Edwards-Penney, sections EPbvp7.6, 5.6. 6.1, 6.2, 7.1, 7.2, 7.3 The textbook topics, definitions and theorems

Edwards-Penney 5.5, 5.6 (15.5 K, txt, 27 Dec 2012)

Edwards-Penney 6.1, 6.2 (7.6 K, txt, 03 Apr 2013)

Edwards-Penney 7.1, 7.2, 7.3, 7.4 (25.6 K, txt, 09 Apr 2013)

Transform TerminologyConvolution theorem and x'' + 4x = cos(t), x(0)=x'(0)=0. Input Output Transfer FunctionCircuits EPbvp3.7: Electrical resonance. Derivation from mechanical problems 5.6. THEOREM: omega = 1/sqrt(LC). Impedance, reactance. Steady-state current amplitude Transfer function. Input and output equation.Chapter 5 references: Electrical circuits (124.8 K, pdf, 04 Mar 2012)Slides: Forced damped vibrations (280.7 K, pdf, 04 Mar 2012)Slides: Forced vibrations and resonance (240.3 K, pdf, 04 Mar 2012)Slides: Forced undamped vibrations (214.2 K, pdf, 03 Mar 2012)Slides: Resonance and undetermined coefficients (199.4 K, pdf, 03 Mar 2012)Slides: Unforced vibrations 2008 (667.9 K, pdf, 03 Mar 2012)Slides: Basic undetermined coefficients, draft 5 (156.3 K, pdf, 29 Mar 2013)Slides: Variation of parameters (164.5 K, pdf, 03 Mar 2012)Slides: Resonance and undetermined coefficients (199.4 K, pdf, 03 Mar 2012)SlidesWine Glass ExperimentDelayed .... due to missing audio in the classroom The lab table setup Speaker. Frequency generator with adjustment knob. Amplifier with volume knob. Wine glass. x(t)=deflection from equilibrium of the radial component of the glass rim, represented in polar coordinates, orthogonal to the speaker front. mx'' + cx' + kx = F_0 cos(omega t) The model of the wine glass m,c,k are properties of the glass sample itself F_0 = volume knob adjustment omega = frequency generator knob adjustmentTheory of Practical ResonanceThe equation is mx''+cx'+kx=F_0 cos(omega t) THEOREM. The limit of x_h(t) is zero at t=infinity THEOREM. x_p(t) = C(omega) cos(omega t - phi) C(omega) = F_0/Z, Z^2 = A^2+B^2, A and B are the undetermined coefficient answers for trial solution x(t) = A cos(omega t) + B sin(omega t). THEOREM. The output x(t) = x_h(t) + x_p(t) is graphically just x_p(t) = C(omega) cos(omega t - phi) for large t. Therefore, x_p(t) is the OBSERVABLE output. THEOREM. The amplitude C(omega) is maximized over all possible input frequencies omega>0 by the single choice omega = sqrt(k/m - c^2/(2m^2)). DEFINITION. Thepractical resonance frequencyis the number omega defined by the above square root expression. Projection: glass-breaking video. Wine glass experiment. Tacoma narrows.: Wine glass breakage (QuickTime MOV) (96.8 K, mov, 21 Mar 2013)Video: Wine glass experiment (12mb mpg, 2min) (12493.8 K, mpg, 01 Apr 2008)Video: Tacoma Narrows Bridge Nov 7, 1940 (18mb mpg, 4min) (18185.8 K, mpg, 01 Apr 2008)Video: Water glass shattering due to resonant sound waves. (96.8 K, mov, 21 Mar 2013)MOVIESample Exam 3 for S2013: sample exam 3, all problems. (182.4 K, pdf, 14 Nov 2010): All sample exams and solution keys. (19.6 K, html, 30 Apr 2013)HTML

Topics from linear systems:Brine tank models. Recirculating brine tanks. Pond pollution. Home heating. Earthquakes. Railway cars. All are 2x2 or 3x3 or nxn system applications that can be solved by Laplace methods.Systems of two differential equationsSolving a system from Chapter 1 methods The Laplace resolvent method for systems. Cramer's Rule, Matrix inversion methods. EXAMPLE: Solving a 2x2 dynamical system using Laplace's resolvent method. Study of u'=Au, u(0)=vector([1,2]), A=matrix([[2,1],[0,3]]). EXAMPLE: Problem 10.2-16, This problem is a 3x3 system for x(t), y(t), z(t) solved by Laplace theory methods. The resolvent formula (sI - A) L(u(t)) = u(0) with u(t) the fixed 3-vector with components x(t), y(t), z(t), amounts to a shortcut to obtain the equations for L(x(t)), L(y(t)), L(z(t)). After the shortcut is applied, in which Cramer's Rule is the method of choice, to find the formulas, there is no further shortcut: we have to find x(t), for example, by partial fractions and the backward table, followed by Lerch's theorem.

