Gradient Flow Independent Component Analysis
|
|
- Emily Hines
- 5 years ago
- Views:
Transcription
1 Graden Fow Independen Componen Anay Mun Sanaćevć and Ger Cauwenbergh Adapve Mcroyem ab John Hopkn Unvery
2 Oune Bnd Sgna Separaon and ocazaon Prncpe of Graden Fow : from deay o empora dervave Equvaen ac near ICA probem Expermena eparaon reu Spary Independence of graden obervaon Monaura ource eparaon Concuon
3 Bnd Separaon and ocazaon Modeng Source gna propagae a raveng wave n free pace Spaay dvere enor array receve near mxure of medeayed ource The me deay deermne he drecon coordnae of he wave reave o he enor geomery Mehod Super-reouon echnque emae he me deay n he pecra doman, aumng narrowband ource Jon emaon of mupe broadband ource and her me deay pobe n an exended ICA framework, bu requre non-convex opmzaon eadng o unpredcabe performance
4 ( Tempora Sere Expanon + τ ( r)) = ( + τ ( r) & ( + τ ( r) && ( + K deay 0 h -order -order nd -order 3 rd -order 4 h -order Reduce he probem of denfyng me deayed ource mxure o ha of eparang ac mxure of he me-dfferenaed ource Impe ubwaveengh geomery of he enor array
5 Graden Fow Prncpe τ ( + τ ) ξ 0 τ ξ 0 ξ & 00 τ &( τ ( d d [ ] τ τ - ξ& ξ ξ & ( τ & ( τ & ( Graden fow bearng reouon fundamenay ndependen of aperure Reouon deermned by envy of graden acquon Mechanca dfferena coupng (Me e a.) Opca dfferena coupng (Degerekn) Anaog VSI dfferena coupng
6 Separaon and ocazaon Source mxure are oberved wh addve enor noe: Graden fow reduce o a ac (noy) mxure probem: oved by mean of near ac ICA ) ( ) ( ) ( n x pq pq pq + + = = τ n A x + = + = ) ( ) ( ν ν ν τ τ τ τ ξ ξ ξ & & M & & drecon vecor ource (me-dfferenaed) obervaon (graden) noe (graden)
7 Order k, dmenon m: Scang Propere j h ( j... h) j... h ( τ ) ( τ )...( τ n ) ( ν j... h = k m ξ + } x = A + n } Maxmum eparabe number of ource max : m 0 3 k Aume fu-rank A wh neary ndependen mxure combnaon Depend on he geomery of he ource drecon vecor reave o he array
8 Graden Fow Acouc Separaon Oudoor Envronmen 4 mcrophone whn 5 mm radu mae peaker a 0.5 m, awn urrounded by budng a 30 m cm
9 Graden Fow Acouc Separaon Indoor Envronmen 4 mcrophone whn 5 mm radu mae peaker a 0.5 m, reverberan room of dmenon 3, 4 and 8 m cm
10 Monaura Source Separaon: Pror Seecon Evdence of mxng mode : x( ( + n( Source eparaon from a nge ource ambguou, une he ource ( have a known rucure. The pror ha o be carefuy choen, accounng for he phyc of he probem.
11 Coherence a Acouc Pror Pror on ource mode : ~ ( ~ A ( ( θ ( ) ~ ( qua-perodc,.e. hor-erm perodc (evera cyce) Shor-erm coherence of a ource can be expreed n erm of me θ and ampude A fucuaon of a perodc waveform Thee fucuaon aow o dnguh and eparae he ource even f hey overap n he pecra doman.
12 Tme-Doman Monaura Separaon + x( ( n( ( A ( ( θ ( ) Succefu eparaon of wo frequency-chrped and ampudemoduaed quaperodc waveform. Separaon ucceed even hough harmonc of he nananeou frequence of he ource concde a wo nance of me. G.Cauwenbergh, Monaura Separaon of Independen Acouca Componen, ISCAS 99
13 Reaon o graden fow. A( ( θ ( ) A( ( ( + θ ( ( ) = A( ( + A( θ ( (. Ampude Co-Moduaon Phae Co-Moduaon Work n progre
14 Concuon A mehod for ocazng and eparang broadband wave propagang n free pace for array of dmenon maer han he hore waveengh n he ource ha been decrbed. Wave graden fow conver he probem o ha of ac ICA, wh mxng coeffcen yedng he drecon cone of he ource. The echnque baed on a merc of coherence ha expree each ource a a qua-perodc waveform wh random hor-erm me and ampude fucuaon wa preened. We pan o exend graden fow prncpe o monaura ource eparaon.
