Linear Algebra. Definition The inverse of an n by n matrix A is an n by n matrix B where, Properties of Matrix Inverse. Minors and cofactors

Similar documents
September 27, Introduction to Ordinary Differential Equations. ME 501A Seminar in Engineering Analysis Page 1. Outline

MECH321 Dynamics of Engineering System Week 4 (Chapter 6)

ME 200 Thermodynamics I Spring 2014 Examination 3 Thu 4/10/14 6:30 7:30 PM WTHR 200, CL50 224, PHY 112 LAST NAME FIRST NAME

Economics 600: August, 2007 Dynamic Part: Problem Set 5. Problems on Differential Equations and Continuous Time Optimization

A Note on Estimability in Linear Models

Jones vector & matrices

Exercises for lectures 7 Steady state, tracking and disturbance rejection

Equil. Properties of Reacting Gas Mixtures. So far have looked at Statistical Mechanics results for a single (pure) perfect gas

EE750 Advanced Engineering Electromagnetics Lecture 17

CHAPTER 33: PARTICLE PHYSICS

The Fourier Transform

FREE VIBRATION ANALYSIS OF FUNCTIONALLY GRADED BEAMS

Small signal analysis

Physics 256: Lecture 2. Physics

Slobodan Lakić. Communicated by R. Van Keer

External Equivalent. EE 521 Analysis of Power Systems. Chen-Ching Liu, Boeing Distinguished Professor Washington State University

Phy213: General Physics III 4/10/2008 Chapter 22 Worksheet 1. d = 0.1 m

Applications of Lagrange Equations

Estimating the Variance in a Simulation Study of Balanced Two Stage Predictors of Realized Random Cluster Means Ed Stanek

What is LP? LP is an optimization technique that allocates limited resources among competing activities in the best possible manner.

Consider a system of 2 simultaneous first order linear equations

The Hyperelastic material is examined in this section.

Review - Probabilistic Classification

Group Codes Define Over Dihedral Groups of Small Order

4D SIMPLICIAL QUANTUM GRAVITY

Grand Canonical Ensemble

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t

Solutions for Homework #9

Basic Electrical Engineering for Welding [ ] --- Introduction ---

Formulas for the Determinant

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Comparisons of the Variance of Predictors with PPS sampling (update of c04ed26.doc) Ed Stanek

[ ] 1+ lim G( s) 1+ s + s G s s G s Kacc SYSTEM PERFORMANCE. Since. Lecture 10: Steady-state Errors. Steady-state Errors. Then

A NON-LINEAR MODEL FOR STUDYING THE MOTION OF A HUMAN BODY. Piteşti, , Romania 2 Department of Automotive, University of Piteşti

Quantum Mechanics for Scientists and Engineers

SAMPLE CSc 340 EXAM QUESTIONS WITH SOLUTIONS: part 2

Chapter 5: Root Locus

Chapter 13 Laplace Transform Analysis

Differentiation of Exponential Functions

Guo, James C.Y. (1998). "Overland Flow on a Pervious Surface," IWRA International J. of Water, Vol 23, No 2, June.

Quick Visit to Bernoulli Land

Ερωτήσεις και ασκησεις Κεφ. 10 (για μόρια) ΠΑΡΑΔΟΣΗ 29/11/2016. (d)

MAE140 - Linear Circuits - Fall 10 Midterm, October 28

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

System in Weibull Distribution

CHAPTER 10 ROTATIONAL MOTION

Solutions to Supplementary Problems

Rayleigh-Schrödinger Perturbation Theory

Math 217 Fall 2013 Homework 2 Solutions

te Finance (4th Edition), July 2017.

Chapter 7: Conservation of Energy

Chapter 11. Supplemental Text Material. The method of steepest ascent can be derived as follows. Suppose that we have fit a firstorder

APPENDIX A Some Linear Algebra

LINEAR SYSTEMS THEORY

International Journal of Mathematical Archive-9(3), 2018, Available online through ISSN

XII.3 The EM (Expectation-Maximization) Algorithm

perm4 A cnt 0 for for if A i 1 A i cnt cnt 1 cnt i j. j k. k l. i k. j l. i l

(1) Then we could wave our hands over this and it would become:

Lecture 7 - SISO Loop Analysis

Optimal Ordering Policy in a Two-Level Supply Chain with Budget Constraint

Optimal Marketing Strategies for a Customer Data Intermediary. Technical Appendix

UNIT 8 TWO-WAY ANOVA WITH m OBSERVATIONS PER CELL

The Matrix Exponential

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J.