EXAMPLE. Recirculating brine tanks 20 x' = -6x + y, 20 y' = 6x - 3y x(t)=pounds of salt in tank 1 (100 gal) y(t)=pounds of salt in tank 2 (200 gal) x(0), y(0) = initial salt amounts in each tank t=minutes 20=inflow rate=outflow rate 0=inflow salt concentration EXAMPLE. Solve x'=-2y, y'=x/2. ANSWER: x(t)=A cos(t) + B sin(t), y(t) = (-A/2) cos(t) + (B/2) sin(t).Conversion Methods to Create a First Order SystemThe position-velocity substitution. How to convert second order systems. EXAMPLE. Transform to a first order system 2x'' = -6x + 2y, y'' = 2x - 2y + 40 sin(3t) ANSWER: u1=x,u2=x',u3=y,u4=y' ==> u1' = u2, u2' = -3u1 + u3, [a divison by 2 needed] u3' = u4, u4' = 2u1 - 2u3 + 40 sin(3t) How to convert nth order scalar differential equations. EXAMPLE. x''' + 2x'' + x = 0 Use u1=x(t), u2=x'(t), u3=x''(t) Non-homogeneous terms and the vector matrix system u' = Au + F(t) Non-linear systems and the vector-matrix system u' = F(t,u) Answer checks for u'=Au Example: The system u'=Au, A=matrix([[2,1],[0,3]]);Systems of two differential equationsThe Laplace resolvent method for systems. Solving the resolvent equation for L(x), L(y). Cramer's Rule Matrix inversion Elimination Example: Solving a 2x2 dynamical system Study of u'=Au, u(0)=vector([1,2]), A=matrix([[2,1],[0,3]]). Dynamical system scalar form is x' = 2x + y, y' = 3y, x(0)=1, y(0)=2. The equations for L(x), L(y) (s-2)L(x) + (-1)L(y)=1, (0)L(x) + (s-3)L(y)=2 REMARK: Laplace resolvent method shortcut. How to solve the [resolvent] equations for L(x), L(y). Cramer's Rule Matrix inversion Elimination Answers: L(x) = delta1/delta, L(y)=delta2/delta delta=(s-2)(s-3), delta1=s-1, delta2=2(s-2) L(x) = -1/(s-2)+2/(s-3), L(y)=2/(s-3) Backward table and Lerch's theorem Answers: x(t) = - e^{2t} + 2 e^{3t}, y(t) = 2 e^{3t}. Edwards-Penney Shortcut Method in Example 5, 7.1. Uses Chapter 1+5 methods. This is the Cayley-Hamilton-Ziebur method. See below. Solve w'+p(t)w=0 as w = constant / integrating factor. Then y' -2y=0 ==> y(t) = 2 exp(3t) Stuff y(t) into the first DE to get the linear DE x' - 2x = 2 exp(3t) Superposition: x(t)=x_h(t)+x_p(t), x_h(t)=c exp(2t), x_p(t) = d1 exp(t) = 2 exp(3t) by undetermined coeff. Then x(t)= - exp(2t) + 2 exp(3t).Cayley-Hamilton TheoremA matrix satisfies its own characteristic equation. ILLUSTRATION: det(A-r I)=0 for the previous example is (2-r)(3-r)=0 or r^2 -5r + 6=0. Then C-H says A^2 - 5A + 6I = 0.Cayley-Hamilton-Ziebur MethodZIEBUR'S LEMMA. The components of u in u'=Au are linear combinations of the atoms created by Euler's theorem applied to the roots of the characteristic equation det(A-rI)=0. THEOREM. Solve u'=Au without complex numbers or eigenanalysis. The solution of u'=Au is a linear combination of atoms times certain constant vectors [not arbitrary vectors]. u(t)=(atom_1)vec(c_1)+ ... + (atom_n)vec(c_n): Cayley-Hamilton-Ziebur method for solving vector-matrix system u'=Au. (152.9 K, pdf, 04 Mar 2012) PROBLEM: Solve by Cayley-Hamilton-Ziebur the 2x2 dynamical system x' = 2x + y, y' = 3y, x(0)=1, y(0)=2. The characteristic equation is (2-lambda)(3-lambda)=0 with roots lambda = 2,3 Euler's theorem implies the atoms are exp(2t), exp(3t). Ziebur's Theorem says that u(t) = exp(2t) vec(v_1) + exp(3t) vec(v_2) where vectors v_1, uv_2 are to be determined from the matrix A = matrix([[2,1],[0,3]]) and initial conditions x(0)=1, y(0)=2. ZIEBUR ALGORITHM. To solve for v_1, v_2 in the example, differentiate the equation u(t) = exp(2t) v_1 + exp(3t) v_2 and set t=0 in both relations. Then u'=Au implies u_0 = v_1 + v_2, Au_0 = 2 v_1 + 3 v_2. These equations can be solved by elimination. The answer: v_1 = (3 u_0 -Au_0), v_2 = (Au_0 - 2 u_0) = vector([-1,0]) = vector([2,2]) Vectors v_1, v_2 are recognized as eigenvectors of A for lambda=2 and lambda=3, respectively, after studying chapter 6. ZIEBUR SHORTCUT [Edwards-Penney textbook method, Example 5 in 7.1] Start with Ziebur's theorem, which implies that x(t) = k1 exp(2t) + k2 exp(3t). Use the first DE to solve for y(t): y(t) = x'(t) - 2x(t) = 2 k1 exp(2t) + 3 k2 exp(3t) - 2 k1 exp(2t) - 2 k2 exp(3t)) = k2 exp(3t) For example, x(0)=1, y(0)=2 implies k1 and k2 are defined by k1 + k2 = 1, k2 = 2, which implies k1 = -1, k2 = 2, agreeing with a previous solution formula.Slides