A 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 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 informationCooling of a hot metal forging. , dt dt
Tranen Conducon Uneady Analy - Lumped Thermal Capacy Model Performed when; Hea ranfer whn a yem produced a unform emperaure drbuon n he yem (mall emperaure graden). The emperaure change whn he yem condered
More informationNotes on the stability of dynamic systems and the use of Eigen Values.
Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon
More informationSimultaneous Localization of Mobile Robot and Multiple Sound Sources Using Microphone Array
Smulaneou Localzaon o Moble Robo and Mulple Sound Source Ung Mcrophone Array Jwu-Sheng Hu, Chen-Yu Chan, Cheng-Kang Wang Deparmen o Elecrcal and Conrol Engneerng aonal Chao-ung Unvery Hnchu, awan, R.O.C.
More informationChapter 6: AC Circuits
Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.
More informationControl Systems. Mathematical Modeling of Control Systems.
Conrol Syem Mahemacal Modelng of Conrol Syem chbum@eoulech.ac.kr Oulne Mahemacal model and model ype. Tranfer funcon model Syem pole and zero Chbum Lee -Seoulech Conrol Syem Mahemacal Model Model are key
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ
More informationModel-Based FDI : the control approach
Model-Baed FDI : he conrol approach M. Saroweck LAIL-CNRS EUDIL, Unver Llle I Olne of he preenaon Par I : model Sem, normal and no normal condon, fal Par II : he decon problem problem eng noe, drbance,
More informationH = d d q 1 d d q N d d p 1 d d p N exp
8333: Sacal Mechanc I roblem Se # 7 Soluon Fall 3 Canoncal Enemble Non-harmonc Ga: The Hamlonan for a ga of N non neracng parcle n a d dmenonal box ha he form H A p a The paron funcon gven by ZN T d d
More informationAdvanced Machine Learning & Perception
Advanced Machne Learnng & Percepon Insrucor: Tony Jebara SVM Feaure & Kernel Selecon SVM Eensons Feaure Selecon (Flerng and Wrappng) SVM Feaure Selecon SVM Kernel Selecon SVM Eensons Classfcaon Feaure/Kernel
More informationTSS = SST + SSE An orthogonal partition of the total SS
ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally
More informationScattering at an Interface: Oblique Incidence
Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may
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 informationLecture 9: Dynamic Properties
Shor Course on Molecular Dynamcs Smulaon Lecure 9: Dynamc Properes Professor A. Marn Purdue Unversy Hgh Level Course Oulne 1. MD Bascs. Poenal Energy Funcons 3. Inegraon Algorhms 4. Temperaure Conrol 5.
More informationChapter 5 Signal-Space Analysis
Chaper 5 Sgnal-Space Analy Sgnal pace analy provde a mahemacally elegan and hghly nghful ool for he udy of daa ranmon. 5. Inroducon o Sacal model for a genec dgal communcaon yem n eage ource: A pror probable
More informationDEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL
DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL Sco Wsdom, John Hershey 2, Jonahan Le Roux 2, and Shnj Waanabe 2 Deparmen o Elecrcal Engneerng, Unversy o Washngon, Seale, WA, USA
More informationSingle-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method
10 h US Naonal Congress on Compuaonal Mechancs Columbus, Oho 16-19, 2009 Sngle-loop Sysem Relably-Based Desgn & Topology Opmzaon (SRBDO/SRBTO): A Marx-based Sysem Relably (MSR) Mehod Tam Nguyen, Junho
More informationu(t) Figure 1. Open loop control system
Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference
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 informationCHAPTER 7: CLUSTERING
CHAPTER 7: CLUSTERING Semparamerc Densy Esmaon 3 Paramerc: Assume a snge mode for p ( C ) (Chapers 4 and 5) Semparamerc: p ( C ) s a mure of denses Mupe possbe epanaons/prooypes: Dfferen handwrng syes,
More informationProblem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.
CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex
More informationRobustness Experiments with Two Variance Components
Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference
More informationby Lauren DeDieu Advisor: George Chen
b Laren DeDe Advsor: George Chen Are one of he mos powerfl mehods o nmercall solve me dependen paral dfferenal eqaons PDE wh some knd of snglar shock waves & blow-p problems. Fed nmber of mesh pons Moves
More informationMachine Learning Linear Regression
Machne Learnng Lnear Regresson Lesson 3 Lnear Regresson Bascs of Regresson Leas Squares esmaon Polynomal Regresson Bass funcons Regresson model Regularzed Regresson Sascal Regresson Mamum Lkelhood (ML)
More informationMath 315: Linear Algebra Solutions to Assignment 6
Mah 35: Linear Algebra s o Assignmen 6 # Which of he following ses of vecors are bases for R 2? {2,, 3, }, {4,, 7, 8}, {,,, 3}, {3, 9, 4, 2}. Explain your answer. To generae he whole R 2, wo linearly independen
More informationDynamic analysis of hoisting viscous damping string with time-varying length
Journa of Physcs: Conference Seres OPEN ACCESS Dynamc anayss of hosng vscous dampng srng wh me-varyng engh To ce hs arce: P Zhang e a 3 J. Phys.: Conf. Ser. 448 Vew he arce onne for updaes and enhancemens.
More informationPanel Data Regression Models
Panel Daa Regresson Models Wha s Panel Daa? () Mulple dmensoned Dmensons, e.g., cross-secon and me node-o-node (c) Pongsa Pornchawseskul, Faculy of Economcs, Chulalongkorn Unversy (c) Pongsa Pornchawseskul,
More informationAdditional File 1 - Detailed explanation of the expression level CPD
Addtonal Fle - Detaled explanaton of the expreon level CPD A mentoned n the man text, the man CPD for the uterng model cont of two ndvdual factor: P( level gen P( level gen P ( level gen 2 (.).. CPD factor
More informationANALYSIS AND MODELING OF HYDROLOGIC TIME SERIES. Wasserhaushalt Time Series Analysis and Stochastic Modelling Spring Semester
ANALYSIS AND MODELING OF HYDROLOGIC TIME SERIES Waerhauhal Tme Sere Analy and Sochac Modellng Sprng Semeer 8 ANALYSIS AND MODELING OF HYDROLOGIC TIME SERIES Defnon Wha a me ere? Leraure: Sala, J.D. 99,
More informationParameters Estimation in a General Failure Rate Semi-Markov Reliability Model
Joura of Saca Theory ad Appcao Vo. No. (Sepember ) - Parameer Emao a Geera Faure Rae Sem-Marov Reaby Mode M. Fahzadeh ad K. Khorhda Deparme of Sac Facuy of Mahemaca Scece Va-e-Ar Uvery of Rafaja Rafaja
More informationLecture 11: Stereo and Surface Estimation
Lecure : Sereo and Surface Emaon When camera poon have been deermned, ung rucure from moon, we would lke o compue a dene urface model of he cene. In h lecure we wll udy he o called Sereo Problem, where
More informationCONSTRUCTING AN INFORMATION MATRIX FOR MULTIVARIATE DCC-MGARCH (1, 1) METHOD
VOL 13 NO 8 APRIL 018 ISSN 1819-6608 ARPN Journal of Engneerng and Appled Scence 006-018 Aan Reearch Pulhng Nework (ARPN) All rgh reerved wwwarpnjournalcom CONSRUCING AN INFORMAION MARIX FOR MULIVARIAE
More informationIncluding the ordinary differential of distance with time as velocity makes a system of ordinary differential equations.
