The Indefinite Admittance Matrix
|
|
- Arthur Wade
- 5 years ago
- Views:
Transcription
1 Subject: ndefinite Adittance Matrices Date: June 6, 998 The ndefinite Adittance Matrix The indefinite adittance atrix, designated F for short, is a circuit analsis technique i,ii,iii which lends itself well to an topolog. Once the nodal equations of the circuit are written, basic inherent properties of the F allow an N N adittance atrix to be collapsed to a twoport adittance atrix. Fro this point, R standard two-port relationships in either - or S- paraeters can be utilized to calculate input, output ipedance, voltage or power gain, R stabilit, etc. R A fundaental propert of the F technique is that an individual row or colun of the F atrix sus to zero. This is due to Kirchoff s current law at each node. One inor exception to this rule, however, is in the presence of independent current sources connecting specific nodes. n those cases the suation of currents will not equal zero. Figure best illustrates the application of the Figure F ethod. Standard nodal equations at each of the individual nodes are written; these are given in []. Rewriting [] in standard atrix for gives [] which, adopting standard adittance notation, can be equivalentl expressed as in []. REF g ( - ),, g, g,, g, g,, [] g, g, g g,,,,,, [] where is adittance and,,,,,, [], = +, = -, = -, = -( + g ) = +, + g, = -,, = -( g, = -(, + g ), =, +, n actual use the F atrix is converted first, through a series of atrix reduction ethods, fro an N N atrix to a atrix coposed of a) input, b) output, and c) rerence nodes. At this point in tie an one of the three nodes can be considered the rerence. Once the rerence node is identified and the reduction fro the to a final atrix copleted, the indefinite atrix becoes definite. When the rerence is identified, all voltages for the reaining two ports are rerenced to this rerence node with none of the reaining nodes floating. ( J.E. Crawford All Rights Reserved )
2 Subject: ndefinite Adittance Matrices Date: June 6, 998 f onl of the 9 eleents in a F atrix are known, it is possible to coplete all entries of the atrix using the zero-su propert that each colun and row ust obe. The reverse operation on the definite atrix in this anner allows the rerence to be shifted to a difrent node, i.e. coon-base versus a coon-eitter configuration. Once again if independent sources are present, the zero-row, zero-colun properties do not hold. f the circuit network is passive, the F atrix is also setrical. The F atrix for the transistor is shown in [] and Figure. t is a siple algebraic atter to absorb the rerence terinal ( base, eitter, or collector ) as the rerence culinating in two-port -paraeters for the respective transistor topolog. [] b c e bb cb eb bc cc ec be ce ee F cc ce [] ec ee B C E [] b B Transistor e E c C REF Figure oltages & Currents for Transistor When E is set to zero, for exaple, the indefinite atrix in [] and Figure describes the coon-eitter configuration. The F in [] describes a coon-base configuration. To coplete the atrix the zero-su propert of the atrix can be used, giving [6]. ob fb rb ib ob rb fb ib F ob fb ob fb [6] rb ib rb ib The steps to deterine the indefinite atrix for the overall network are the following:. abel each node. Break the circuit up into coponent networks one network for the passive eleents and separate networks for each active eleent. Deterine the F for each coponent network. Add the individual Fs to give the coplete indefinite atrix. Each of the atrices for the coponent networks, as well as the overall atrix, have diensions of N N, where N is the nuber of nodes in the circuit. The row and colun that correspond to an unconnected node of the coponent network are set to zero. For a circuit fragent that includes a transistor, the letters B, E, and C are placed against the respective nodes to which the base, eitter, and collector are connected. These three nodes are treated as if the were the indefinite atrix that represents the transistor. Specificall, for a coon-eitter transistor connected with ( B, E, C ) to nodes (,, ) respectivel, the following sub-atrix, and, B, E, C associated row-colun nubers, applies., B F, E, C bb cb ie bc Application of the zero-su propert for rows and coluns ( J.E. Crawford All Rights Reserved ) cc re oe [7]
3 Subject: ndefinite Adittance Matrices Date: June 6, 998 copletes the atrix in [7] as shown in [8]. The final result is obtained b transrring the eleents to their proper position in the N N atrix for the coplete network. The F atrix for the passive portion of the circuit can be written b inspection, following the following rules:. Each diagonal eleent rr equals the su of all adittances connected to node r.. An off-diagonal eleent rs equals inus the adittance connected between node r and node s.. Eleents in rows and coluns that correspond to unconnected nodes are zero. F, B, E, C, B ie ie ie re oe re oe, E ie oe re, C oe re [8] n the process of node reduction to a final adittance atrix, the nodes which are suppressed are no longer available for connection to external coponents or other sources. The corresponding current at each of these nodes, j, ust be zero. For exaple, if node is being suppressed for a circuit with a total of nodes, the current entering node is identicall zero, giving [9]. 