Electcal and Sytem Engneeng Wahngton Unvety 411 Jolley Hall 314-935-4173 (Lnda anwe) jao@wutl.edu
More informationProjectile Motion. Parabolic Motion curved motion in the shape of a parabola. In the y direction, the equation of motion has a t 2.
Projectle Moton Phc Inentor Parabolc Moton cured oton n the hape of a parabola. In the drecton, the equaton of oton ha a t ter Projectle Moton the parabolc oton of an object, where the horzontal coponent
More informationMonetary policy and models
Moneay polcy and odels Kes Næss and Kes Haae Moka Noges Bank Moneay Polcy Unvesy of Copenhagen, 8 May 8 Consue pces and oney supply Annual pecenage gowh. -yea ovng aveage Gowh n oney supply Inflaon - 9
More informationGMM parameter estimation. Xiaoye Lu CMPS290c Final Project
GMM paraeer esaon Xaoye Lu M290c Fnal rojec GMM nroducon Gaussan ure Model obnaon of several gaussan coponens Noaon: For each Gaussan dsrbuon:, s he ean and covarance ar. A GMM h ures(coponens): p ( 2π
More informationStrong Result for Level Crossings of Random Polynomials. Dipty Rani Dhal, Dr. P. K. Mishra. Department of Mathematics, CET, BPUT, BBSR, ODISHA, INDIA
Iteatioal Joual of Reseach i Egieeig ad aageet Techology (IJRET) olue Issue July 5 Available at http://wwwijetco/ Stog Result fo Level Cossigs of Rado olyoials Dipty Rai Dhal D K isha Depatet of atheatics
More informationLECTURE 14. m 1 m 2 b) Based on the second law of Newton Figure 1 similarly F21 m2 c) Based on the third law of Newton F 12
CTU 4 ] NWTON W O GVITY -The gavity law i foulated fo two point paticle with ae and at a ditance between the. Hee ae the fou tep that bing to univeal law of gavitation dicoveed by NWTON. a Baed on expeiental
More information[ ] = jω µ [ + jω ε E r
Guided Wave Foulation of Maxwell's Equations I. Geneal Theoy: Recapitulation -- fequency doain foulation of the acoscopic Maxwel l equations in a souce-fee egion: cul E H cul H ( ) jω µ ( ) [ I-1a ] (
More information8.5 Circles and Lengths of Segments
LenghofSegmen20052006.nb 1 8.5 Cicle and Lengh of Segmen In hi ecion we will how (and in ome cae pove) ha lengh of chod, ecan, and angen ae elaed in ome nal way. We will look a hee heoem ha ae hee elaionhip
More informationOrdinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s
Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class
More informationChapter Lagrangian Interpolation
Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and
More informationANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2
Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads
More informationLecture 4. Electrons and Holes in Semiconductors
ecue 4 lec ad Hle i Semicduc I hi lecue yu will lea: eeai-ecmbiai i emicduc i me deail The baic e f euai gveig he behavi f elec ad hle i emicduc Shcley uai Quai-eualiy i cducive maeial C 35 Sig 2005 Faha
More informationChapter 13 - Universal Gravitation
Chapte 3 - Unesal Gataton In Chapte 5 we studed Newton s thee laws of moton. In addton to these laws, Newton fomulated the law of unesal gataton. Ths law states that two masses ae attacted by a foce gen
More informationThe far field calculation: Approximate and exact solutions. Persa Kyritsi November 10th, 2005 B2-109
Th fa fl calculao: Appoa a ac oluo Pa K Novb 0h 005 B-09 Oul Novb 0h 005 Pa K Iouco Appoa oluo flco fo h gou ac oluo Cocluo Pla wav fo Ic fl: pla wav k ( ) jk H ( ) λ λ ( ) Polaao fo η 0 0 Hooal polaao
More informationON THE EXTENSION OF WEAK ARMENDARIZ RINGS RELATIVE TO A MONOID
wwweo/voue/vo9iue/ijas_9 9f ON THE EXTENSION OF WEAK AENDAIZ INGS ELATIVE TO A ONOID Eye A & Ayou Eoy Dee of e Nowe No Uvey Lzou 77 C Dee of e Uvey of Kou Ou Su E-: eye76@o; you975@yooo ABSTACT Fo oo we
More information(8) Gain Stage and Simple Output Stage
EEEB23 Electoncs Analyss & Desgn (8) Gan Stage and Smple Output Stage Leanng Outcome Able to: Analyze an example of a gan stage and output stage of a multstage amplfe. efeence: Neamen, Chapte 11 8.0) ntoducton
More informationA Demand System for Input Factors when there are Technological Changes in Production
A Demand Syem for Inpu Facor when here are Technologcal Change n Producon Movaon Due o (e.g.) echnologcal change here mgh no be a aonary relaonhp for he co hare of each npu facor. When emang demand yem
More informationTHEORETICAL AUTOCORRELATIONS. ) if often denoted by γ. Note that
THEORETICAL AUTOCORRELATIONS Cov( y, y ) E( y E( y))( y E( y)) ρ = = Var( y) E( y E( y)) =,, L ρ = and Cov( y, y ) s ofen denoed by whle Var( y ) f ofen denoed by γ. Noe ha γ = γ and ρ = ρ and because
More information4/3/2017. PHY 712 Electrodynamics 9-9:50 AM MWF Olin 103
PHY 7 Eleodnais 9-9:50 AM MWF Olin 0 Plan fo Leue 0: Coninue eading Chap Snhoon adiaion adiaion fo eleon snhoon deies adiaion fo asonoial objes in iula obis 0/05/07 PHY 7 Sping 07 -- Leue 0 0/05/07 PHY
More informationThen the number of elements of S of weight n is exactly the number of compositions of n into k parts.
Geneating Function In a geneal combinatoial poblem, we have a univee S of object, and we want to count the numbe of object with a cetain popety. Fo example, if S i the et of all gaph, we might want to
More information