Soluons o Ordnary Derenal Equaons An ordnary derenal equaon has only one ndependen varable. A sysem o ordnary derenal equaons consss o several derenal equaons each wh he same ndependen varable. An eample
More informationA Principled Approach to MILP Modeling
A Prncpled Approach o MILP Modelng John Hooer Carnege Mellon Unvers Augus 008 Slde Proposal MILP modelng s an ar, bu need no be unprncpled. Slde Proposal MILP modelng s an ar, bu need no be unprncpled.
More informationSystem of Linear Differential Equations
Sysem of Linear Differenial Equaions In "Ordinary Differenial Equaions" we've learned how o solve a differenial equaion for a variable, such as: y'k5$e K2$x =0 solve DE yx = K 5 2 ek2 x C_C1 2$y''C7$y
More information[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5
TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres
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 informationDynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005
Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc
More informationL N O Q. l q l q. I. A General Case. l q RANDOM LAGRANGE MULTIPLIERS AND TRANSVERSALITY. Econ. 511b Spring 1998 C. Sims
Econ. 511b Sprng 1998 C. Sm RAD AGRAGE UPERS AD RASVERSAY agrange mulpler mehod are andard fare n elemenary calculu coure, and hey play a cenral role n economc applcaon of calculu becaue hey ofen urn ou
More informationHEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD
Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,
More informationWhat is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models
Wha i maximum Likelihood? Hiory Feaure of ML mehod Tool ued Advanage Diadvanage Evoluionary model Maximum likelihood mehod creae all he poible ree conaining he e of organim conidered, and hen ue he aiic
More informationOnline EM Algorithm for Background Subtraction
Avalable onlne a www.cencedrec.com Proceda Engneerng 9 (0) 64 69 0 Inernaonal Workhop on Informaon and Elecronc Engneerng (IWIEE) Onlne E Algorhm for Background Subracon Peng Chen a*, Xang Chen b,bebe
More informationMechanical Property Analysis with Ultrasonic Phased Array
7th Word onference on Nondetructve Tetng, 25-28 Oct 28, Shangha, hna Mechanca Property Anay wth Utraonc Phaed Array Wen-A SONG, Ke-Y YUAN, Y-Fang HEN, Hu-Mng YAN 2 Department of Mechanca Engneerng, Tnghua
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 informationCHAPTER 10: LINEAR DISCRIMINATION
CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g
More informationTranscription: Messenger RNA, mrna, is produced and transported to Ribosomes
Quanave Cenral Dogma I Reference hp//book.bonumbers.org Inaon ranscrpon RNA polymerase and ranscrpon Facor (F) s bnds o promoer regon of DNA ranscrpon Meenger RNA, mrna, s produced and ranspored o Rbosomes
More informationHow about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?
lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of
More informationSeasonal Adjustment Programs. 1. Introduction
Bernhard Hammer 010394 Klau Prener 001418 Seaonal Adumen Program Chaper 4: "The Economerc Anal of Seaonal Tme Sere (Ghel, Oborn, 001) 1. Inroducon A procedure ha fler he eaonal flucuaon from a me ere called
More informationEEL 6266 Power System Operation and Control. Chapter 5 Unit Commitment
EEL 6266 Power Sysem Operaon and Conrol Chaper 5 Un Commmen Dynamc programmng chef advanage over enumeraon schemes s he reducon n he dmensonaly of he problem n a src prory order scheme, here are only N
More informationLaplace Transformation of Linear Time-Varying Systems
Laplace Tranformaon of Lnear Tme-Varyng Syem Shervn Erfan Reearch Cenre for Inegraed Mcroelecronc Elecrcal and Compuer Engneerng Deparmen Unvery of Wndor Wndor, Onaro N9B 3P4, Canada Aug. 4, 9 Oulne of
More informationFTCS Solution to the Heat Equation
FTCS Soluon o he Hea Equaon ME 448/548 Noes Gerald Reckenwald Porland Sae Unversy Deparmen of Mechancal Engneerng gerry@pdxedu ME 448/548: FTCS Soluon o he Hea Equaon Overvew Use he forward fne d erence
More information. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue.