0,,, [9] The expression in [9] is then used to solve for, and this expression added back to the original atrix for all entries of, thus suppressing an rerence to.,,, For an exaple circuit in which node is reoved, the expression in [0] is substituted for all appearances of in the nodal equation, giving for the first row of the new, reduced atrix that in []. After consolidating and siplifing ters, [] takes on the for of []. [0],,,,,,, [],,,,,, [] The copleted F after the suppression of node is shown in []. A further suppression of nodes is then perfored, driving toward having a defined rerence and input and output nodes. At this point, coon two-port relationships are then applied. ( J.E. Crawford All Rights Reserved )
4 Subject: ndefinite Adittance Matrices Date: June 6, 998,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Reduced Adittance Matrix After Suppression of Node,,,,,,, [] Using the copleted two-port adittance paraeters, the following calculations iv of interest a be perfored. Alternativel, a transforation fro to S paraeters a be ade and a siilar set of calculations perfored in the S-doain. oltage Gain A A Current Gain,, nput Adittance Output Adittance Stern K-Factor in out, K,,, where S g, GS g G Re n the actual reduction forulation, the first process is to order the coluns and rows to reflect the nodes desired for input, output, and rerence, respectivel, in order,, and. Then the reduction coences eliinating row/colun N, followed b N-, etc. until onl a F atrix reains. Before each successive reduction, additional reordering aong the rows/coluns reaining to be suppressed should be done to iniize round-off errors, etc. The actual procedure suitable for this atrix reduction is shown in the Appendix. ( J.E. Crawford All Rights Reserved )
5 Subject: ndefinite Adittance Matrices Date: June 6, 998 Appendix oid Reduce_Mat( int n_node, int Out_node, N int) Den double; // agnitude of rr r int; // row and colun being used i,j int; int; // argest diagonal eleent row XX double; // real part of coon ter double; // iaginar part of coon ter S, S double; // tests for largest diagonal eleent oid Swap( double x, double x) XX double; XX = x; x = ; = XX; f( n_node <> ) or ( Out_node <> ) then for j = to N do Swap( [,j].r, [n_node,j].r; Swap( [,j].i, [n_node,j].i; Swap( [,j].r, [Out_node,j].r; Swap( [,j].i, [Out_node,j].i; for j = to N do Swap( [j,].r, [j, n_node].r; Swap( [j,].i, [j, n_node].i; Swap( [j,].r, [j, Out_node].r; Swap( [j,].i, [j, Out_node].i; while N > do = ; S = abs([,].r) + abs([,].i); f N > then for i = to N do S = abs([,].r) + abs([,].i); f S > S then Begin S = S; = ; if <> N then // swap n and Out ( J.E. Crawford All Rights Reserved )
6 Subject: ndefinite Adittance Matrices Date: June 6, 998 for j = to N do Swap( [,j].r, [N,j].r); Swap( [,j].i, [N,j].i); For j = to N do Swap( [j,].r, [j,n].r); Swap( [j,].i, [j,n].i); Den = sqr([n,n].r) + sqr([n,n].i); R = N; N = N-; for i = to N do if([i,r].r <> 0) or ([i,r].i <> 0 ) then XX = ([,r].r * [r,r].r + [r,r].i*[,r].i) / Den; = ([r,r].r * [,r].i [,r].r * [r,r].i ) / Den; For j = to N do Begin if([r,j].r <> 0) or ([r,j].i <> 0 ) then [i,j].r = [i,j].r [r,j].r*xx + [r,j].i*; [,j].i = [,j].i [r,j].r * [r,j].i * XX; end. i Unif Two-Port Calculations, Daruvala, D. J., Electronic Design, Januar, 97, pp. -6 ii Consider the ndefinite Matrix, Daruvala, D. J., Electronic Design, Januar 8, 97, pp iii Coputer Methods for Circuit Analsis and Design, lach, J., Singhal, K., an Nostrand Reinhold, 98 iv Solid State Radio Engineering, Krauss, H.., Bostian, C.W., Raab, F. H., John Wile & Sons, 980 ( J.E. Crawford All Rights Reserved ) 6
Chapter 2. Small-Signal Model Parameter Extraction Method
Chapter Sall-Signal Model Paraeter Extraction Method In this chapter, we introduce a new paraeter extraction technique for sall-signal HBT odeling. Figure - shows the sall-signal equivalent circuit of
More informationEE 330 Lecture 30. Basic amplifier architectures
33 Lecture 3 asic aplifier architectures asic plifier Structures MOS and ipolar Transistors oth have 3 priary terinals MOS transistor has a fourth terinal that is generally considered a parasitic D terinal
More informationEE 330 Lecture 31. Basic amplifier architectures. Common Emitter/Source Common Collector/Drain Common Base/Gate
33 Lecture 3 asic aplifier architectures oon itter/source oon ollector/drain oon ase/gate eview fro arlier Lecture Two-port representation of aplifiers plifiers can be odeled as a two-port y 2 2 y y 22
More informationLinear Transformations
Linear Transforations Hopfield Network Questions Initial Condition Recurrent Layer p S x W S x S b n(t + ) a(t + ) S x S x D a(t) S x S S x S a(0) p a(t + ) satlins (Wa(t) + b) The network output is repeatedly
More informationEE5900 Spring Lecture 4 IC interconnect modeling methods Zhuo Feng
EE59 Spring Parallel LSI AD Algoriths Lecture I interconnect odeling ethods Zhuo Feng. Z. Feng MTU EE59 So far we ve considered only tie doain analyses We ll soon see that it is soeties preferable to odel
More information}, (n 0) be a finite irreducible, discrete time MC. Let S = {1, 2,, m} be its state space. Let P = [p ij. ] be the transition matrix of the MC.