Lecture 21: Numerical methods for pricing American type derivatives

Logarithms. Secondary Mathematics 3 Page 164 Jordan School District

Having a glimpse of some of the possibilities for solutions of linear systems, we move to methods of finding these solutions. The basic idea we shall

8-node quadrilateral element. Numerical integration

Fall 2012 Analysis of Experimental Measurements B. Eisenstein/rev. S. Errede. ) with a symmetric Pcovariance matrix of the y( x ) measurements V

LEBANESE UNIVERSITY FACULTY OF ENGINEERING

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns

2.3 Nilpotent endomorphisms

A Probabilistic Characterization of Simulation Model Uncertainties

Applied Stochastic Processes

Period vs. Length of a Pendulum

The Relationship Between Loss, Conductivity, and Dielectric Constant

Applied Mathematics Letters

Lucas Test is based on Euler s theorem which states that if n is any integer and a is coprime to n, then a φ(n) 1modn.

ECE602 Exam 1 April 5, You must show ALL of your work for full credit.

Field and Wave Electromagnetic. Chapter.4

1) They represent a continuum of energies (there is no energy quantization). where all values of p are allowed so there is a continuum of energies.

Lecture 3: Phasor notation, Transfer Functions. Context

1 cos. where v v sin. Range Equations: for an object that lands at the same height at which it starts. v sin 2 i. t g. and. sin g

Convexity preserving interpolation by splines of arbitrary degree

The Matrix Exponential

3.4 Properties of the Stress Tensor

Instructors Solution for Assignment 3 Chapter 3: Time Domain Analysis of LTIC Systems

CHAPTER 7d. DIFFERENTIATION AND INTEGRATION

A New Refinement of Jacobi Method for Solution of Linear System Equations AX=b

for Linear Systems With Strictly Diagonally Dominant Matrix

MEM 255 Introduction to Control Systems Review: Basics of Linear Algebra

INTRODUCTION TO AUTOMATIC CONTROLS INDEX LAPLACE TRANSFORMS

Norms, Condition Numbers, Eigenvalues and Eigenvectors

Variable Structure Control ~ Basics

Analyzing Frequencies

Econ107 Applied Econometrics Topic 10: Dummy Dependent Variable (Studenmund, Chapter 13)

Thomas Whitham Sixth Form

Our focus will be on linear systems. A system is linear if it obeys the principle of superposition and homogenity, i.e.

SUPPLEMENTARY INFORMATION

Transcription:

Dfnton Th nvr of an n by n atrx A an n by n atrx B whr, Not: nar Algbra Matrx Invron atrc on t hav an nvr. If a atrx ha an nvr, thn t call. Proprt of Matrx Invr. If A an nvrtbl atrx thn t nvr unqu.. (A - ) -. (A k ) -. (ca) -. ( A T ) - 6. If A an nvrtbl atrx, thn th yt of quaton Ax b ha a unqu oluton gvn by www.ngr.uak.ca/cla/ge//not9s/cturs.ppt www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Th nvr of a x atrx A x atrx a A c b A x atrx A f an only f a-bc. Th quantty (a-bc) ha o othr uful proprt a wll an o fn to b th of th atrx A. Mnor an cofactor If A a quar atrx, thn th M j of th lnt a j of A th trnant of th atrx obtan by ltng th -th row an th j-th colun fro A. Th j (-) j M j. www.ngr.uak.ca/cla/ge//not9s/cturs.ppt www.ngr.uak.ca/cla/ge//not9s/cturs.ppt

Dfnton of a Dtrnant If A a quar atrx of orr or gratr, thn th trnant of A th u of th ntr n th frt row* of A ultpl by thr cofactor. That, * any can b u a th pvot for th cofactor o not hav to b frt row Dtrnant of -by- Matrx A j a a A c b j j a a ( ) M t( A) A a b ( c) ( ) M www.ngr.uak.ca/cla/ge//not9s/cturs.ppt www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Dtrnant of a x atrx Dtrnant of -by- Matrx If A a x atrx Thn w fn a a a t(a) a a a a a a a A a a a a a a a a a a a a a -a a a a a a a a a a A t( A ) A a h a g f b c f h b g pvot row f c g h www.rp.u/~kblp/iea/lctur.9.matrx.ppt www.ngr.uak.ca/cla/ge//not9s/cturs.ppt

Dtrnant of -by- Matrx Dtrnant of a x atrx A t( A ) A a h a g f b c f h b h pvot colun c b g c f Exapl - t(a) - - - www.ngr.uak.ca/cla/ge//not9s/cturs.ppt www.rp.u/~kblp/iea/lctur.9.matrx.ppt Exapl: valuat t(a) for: A - - - t(a)() - -() - - - - - (-) - ()()-()(6)-(-)()98 www.rp.u/~kblp/iea/lctur.9.matrx.ppt In-la Exrc # Fn t(a) ung a) cofactor xpanon along th frt row. b) cofactor xpanon along th frt colun. c) cofactor xpanon along th con colun. www.rp.u/~kblp/iea/lctur.9.matrx.ppt