References for Eigenanalysis and Systems of Differential Equations.: Algebraic eigenanalysis (187.6 K, pdf, 04 Mar 2012)Manuscript: What's eigenanalysis 2008 (174.2 K, pdf, 04 Mar 2012)Manuscript: What's eigenanalysis, draft 1 (152.2 K, pdf, 01 Apr 2008)Manuscript: What's eigenanalysis, draft 2 (124.0 K, pdf, 14 Nov 2007)Manuscript: Cayley-Hamilton-Ziebur method for solving vector-matrix system u'=Au. (152.9 K, pdf, 04 Mar 2012)Slides: Laplace resolvent method (88.1 K, pdf, 04 Mar 2012)Slides: Laplace second order systems (288.1 K, pdf, 04 Mar 2012)Slides: Systems of DE examples and theory (785.8 K, pdf, 16 Nov 2008)Manuscript: Home heating, attic, main floor, basement (109.8 K, pdf, 04 Mar 2012)Slides: Lawrence Page's pagerank algorithm (0.7 K, txt, 06 Oct 2008)Text: History of telecom companies (1.9 K, txt, 04 Apr 2013)Text: Cable hoist example (73.2 K, pdf, 21 Aug 2008)Slides: Sliding plates example (105.8 K, pdf, 21 Aug 2008)Slides## Wednesday and Friday: Sections 6.1, 6.2, 7.1