Abstract Questions are posed regarding the influence that the colun sus of the transition probabilities of a stochastic atrix (with row sus all one) have on the stationary distribution, the ean first passage
More informationPage 1 Lab 1 Elementary Matrix and Linear Algebra Spring 2011
Page Lab Eleentary Matri and Linear Algebra Spring 0 Nae Due /03/0 Score /5 Probles through 4 are each worth 4 points.. Go to the Linear Algebra oolkit site ransforing a atri to reduced row echelon for
More informationPhysics 215 Winter The Density Matrix
Physics 215 Winter 2018 The Density Matrix The quantu space of states is a Hilbert space H. Any state vector ψ H is a pure state. Since any linear cobination of eleents of H are also an eleent of H, it
More informationBlock designs and statistics
Bloc designs and statistics Notes for Math 447 May 3, 2011 The ain paraeters of a bloc design are nuber of varieties v, bloc size, nuber of blocs b. A design is built on a set of v eleents. Each eleent
More informationChapter 6 1-D Continuous Groups
Chapter 6 1-D Continuous Groups Continuous groups consist of group eleents labelled by one or ore continuous variables, say a 1, a 2,, a r, where each variable has a well- defined range. This chapter explores:
More informationThe Distribution of the Covariance Matrix for a Subset of Elliptical Distributions with Extension to Two Kurtosis Parameters
journal of ultivariate analysis 58, 96106 (1996) article no. 0041 The Distribution of the Covariance Matrix for a Subset of Elliptical Distributions with Extension to Two Kurtosis Paraeters H. S. Steyn
More informationKernel Methods and Support Vector Machines
Intelligent Systes: Reasoning and Recognition Jaes L. Crowley ENSIAG 2 / osig 1 Second Seester 2012/2013 Lesson 20 2 ay 2013 Kernel ethods and Support Vector achines Contents Kernel Functions...2 Quadratic
More informationAbout the definition of parameters and regimes of active two-port networks with variable loads on the basis of projective geometry
About the definition of paraeters and regies of active two-port networks with variable loads on the basis of projective geoetry PENN ALEXANDR nstitute of Electronic Engineering and Nanotechnologies "D
More informationModel Fitting. CURM Background Material, Fall 2014 Dr. Doreen De Leon
Model Fitting CURM Background Material, Fall 014 Dr. Doreen De Leon 1 Introduction Given a set of data points, we often want to fit a selected odel or type to the data (e.g., we suspect an exponential
More informationFeature Extraction Techniques
Feature Extraction Techniques Unsupervised Learning II Feature Extraction Unsupervised ethods can also be used to find features which can be useful for categorization. There are unsupervised ethods that
More informationON THE TWO-LEVEL PRECONDITIONING IN LEAST SQUARES METHOD
PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY Physical and Matheatical Sciences 04,, p. 7 5 ON THE TWO-LEVEL PRECONDITIONING IN LEAST SQUARES METHOD M a t h e a t i c s Yu. A. HAKOPIAN, R. Z. HOVHANNISYAN
More informationUsing a De-Convolution Window for Operating Modal Analysis
Using a De-Convolution Window for Operating Modal Analysis Brian Schwarz Vibrant Technology, Inc. Scotts Valley, CA Mark Richardson Vibrant Technology, Inc. Scotts Valley, CA Abstract Operating Modal Analysis
More informationChapter 10: Sinusoidal Steady-State Analysis
Chapter 0: Sinusoidal Steady-State Analysis Sinusoidal Sources If a circuit is driven by a sinusoidal source, after 5 tie constants, the circuit reaches a steady-state (reeber the RC lab with t = τ). Consequently,
More informationPolynomial Division By Convolution
Applied Matheatics E-Notes, (0), 9 c ISSN 0-0 Available free at irror sites of http://wwwathnthuedutw/aen/ Polynoial Division By Convolution Feng Cheng Chang y Received 9 March 0 Abstract The division
More informationTopic 5a Introduction to Curve Fitting & Linear Regression
/7/08 Course Instructor Dr. Rayond C. Rup Oice: A 337 Phone: (95) 747 6958 E ail: rcrup@utep.edu opic 5a Introduction to Curve Fitting & Linear Regression EE 4386/530 Coputational ethods in EE Outline
More informationA Simplified Analytical Approach for Efficiency Evaluation of the Weaving Machines with Automatic Filling Repair
Proceedings of the 6th SEAS International Conference on Siulation, Modelling and Optiization, Lisbon, Portugal, Septeber -4, 006 0 A Siplified Analytical Approach for Efficiency Evaluation of the eaving
More informationDeflation of the I-O Series Some Technical Aspects. Giorgio Rampa University of Genoa April 2007
Deflation of the I-O Series 1959-2. Soe Technical Aspects Giorgio Rapa University of Genoa g.rapa@unige.it April 27 1. Introduction The nuber of sectors is 42 for the period 1965-2 and 38 for the initial
More informationLeast Squares Fitting of Data