Lnear Algebra Lecure # Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons
More informationClustering (Bishop ch 9)
Cluserng (Bshop ch 9) Reference: Daa Mnng by Margare Dunham (a slde source) 1 Cluserng Cluserng s unsupervsed learnng, here are no class labels Wan o fnd groups of smlar nsances Ofen use a dsance measure
More informationNotes on cointegration of real interest rates and real exchange rates. ρ (2)
Noe on coinegraion of real inere rae and real exchange rae Charle ngel, Univeriy of Wiconin Le me ar wih he obervaion ha while he lieraure (mo prominenly Meee and Rogoff (988) and dion and Paul (993))
More informationMEEN Handout 4a ELEMENTS OF ANALYTICAL MECHANICS
MEEN 67 - Handou 4a ELEMENTS OF ANALYTICAL MECHANICS Newon's laws (Euler's fundamenal prncples of moon) are formulaed for a sngle parcle and easly exended o sysems of parcles and rgd bodes. In descrbng
More informationMIMO principles. s1(t) y1(t) H(,t) ( t) s2(t) y2(t) Helka Määttänen. paper provides a general overview of this promising transmission technique.
S-7.333 Pograduae Coure n Rado Communcaon 1 IO prncple ela ääänen I. IRODUCIO e growng demand of mulmeda ervce and e grow of Inerne relaed conen lead o ncreang nere o g peed communcaon. e requremen for
More information. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue.
Mah E-b Lecure #0 Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons are
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 informationOn One Analytic Method of. Constructing Program Controls
Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna
More informationEFFICIENT TRAINING OF RBF NETWORKS VIA THE KURTOSIS AND SKEWNESS MINIMIZATION LEARNING ALGORITHM
Journa o heoreca and Apped Inormaon echnoogy 0 h February 03. Vo. 48 o. 005-03 JAI & LLS. A rghs reserved. ISS: 99-8645 www.a.org E-ISS: 87-395 EFFICIE RAIIG OF RBF EWORKS VIA HE KUROSIS AD SKEWESS MIIMIZAIO
More informationTHE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS
THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he
More informationThruster Modulation for Unsymmetric Flexible Spacecraft with Consideration of Torque Arm Perturbation
hruer Modulaon for Unymmerc Flexble Sacecraf wh onderaon of orue rm Perurbaon a Shgemune anwak Shnchro chkawa a Yohak hkam b a Naonal Sace evelomen gency of Jaan 2-- Sengen ukuba-h barak b eo Unvery 3--
More informationDelay 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 informationSSRG International Journal of Thermal Engineering (SSRG-IJTE) Volume 4 Issue 1 January to April 2018
SSRG Inernaonal Journal of Thermal Engneerng (SSRG-IJTE) Volume 4 Iue 1 January o Aprl 18 Opmal Conrol for a Drbued Parameer Syem wh Tme-Delay, Non-Lnear Ung he Numercal Mehod. Applcaon o One- Sded Hea
More informationLaser Interferometer Space Antenna (LISA)
aser nerferomeer Sace Anenna SA Tme-elay nerferomery wh Movng Sacecraf Arrays Massmo Tno Je Proulson aboraory, Calforna nsue of Technology GSFC JP 8 h GWAW, ec 7-0, 00, Mlwaukee, Wsconsn WM Folkner e al,
More informationLecture 18: The Laplace Transform (See Sections and 14.7 in Boas)
Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on
More informationWrap up: Weighted, directed graph shortest path Minimum Spanning Tree. Feb 25, 2019 CSCI211 - Sprenkle
Objecive Wrap up: Weighed, direced graph hore pah Minimum Spanning Tree eb, 1 SI - Sprenkle 1 Review Wha are greedy algorihm? Wha i our emplae for olving hem? Review he la problem we were working on: Single-ource,
More informationDelay-Limited Cooperative Communication with Reliability Constraints in Wireless Networks
ource relay 1 relay 2 relay m PROC. IEEE INFOCOM, RIO DE JANEIRO, BRAZIL, APRIL 2009 1 Delay-Lmed Cooperave Communcaon wh Relably Conran n rele Nework Rahul Urgaonkar, Mchael J. Neely Unvery of Souhern
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 informationNPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management
P age NPTEL Proec Economerc Modellng Vnod Gua School of Managemen Module23: Granger Causaly Tes Lecure35: Granger Causaly Tes Rudra P. Pradhan Vnod Gua School of Managemen Indan Insue of Technology Kharagur,
More informationE β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem.