Proprt of Dtrnant. Th valu of a trnant f t row ar wrttn a colun n th a orr. 6 7 6 7. If any two row (or two colun) of a trnant ar ntrchang, th valu of th trnant 6 6 7 7 www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Proprt of Dtrnant. A coon factor of all lnt of any row (or colun) th trnant. 8 www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Proprt of Dtrnant. If th corrponng lnt of two row (or colun) of a trnant ar, th valu of th trnant. 6 7 8 Matrx Invron Ajont Mtho How to calculat th atrx nvr? Manng: Row ( Row ) on Row ( Row ). Thrfor, th lnar yt wth thr unknown o not hav a unqu oluton. www.ngr.uak.ca/cla/ge//not9s/cturs.ppt www.ngr.uak.ca/cla/ge//not9s/cturs.ppt

Mnor an ofactor of a Matrx Entry Mnor an ofactor of a Matrx Entry For x atrx a a a A a a a a a a For x atrx a a a A a a a a a a M (-) M M (-) M for t row, t colun for t row, t colun for n row, r colun for n row, r colun www.rp.u/~kblp/iea/lctur.9.matrx.ppt www.rp.u/~kblp/iea/lctur.9.matrx.ppt Ajont Matrx - ofactor Ajont Matrx Mnor an ofactor Th ajont atrx of [A], aj[a] obtan by takng th tranpo of th cofactor atrx of [A]. A aj ( A) A [ ] Matrx Invron onr th followng t of ultanou lnar quaton. Th coffcnt can b arrang n a atrx for a hown. www.ngr.uak.ca/cla/ge//not9s/cturs.ppt www.ngr.uak.ca/cla/ge//not9s/cturs.ppt

Matrx Invron 8 7 8 7 8 7 www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Matrx Invron Th rultng atrx of nor : 8 7 www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Matrx Invron ofactor: ofactor ar th gn nor. Th cofactor of lnt a j of atrx [A] : Thrfor Th rultng cofactor atrx of : www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Matrx Invron Ajont atrx: Th ajont atrx of [A], aj[a] obtan by takng th tranpo of th cofactor atrx of [A]. www.ngr.uak.ca/cla/ge//not9s/cturs.ppt

Matrx Invron www.ngr.uak.ca/cla/ge//not9s/cturs.ppt In-la Exrc # U th ajont tho to fn th nvr of th A atrx: 6 z y x ME 7 - Tranfr Functon Exapl (t) - R Fn th tranfr functon for th lctrcal yt blow t c ( ) R - - (t) t c Soluton tchnqu to tak th aplac Tranfor of th quaton, t ntal conton to zro, an olv th SE ME 7 - Tranfr Functon Exapl [ ] ) ( E I E R Sultanou lnar quaton wth ybolc coffcnt, Wll n to fn th trnant of th x atrx, u a procur a for nurcal coffcnt.

ME 7 - Tranfr Functon Exapl R In-la Exrc # U th ajont tho to fn th nvr of th followng atrx: Δ B K K τ ω ω θ ( )( ) ( ) ( ) K B K B M Matrx Invron Ung G- Elnaton If Gau oran lnaton appl on a quar atrx, t can b u to calculat th atrx nvr. Th can b on by augntng th quar atrx wth th ntty atrx of th a non, an through th followng atrx opraton: www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Exapl A If th orgnal quar atrx, A, gvn by th followng xpron: Thn, aftr augntng by I, th followng obtan: www.ngr.uak.ca/cla/ge//not9s/cturs.ppt

Exapl By prforng lntary row opraton on th [AI] atrx untl A rach ruc row chlon for, th followng th fnal rult: [ I A ] Th atrx augntaton can now b unon, whch gv th followng: I Atonal Rourc http://nurcaltho.ng.uf.u/topc/prr_l.htl A Txtbook haptr on Syt of Equaton www.ngr.uak.ca/cla/ge//not9s/cturs.ppt Duplcat olun Mtho for x atrx Fro th prvou l: a a a t(a) a a a a a a a a a a a -a a a a a a a a a a t(a) a a a a a a a a a -a a a -a a a -a a a Duplcat olun Mtho for x Exapl : - t(a) - a a a a a a a a a Alo work wth x, x, tc. www.rp.u/~kblp/iea/lctur.9.matrx.ppt www.rp.u/~kblp/iea/lctur.9.matrx.ppt