Least Squares Fitting of Data David Eberly, Geoetric Tools, Redond WA 98052 https://www.geoetrictools.co/ This work is licensed under the Creative Coons Attribution 4.0 International License. To view a
More informationExperimental Design For Model Discrimination And Precise Parameter Estimation In WDS Analysis
City University of New York (CUNY) CUNY Acadeic Works International Conference on Hydroinforatics 8-1-2014 Experiental Design For Model Discriination And Precise Paraeter Estiation In WDS Analysis Giovanna
More informationDESIGN OF MECHANICAL SYSTEMS HAVING MAXIMALLY FLAT RESPONSE AT LOW FREQUENCIES
DESIGN OF MECHANICAL SYSTEMS HAVING MAXIMALLY FLAT RESPONSE AT LOW FREQUENCIES V.Raachran, Ravi P.Raachran C.S.Gargour Departent of Electrical Coputer Engineering, Concordia University, Montreal, QC, CANADA,
More informationProc. of the IEEE/OES Seventh Working Conference on Current Measurement Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES
Proc. of the IEEE/OES Seventh Working Conference on Current Measureent Technology UNCERTAINTIES IN SEASONDE CURRENT VELOCITIES Belinda Lipa Codar Ocean Sensors 15 La Sandra Way, Portola Valley, CA 98 blipa@pogo.co
More informationSimple procedures for finding mean first passage times in Markov chains
Res. Lett. Inf. Math. Sci., 2005, Vol. 8, pp 209-226 209 Availale online at http://iis.assey.ac.nz/research/letters/ Siple procedures for finding ean first passage ties in Markov chains JEFFREY J. HUNER
More information13.2 Fully Polynomial Randomized Approximation Scheme for Permanent of Random 0-1 Matrices
CS71 Randoness & Coputation Spring 018 Instructor: Alistair Sinclair Lecture 13: February 7 Disclaier: These notes have not been subjected to the usual scrutiny accorded to foral publications. They ay
More informationCOS 424: Interacting with Data. Written Exercises
COS 424: Interacting with Data Hoework #4 Spring 2007 Regression Due: Wednesday, April 18 Written Exercises See the course website for iportant inforation about collaboration and late policies, as well
More informationA Markov Framework for the Simple Genetic Algorithm
A arkov Fraework for the Siple Genetic Algorith Thoas E. Davis*, Jose C. Principe Electrical Engineering Departent University of Florida, Gainesville, FL 326 *WL/NGS Eglin AFB, FL32542 Abstract This paper
More information1 Analysis of heat transfer in a single-phase transformer
Assignent -7 Analysis of heat transr in a single-phase transforer The goal of the first assignent is to study the ipleentation of equivalent circuit ethod (ECM) and finite eleent ethod (FEM) for an electroagnetic
More informationThe Fundamental Basis Theorem of Geometry from an algebraic point of view
Journal of Physics: Conference Series PAPER OPEN ACCESS The Fundaental Basis Theore of Geoetry fro an algebraic point of view To cite this article: U Bekbaev 2017 J Phys: Conf Ser 819 012013 View the article
More informationOrder Recursion Introduction Order versus Time Updates Matrix Inversion by Partitioning Lemma Levinson Algorithm Interpretations Examples
Order Recursion Introduction Order versus Tie Updates Matrix Inversion by Partitioning Lea Levinson Algorith Interpretations Exaples Introduction Rc d There are any ways to solve the noral equations Solutions
More informationSupplementary to Learning Discriminative Bayesian Networks from High-dimensional Continuous Neuroimaging Data
Suppleentary to Learning Discriinative Bayesian Networks fro High-diensional Continuous Neuroiaging Data Luping Zhou, Lei Wang, Lingqiao Liu, Philip Ogunbona, and Dinggang Shen Proposition. Given a sparse
More informationThe Wilson Model of Cortical Neurons Richard B. Wells
The Wilson Model of Cortical Neurons Richard B. Wells I. Refineents on the odgkin-uxley Model The years since odgkin s and uxley s pioneering work have produced a nuber of derivative odgkin-uxley-like
More informationPhysics 139B Solutions to Homework Set 3 Fall 2009
Physics 139B Solutions to Hoework Set 3 Fall 009 1. Consider a particle of ass attached to a rigid assless rod of fixed length R whose other end is fixed at the origin. The rod is free to rotate about
More informationA note on the multiplication of sparse matrices
Cent. Eur. J. Cop. Sci. 41) 2014 1-11 DOI: 10.2478/s13537-014-0201-x Central European Journal of Coputer Science A note on the ultiplication of sparse atrices Research Article Keivan Borna 12, Sohrab Aboozarkhani
More informationChapter 10: Sinusoidal Steady-State Analysis
Chapter 0: Sinusoidal Steady-State Analysis Sinusoidal Sources If a circuit is driven by a sinusoidal source, after 5 tie constants, the circuit reaches a steady-state (reeber the RC lab with t τ). Consequently,
More informationJordan Journal of Physics