Noes, M. Krause.. Problem Se 9: Exercise on FTPL Same model as in paper and lecure, only ha one-period govenmen bonds are replaced by consols, which are bonds ha pay one dollar forever. I has curren marke
More informationFundamentals of PLLs (I)
Phae-Locked Loop Fundamenal of PLL (I) Chng-Yuan Yang Naonal Chung-Hng Unvery Deparmen of Elecrcal Engneerng Why phae-lock? - Jer Supreon - Frequency Synhe T T + 1 - Skew Reducon T + 2 T + 3 PLL fou =
More informationCTLS 4 SNR. Multi Reference CTLS Method for Passive Localization of Radar Targets
دا ند رعا ل» ی و ناوری ج ه ع ی و ی «ع وم 79-85 9 C 4 * Donloaded from ad.r a 9:06 +040 on Frda arch nd 09-4 - - - - (9/06/4 : 90/05/7 : ) DOA. DOA. C DOA.. C.. C SR.. C.C DOA : ul Reference C ehod for
More informationWEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x
WEEK-3 Reciaion PHYS 131 Ch. 3: FOC 1, 3, 4, 6, 14. Problems 9, 37, 41 & 71 and Ch. 4: FOC 1, 3, 5, 8. Problems 3, 5 & 16. Feb 8, 018 Ch. 3: FOC 1, 3, 4, 6, 14. 1. (a) The horizonal componen of he projecile
More informationPHYS 1443 Section 001 Lecture #4
PHYS 1443 Secon 001 Lecure #4 Monda, June 5, 006 Moon n Two Dmensons Moon under consan acceleraon Projecle Moon Mamum ranges and heghs Reerence Frames and relae moon Newon s Laws o Moon Force Newon s Law
More informationt is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...
Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger
More informationBlock compressed sensing of video based on unstable sampling rates and multihypothesis predictions
ISSN : 0974-745 Voume 0 Issue 7 BoTechnoog BoTechnoog An Indan Journa BTAIJ, 0(7), 04 [95-95] Bock compressed sensng of vdeo based on unsabe sampng raes and muhpohess predcons Zhao Chengn *, Lu Jangun
More informationCS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4
CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped
More informationSklar: Sections (4.4.2 is not covered).
COSC 44: Dgal Councaons Insrucor: Dr. Ar Asf Deparen of Copuer Scence and Engneerng York Unversy Handou # 6: Bandpass Modulaon opcs:. Phasor Represenaon. Dgal Modulaon Schees: PSK FSK ASK APK ASK/FSK)
More informationThen. 1 The eigenvalues of A are inside R = n i=1 R i. 2 Union of any k circles not intersecting the other (n k)
Ger sgorin Circle Chaper 9 Approimaing Eigenvalues Per-Olof Persson persson@berkeley.edu Deparmen of Mahemaics Universiy of California, Berkeley Mah 128B Numerical Analysis (Ger sgorin Circle) Le A be
More information2.1 Constitutive Theory
Secon.. Consuve Theory.. Consuve Equaons Governng Equaons The equaons governng he behavour of maerals are (n he spaal form) dρ v & ρ + ρdv v = + ρ = Conservaon of Mass (..a) d x σ j dv dvσ + b = ρ v& +
More informationDuality Model of TCP/AQM
Optimization and Contro of Network Duaity Mode of TCP/AQM Lijun Chen 02/08/2016 Agenda Utiity maimization and dua decompoition An introduction to TCP congetion contro A genera dynamica mode of TCP/AQM
More informationGraduate Macroeconomics 2 Problem set 5. - Solutions
Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K
More information0 of the same magnitude. If we don t use an OA and ignore any damping, the CTF is
1 4. Image Simulation Influence of C Spherical aberration break the ymmetry that would otherwie exit between overfocu and underfocu. One reult i that the fringe in the FT of the CTF are generally farther
More informationON THE DEGREES OF RATIONAL KNOTS