Volue 5, Nuber 3, 212. pp. 113-118 ARTILE Jordan Journal of Physics Networks of Identical apacitors with a Substitutional apacitor Departent of Physics, Al-Hussein Bin Talal University, Ma an, 2, 71111,
More informationInteractive Markov Models of Evolutionary Algorithms
Cleveland State University EngagedScholarship@CSU Electrical Engineering & Coputer Science Faculty Publications Electrical Engineering & Coputer Science Departent 2015 Interactive Markov Models of Evolutionary
More informationSolutions of some selected problems of Homework 4
Solutions of soe selected probles of Hoework 4 Sangchul Lee May 7, 2018 Proble 1 Let there be light A professor has two light bulbs in his garage. When both are burned out, they are replaced, and the next
More informationA Finite Element Propagation Model For Extracting Normal Incidence Impedance In Nonprogressive Acoustic Wave Fields
NASA Technical Meorandu 110160 A Finite Eleent Propagation Model For Extracting Noral Incidence Ipedance In Nonprogressive Acoustic Wave Fields Willie R. Watson Langley Research Center, Hapton, Virginia
More informationIntroduction to Robotics (CS223A) (Winter 2006/2007) Homework #5 solutions
Introduction to Robotics (CS3A) Handout (Winter 6/7) Hoework #5 solutions. (a) Derive a forula that transfors an inertia tensor given in soe frae {C} into a new frae {A}. The frae {A} can differ fro frae
More informationAN APPLICATION OF CUBIC B-SPLINE FINITE ELEMENT METHOD FOR THE BURGERS EQUATION
Aksan, E..: An Applıcatıon of Cubıc B-Splıne Fınıte Eleent Method for... THERMAL SCIECE: Year 8, Vol., Suppl., pp. S95-S S95 A APPLICATIO OF CBIC B-SPLIE FIITE ELEMET METHOD FOR THE BRGERS EQATIO by Eine
More informationA NEW ELECTROSTATIC FIELD GEOMETRY. Jerry E. Bayles
INTRODUCTION A NEW ELECTROSTATIC FIELD GEOMETRY by Jerry E Bayles The purpose of this paper is to present the electrostatic field in geoetrical ters siilar to that of the electrogravitational equation
More informationa a a a a a a m a b a b
Algebra / Trig Final Exa Study Guide (Fall Seester) Moncada/Dunphy Inforation About the Final Exa The final exa is cuulative, covering Appendix A (A.1-A.5) and Chapter 1. All probles will be ultiple choice
More informationEFFECTIVE MODAL MASS & MODAL PARTICIPATION FACTORS Revision I
EFFECTIVE MODA MASS & MODA PARTICIPATION FACTORS Revision I B To Irvine Eail: to@vibrationdata.co Deceber, 5 Introduction The effective odal ass provides a ethod for judging the significance of a vibration
More informationSupport Vector Machine Classification of Uncertain and Imbalanced data using Robust Optimization
Recent Researches in Coputer Science Support Vector Machine Classification of Uncertain and Ibalanced data using Robust Optiization RAGHAV PAT, THEODORE B. TRAFALIS, KASH BARKER School of Industrial Engineering
More informationExplicit solution of the polynomial least-squares approximation problem on Chebyshev extrema nodes
Explicit solution of the polynoial least-squares approxiation proble on Chebyshev extrea nodes Alfredo Eisinberg, Giuseppe Fedele Dipartiento di Elettronica Inforatica e Sisteistica, Università degli Studi
More information(t, m, s)-nets and Maximized Minimum Distance, Part II
(t,, s)-nets and Maxiized Miniu Distance, Part II Leonhard Grünschloß and Alexander Keller Abstract The quality paraeter t of (t,, s)-nets controls extensive stratification properties of the generated
More informationSupplementary Information for Design of Bending Multi-Layer Electroactive Polymer Actuators
Suppleentary Inforation for Design of Bending Multi-Layer Electroactive Polyer Actuators Bavani Balakrisnan, Alek Nacev, and Elisabeth Sela University of Maryland, College Park, Maryland 074 1 Analytical
More informationLecture 13 Eigenvalue Problems
Lecture 13 Eigenvalue Probles MIT 18.335J / 6.337J Introduction to Nuerical Methods Per-Olof Persson October 24, 2006 1 The Eigenvalue Decoposition Eigenvalue proble for atrix A: Ax = λx with eigenvalues
More informationSequence Analysis, WS 14/15, D. Huson & R. Neher (this part by D. Huson) February 5,
Sequence Analysis, WS 14/15, D. Huson & R. Neher (this part by D. Huson) February 5, 2015 31 11 Motif Finding Sources for this section: Rouchka, 1997, A Brief Overview of Gibbs Sapling. J. Buhler, M. Topa:
More informationVulnerability of MRD-Code-Based Universal Secure Error-Correcting Network Codes under Time-Varying Jamming Links
Vulnerability of MRD-Code-Based Universal Secure Error-Correcting Network Codes under Tie-Varying Jaing Links Jun Kurihara KDDI R&D Laboratories, Inc 2 5 Ohara, Fujiino, Saitaa, 356 8502 Japan Eail: kurihara@kddilabsjp
More informationLecture #8-3 Oscillations, Simple Harmonic Motion
Lecture #8-3 Oscillations Siple Haronic Motion So far we have considered two basic types of otion: translation and rotation. But these are not the only two types of otion we can observe in every day life.
More informationThe proofs of Theorem 1-3 are along the lines of Wied and Galeano (2013).
A Appendix: Proofs The proofs of Theore 1-3 are along the lines of Wied and Galeano (2013) Proof of Theore 1 Let D[d 1, d 2 ] be the space of càdlàg functions on the interval [d 1, d 2 ] equipped with
More informationINTELLECTUAL DATA ANALYSIS IN AIRCRAFT DESIGN
INTELLECTUAL DATA ANALYSIS IN AIRCRAFT DESIGN V.A. Koarov 1, S.A. Piyavskiy 2 1 Saara National Research University, Saara, Russia 2 Saara State Architectural University, Saara, Russia Abstract. This article
More informationReed-Muller Codes. m r inductive definition. Later, we shall explain how to construct Reed-Muller codes using the Kronecker product.
Coding Theory Massoud Malek Reed-Muller Codes An iportant class of linear block codes rich in algebraic and geoetric structure is the class of Reed-Muller codes, which includes the Extended Haing code.
More informationNon-Parametric Non-Line-of-Sight Identification 1
Non-Paraetric Non-Line-of-Sight Identification Sinan Gezici, Hisashi Kobayashi and H. Vincent Poor Departent of Electrical Engineering School of Engineering and Applied Science Princeton University, Princeton,
More informationMutual capacitor and its applications
Mutual capacitor and its applications Chun Li, Jason Li, Jieing Li CALSON Technologies, Toronto, Canada E-ail: calandli@yahoo.ca Published in The Journal of Engineering; Received on 27th October 2013;
More informationCh 12: Variations on Backpropagation
Ch 2: Variations on Backpropagation The basic backpropagation algorith is too slow for ost practical applications. It ay take days or weeks of coputer tie. We deonstrate why the backpropagation algorith
More informationLATTICE POINT SOLUTION OF THE GENERALIZED PROBLEM OF TERQUEi. AND AN EXTENSION OF FIBONACCI NUMBERS.
i LATTICE POINT SOLUTION OF THE GENERALIZED PROBLEM OF TERQUEi. AND AN EXTENSION OF FIBONACCI NUMBERS. C. A. CHURCH, Jr. and H. W. GOULD, W. Virginia University, Morgantown, W. V a. In this paper we give
More informationIntelligent Systems: Reasoning and Recognition. Perceptrons and Support Vector Machines
Intelligent Systes: Reasoning and Recognition Jaes L. Crowley osig 1 Winter Seester 2018 Lesson 6 27 February 2018 Outline Perceptrons and Support Vector achines Notation...2 Linear odels...3 Lines, Planes
More informationHESSIAN MATRICES OF PENALTY FUNCTIONS FOR SOLVING CONSTRAINED-OPTIMIZATION PROBLEMS
R 702 Philips Res. Repts 24, 322-330, 1969 HESSIAN MATRICES OF PENALTY FUNCTIONS FOR SOLVING CONSTRAINED-OPTIMIZATION PROBLEMS by F. A. LOOTSMA Abstract This paper deals with the Hessian atrices of penalty
More informationFour-vector, Dirac spinor representation and Lorentz Transformations
Available online at www.pelagiaresearchlibrary.co Advances in Applied Science Research, 2012, 3 (2):749-756 Four-vector, Dirac spinor representation and Lorentz Transforations S. B. Khasare 1, J. N. Rateke
More informationHomework 3 Solutions CSE 101 Summer 2017
Hoework 3 Solutions CSE 0 Suer 207. Scheduling algoriths The following n = 2 jobs with given processing ties have to be scheduled on = 3 parallel and identical processors with the objective of iniizing
More informationOn the summations involving Wigner rotation matrix elements
Journal of Matheatical Cheistry 24 (1998 123 132 123 On the suations involving Wigner rotation atrix eleents Shan-Tao Lai a, Pancracio Palting b, Ying-Nan Chiu b and Harris J. Silverstone c a Vitreous
More informationNUMERICAL MODELLING OF THE TYRE/ROAD CONTACT
NUMERICAL MODELLING OF THE TYRE/ROAD CONTACT PACS REFERENCE: 43.5.LJ Krister Larsson Departent of Applied Acoustics Chalers University of Technology SE-412 96 Sweden Tel: +46 ()31 772 22 Fax: +46 ()31
More informationOn the Communication Complexity of Lipschitzian Optimization for the Coordinated Model of Computation
journal of coplexity 6, 459473 (2000) doi:0.006jco.2000.0544, available online at http:www.idealibrary.co on On the Counication Coplexity of Lipschitzian Optiization for the Coordinated Model of Coputation
More informationKinetic Theory of Gases: Elementary Ideas
Kinetic Theory of Gases: Eleentary Ideas 17th February 2010 1 Kinetic Theory: A Discussion Based on a Siplified iew of the Motion of Gases 1.1 Pressure: Consul Engel and Reid Ch. 33.1) for a discussion