ON THE DEGREES OF RATIONAL KNOTS DONOVAN MCFERON, ALEXANDRA ZUSER Absrac. In his paper, we explore he issue of minimizing he degrees on raional knos. We se a bound on hese degrees using Bézou s heorem,
More informationSINGLE CHANNEL SOURCE SEPARATION USING STATIC AND DYNAMIC FEATURES IN THE POWER DOMAIN
SINGLE CHANNEL SOURCE SEPARATION USING STATIC AND DYNAMIC FEATURES IN THE POWER DOMAIN Ilya Poa ± Alexey Ozerov ± Deparen of Muc Technology Acouc Technologcal Educaonal Inue of Cree E. Dakalak - Pervola
More informationCH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC
CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal
More informationA NUMERICAL ANALYSIS OF FLOW AND DISPERSION AROUND A CUBE
A NUMERICAL ANALYSIS OF FLOW AND DISPERSION AROUND A CUBE $%675$&7 Ths work descrbes he compuaona fud dynamc (CFD) smuaon of fow and pouan dsperson around a cube. The work aemps o mode he characerscs of
More informationDYNAMIC ANALYSIS OF BRIDGES SUBJECTED TO MOVING VEHICLES
Mahmood: Dynamc Anayss Of Brdges Subjeced o Mong Vehces DYNAMIC ANALYSIS OF BRIDGES SUBJECTED TO MOVING VEHICLES Dr. Mohamad Najm Mahmood Ayad Thab Saeed A-Ghabsha Asssan Professor Asssan Lecurer C Engneerng
More informationLesson 2 Transmission Lines Fundamentals
Lesson Transmsson Lnes Funamenals 楊尚達 Shang-Da Yang Insue of Phooncs Technologes Deparmen of Elecrcal Engneerng Naonal Tsng Hua Unersy Tawan Sec. -1 Inroucon 1. Why o scuss TX lnes srbue crcus?. Crera
More informationLet us start with a two dimensional case. We consider a vector ( x,
Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our
More informationReal Time Optimization of Traffic Signal Control: Application to Coordinated Intersections
Rea Tme Opmzaon o Trac Sgna Conro: Appcaon o Coordnaed Inersecons Maragraza Doo Mara Pa Fan Caro Meon Dparmeno d Eeroecnca ed Eeronca Poecnco d Bar Bar, Iay doo@deema.poba. Dparmeno d Eeroecnca ed Eeronca
More informationAn adaptive approach to small object segmentation
An adapve approach o small ojec segmenaon Shen ngzh ang Le Dep. of Elecronc Engneerng ejng Insue of echnology ejng 8 Chna Asrac-An adapve approach o small ojec segmenaon ased on Genec Algorhms s proposed.
More informationA new topology for quasi-z-source inverter
pp.: A new opology or qua-z-ource nerer Negar Mrkazeman, Ebrahm Babae Elecrcal Engneerng Deparmen, Shabear Branch, Ilamc Azad Unery, Shabear, Iran, Emal:negarmrkazeman@auhab.ac.r Elecrcal and Compuer Engneerng,
More informationFlow networks. Flow Networks. A flow on a network. Flow networks. The maximum-flow problem. Introduction to Algorithms, Lecture 22 December 5, 2001
CS 545 Flow Nework lon Efra Slide courey of Charle Leieron wih mall change by Carola Wenk Flow nework Definiion. flow nework i a direced graph G = (V, E) wih wo diinguihed verice: a ource and a ink. Each
More informationDensity Matrix Description of NMR BCMB/CHEM 8190
Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary
More informationMechanics Physics 151
Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu
More information5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method
ME 352 GRHICL VELCITY NLYSIS 52 GRHICL VELCITY NLYSIS olygon Mehod Velociy analyi form he hear of kinemaic and dynamic of mechanical yem Velociy analyi i uually performed following a poiion analyi; ie,
More informationVIII. Addition of Angular Momenta
VIII Addition of Anguar Momenta a Couped and Uncouped Bae When deaing with two different ource of anguar momentum, Ĵ and Ĵ, there are two obviou bae that one might chooe to work in The firt i caed the
More information