More informationRESTARTED FULL ORTHOGONALIZATION METHOD FOR SHIFTED LINEAR SYSTEMS
BIT Nuerical Matheatics 43: 459 466, 2003. 2003 Kluwer Acadeic Publishers. Printed in The Netherlands 459 RESTARTED FULL ORTHOGONALIZATION METHOD FOR SHIFTED LINEAR SYSTEMS V. SIMONCINI Dipartiento di
More informationWhat is the instantaneous acceleration (2nd derivative of time) of the field? Sol. The Euler-Lagrange equations quickly yield:
PHYSICS 75: The Standard Model Midter Exa Solution Key. [3 points] Short Answer (6 points each (a In words, explain how to deterine the nuber of ediator particles are generated by a particular local gauge
More informationMulti-Dimensional Hegselmann-Krause Dynamics
Multi-Diensional Hegselann-Krause Dynaics A. Nedić Industrial and Enterprise Systes Engineering Dept. University of Illinois Urbana, IL 680 angelia@illinois.edu B. Touri Coordinated Science Laboratory
More informationCHAPTER.4: Transistor at low frequencies
CHAPTER.4: Transistor at low frequencies Introduction Amplification in the AC domain BJT transistor modeling The re Transistor Model The Hybrid equivalent Model Introduction There are three models commonly
More informationA Simple Regression Problem
A Siple Regression Proble R. M. Castro March 23, 2 In this brief note a siple regression proble will be introduced, illustrating clearly the bias-variance tradeoff. Let Y i f(x i ) + W i, i,..., n, where
More informationAPPENDIX A THE ESSENTIALS OF MATRIX ANALYSIS
APPENDIX A THE ESSENTIALS OF MATRIX ANALYSIS A atrix is a rectangular collection of nubers. If there are η rows and coluns, we write the atrix as A n x, and the nubers of the atrix are α^, where i gives
More informationChaotic Coupled Map Lattices
Chaotic Coupled Map Lattices Author: Dustin Keys Advisors: Dr. Robert Indik, Dr. Kevin Lin 1 Introduction When a syste of chaotic aps is coupled in a way that allows the to share inforation about each
More informationSupporting Information for Supression of Auger Processes in Confined Structures
Supporting Inforation for Supression of Auger Processes in Confined Structures George E. Cragg and Alexander. Efros Naval Research aboratory, Washington, DC 20375, USA 1 Solution of the Coupled, Two-band
More informationKinetic Theory of Gases: Elementary Ideas
Kinetic Theory of Gases: Eleentary Ideas 9th February 011 1 Kinetic Theory: A Discussion Based on a Siplified iew of the Motion of Gases 1.1 Pressure: Consul Engel and Reid Ch. 33.1) for a discussion of
More informationGeneralized Sampling Theorem for Bandpass Signals
Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volue 26, Article ID 59587, Pages 6 DOI 55/ASP/26/59587 Generalized Sapling Theore for Bandpass Signals Ales Prokes Departent
More informationHee = ~ dxdy\jj+ (x) 'IJ+ (y) u (x- y) \jj (y) \jj (x), V, = ~ dx 'IJ+ (x) \jj (x) V (x), Hii = Z 2 ~ dx dy cp+ (x) cp+ (y) u (x- y) cp (y) cp (x),
SOVIET PHYSICS JETP VOLUME 14, NUMBER 4 APRIL, 1962 SHIFT OF ATOMIC ENERGY LEVELS IN A PLASMA L. E. PARGAMANIK Khar'kov State University Subitted to JETP editor February 16, 1961; resubitted June 19, 1961
More informationRandomized Recovery for Boolean Compressed Sensing
Randoized Recovery for Boolean Copressed Sensing Mitra Fatei and Martin Vetterli Laboratory of Audiovisual Counication École Polytechnique Fédéral de Lausanne (EPFL) Eail: {itra.fatei, artin.vetterli}@epfl.ch
More informationAn Accurate Discrete Fourier Transform for Image Processing
An Accurate Discrete Fourier Transfor for Iage Processing Norand Beaudoin' and Steven S. Beauchernint Abstract The classical ethod of nuerically coputing the Fourier transfor of digitizedfunctions in one
More informationAccuracy of the Scaling Law for Experimental Natural Frequencies of Rectangular Thin Plates
The 9th Conference of Mechanical Engineering Network of Thailand 9- October 005, Phuket, Thailand Accuracy of the caling Law for Experiental Natural Frequencies of Rectangular Thin Plates Anawat Na songkhla
More informationA MAXIMUM-LIKELIHOOD DECODER FOR JOINT PULSE POSITION AND AMPLITUDE MODULATIONS
The 18th Annual IEEE International Syposiu on Personal, Indoor and Mobile Radio Counications (PIMRC 07) A MAXIMUM-LIKELIHOOD DECODER FOR JOINT PULSE POSITION AND AMPLITUDE MODULATIONS Chadi Abou-Rjeily,
More informationLecture 36: MOSFET Common Drain (Source Follower) Amplifier.
Whites, EE 320 Lecture 36 Pae 1 of 10 Lecture 36: MOSFET Coon Drain (Source Follower) Aplifier. The third, and last, discrete-for MOSFET aplifier we ll consider in this course is the coon drain aplifier.
More informationA New Algorithm for Reactive Electric Power Measurement
A. Abiyev, GAU J. Soc. & Appl. Sci., 2(4), 7-25, 27 A ew Algorith for Reactive Electric Power Measureent Adalet Abiyev Girne Aerican University, Departernt of Electrical Electronics Engineering, Mersin,
More informationNumerical issues in the implementation of high order polynomial multidomain penalty spectral Galerkin methods for hyperbolic conservation laws
Nuerical issues in the ipleentation of high order polynoial ultidoain penalty spectral Galerkin ethods for hyperbolic conservation laws Sigal Gottlieb 1 and Jae-Hun Jung 1, 1 Departent of Matheatics, University
More information2.003 Engineering Dynamics Problem Set 2 Solutions
.003 Engineering Dynaics Proble Set Solutions This proble set is priarily eant to give the student practice in describing otion. This is the subject of kineatics. It is strongly recoended that you study
More informationUsing EM To Estimate A Probablity Density With A Mixture Of Gaussians
Using EM To Estiate A Probablity Density With A Mixture Of Gaussians Aaron A. D Souza adsouza@usc.edu Introduction The proble we are trying to address in this note is siple. Given a set of data points
More informationi ij j ( ) sin cos x y z x x x interchangeably.)
Tensor Operators Michael Fowler,2/3/12 Introduction: Cartesian Vectors and Tensors Physics is full of vectors: x, L, S and so on Classically, a (three-diensional) vector is defined by its properties under
More informationPolygonal Designs: Existence and Construction
Polygonal Designs: Existence and Construction John Hegean Departent of Matheatics, Stanford University, Stanford, CA 9405 Jeff Langford Departent of Matheatics, Drake University, Des Moines, IA 5011 G
More informationElectric Power System Transient Stability Analysis Methods
1 Electric Power Syste Transient Stability Analysis Methods João Pedro de Carvalho Mateus, IST Abstract In this paper are presented the state of the art of Electric Power Syste transient stability analysis
More informationA1. Find all ordered pairs (a, b) of positive integers for which 1 a + 1 b = 3
A. Find all ordered pairs a, b) of positive integers for which a + b = 3 08. Answer. The six ordered pairs are 009, 08), 08, 009), 009 337, 674) = 35043, 674), 009 346, 673) = 3584, 673), 674, 009 337)
More informationINNER CONSTRAINTS FOR A 3-D SURVEY NETWORK
eospatial Science INNER CONSRAINS FOR A 3-D SURVEY NEWORK hese notes follow closely the developent of inner constraint equations by Dr Willie an, Departent of Building, School of Design and Environent,
More informationALGEBRA REVIEW. MULTINOMIAL An algebraic expression consisting of more than one term.
Page 1 of 6 ALGEBRAIC EXPRESSION A cobination of ordinary nubers, letter sybols, variables, grouping sybols and operation sybols. Nubers reain fixed in value and are referred to as constants. Letter sybols
More informationarxiv: v2 [math.co] 8 Mar 2018
Restricted lonesu atrices arxiv:1711.10178v2 [ath.co] 8 Mar 2018 Beáta Bényi Faculty of Water Sciences, National University of Public Service, Budapest beata.benyi@gail.co March 9, 2018 Keywords: enueration,
More informationAVOIDING PITFALLS IN MEASUREMENT UNCERTAINTY ANALYSIS
VOIDING ITFLLS IN ESREENT NERTINTY NLYSIS Benny R. Sith Inchwor Solutions Santa Rosa, Suary: itfalls, both subtle and obvious, await the new or casual practitioner of easureent uncertainty analysis. This
More informationAlgebraic Montgomery-Yang problem: the log del Pezzo surface case
c 2014 The Matheatical Society of Japan J. Math. Soc. Japan Vol. 66, No. 4 (2014) pp. 1073 1089 doi: 10.2969/jsj/06641073 Algebraic Montgoery-Yang proble: the log del Pezzo surface case By DongSeon Hwang
More informationRECOVERY OF A DENSITY FROM THE EIGENVALUES OF A NONHOMOGENEOUS MEMBRANE
Proceedings of ICIPE rd International Conference on Inverse Probles in Engineering: Theory and Practice June -8, 999, Port Ludlow, Washington, USA : RECOVERY OF A DENSITY FROM THE EIGENVALUES OF A NONHOMOGENEOUS
More information