Maple Example to find roots of the characteristic equationConsider the recirculating brine tank example: 20 x' = -6x + y, 20 y' = 6x - 3y Themaple codeto solve the char eq: A:=(1/20)*Matrix([[-6,1],[6,-3]]); linalg[charpoly](A,r); solve(%,r); # Answer: -9/40+(1/40)*sqrt(33), -9/40-(1/40)*sqrt(33)EIGENANALYSIS WARNINGReading Edwards-Penney Chapter 6 may deliver the wrong ideas about how to solve for eigenpairs. The examples emphasize a clever shortcut, which does not apply in general to solve for eigenpairs. HISTORY. Chapter 6 originally appeared in the 2280 book as a summary, which assumed a linear algebra course. The chapter was copied without changes into the Edwards-Penney Differential Equations and Linear Algebra textbook, which you currently own. The text contains only shortcuts. There is no discussion of a general method for finding eigenpairs. You will have to fill in the details by yourself. The online lecture notes and slides were created to fill in the gap.Lecture: Fourier's Model. Intro to Eigenanalysis, Ch6.Examples and motivation. Ellipse, rotations, eigenpairs. General solution of a differential equation u'=Au and eigenpairs. Fourier's model. History. J.B.Fourier's 1822 treatise on the theory of heat. The rod example. Physical Rod: a welding rod of unit length, insulated on the lateral surface and ice packed on the ends. Define f(x)=thermometer reading at loc=x along the rod at t=0. Define u(x,t)=thermometer reading at loc=x and time=t>0. Problem: Find u(x,t). Fourier's solution. Let's assume that f(x) = 17 sin (pi x) + 29 sin(5 pi x) = 17 v1 + 29 v2 Packages v1, v2 are vectors in a vector space V of functions on [0,1]. Fourier computes u(x,t) by re-scaling v1, v2 with numbers Lambda_1, Lambda_2 that depend on t. This idea is calledFourier's Model.u(x,t) = 17 ( exp(-pi^2 t) sin(pi x)) + 29 ( exp(-25 pi^2 t) sin (5 pi x)) = 17 (Lambda_1 v1) + 29 (Lambda_2 v2) Eigenanalysis of u'=Au is the identical idea. u(0) = c1 v1 + c2 v2 implies u(t) = c1 exp(lambda_1 t) v1 + c2 exp(lambda_2 t) v2 Fourier's re-scaling idea from 1822, applied to u'=Au, replaces v1 and v2 in the expression c1 v1 + c2 v2 by their re-scaled versions to obtain the answer c1 (Lambda1 v1) + c2 (Lambda2 v2) where Lambda1 = exp(lambda_1 t), Lambda2 = exp(lambda_2 t).Main Theorem on Fourier's ModelTHEOREM. Fourier's model A(c1 v1 + c2 v2) = c1 (lambda1 v1) + c2 (lambda2 v2) with v1, v2 a basis of R^2 holds [for all constants c1, c2] if and only if the vector-matrix system A(v1) = lambda1 v1, A(v2) = lambda2 v2, has a solution with vectors v1, v2 independent if and only if the diagonal matrix D=diag(lambda1,lambda2) and the augmented matrix P=aug(v1,v2) satisfy 1. det(P) not zero [then v1, v2 are independent] 2. AP=PD THEOREM. The eigenvalues of A are found from the determinant equation det(A -lambda I)=0, which is called the characteristic equation. THEOREM. The eigenvectors of A are found from the frame sequence which starts with B=A-lambda I [lambda a root of the characteristic equation], ending with last frame rref(B). The eigenvectors for lambda are the partial derivatives of the general solution obtained by the Last Frame Algorithm, with respect to the invented symbols t1, t2, t3, ...Algebraic Eigenanalysis Section 6.2.Calculation of eigenpairs to produce Fourier's model. Connection between Fourier's model and a diagonalizable matrix. How to find the variables lambda and v in Fourier's model using determinants and frame sequences. Solved in class: examples similar to the problems in 6.1 and 6.2. Web slides and problem notes exist for the 6.1 and 6.2 problems. Examples where A has an eigenvalue of multiplicity greater than one.

Monday: Eigenanalysis. First Order Systems. Sections 6.1, 6.2, 7.1, 7.3Projection: glass-breaking video. Wine glass experiment. Tacoma narrows.: Wine glass breakage (QuickTime MOV) (96.8 K, mov, 21 Mar 2013)Video: Wine glass experiment (12mb mpg, 2min) (12493.8 K, mpg, 01 Apr 2008)Video: Tacoma Narrows Bridge Nov 7, 1940 (18mb mpg, 4min) (18185.8 K, mpg, 01 Apr 2008)Video

Video: Resonance #17, Wine Glass and Tacoma Narrows (29min Annenburg CPB)Eigenanalysis ExamplesProblems 6.1, 6.2. See also FAQ online.Solving DE System u' = Au by EigenanalysisExample: Solving a 2x2 dynamical system Study of u'=Au, u(0)=vector([1,2]), A=matrix([[2,3],[0,4]]). Dynamical system scalar form is x' = 2x + 1y, y' = 3y, x(0)=1, y(0)=2. Find the eigenpairs (2, v1), (3,v2) where v1=vector([1,0]) and v2=vector([1,1]). THEOREM. The solution of u' = Au in the 2x2 case is u(t) = c1 exp(lambda1 t) v1 + c2 exp(lambda2 t) v2 APPLICATION: u(t) = c1 exp(2t) v1 + c2 exp(4t) v2 [ 1 ] [ 1 ] u(t) = c1 e^{2t} [ ] + c2 e^4t} [ ] [ 0 ] [ 1 ] which means x(t) = c1 exp(2t) + 3 c2 exp(4t), y(t) = 2 c2 exp(4t).Diagonalization TheoryIn the case of a 2x2 matrix A, FOURIER'S MODEL is A(c1 v1 + c2 v2) = c1(lambda1 v1) + c2(lambda2 v2) where v1,v2 are a basis for the plane equivalent to DIAGONALIZATION AP=PD, where D=diag(lamba1,lambda2), P=augment(v1,v2), where det(P) is not zero equivalent to EIGENPAIR EQUATIONS A(v1)=lambda1 v1, A(v2)=lambda2 v2, where vectors v1,v2 are independentExamplesGiven the eigenpairs of A, find A via AP=PD. Given P, D, then find A. Given A, then find P, D.Cayley-Hamilton topics, Section 6.3.Computing powers of matrices. Stochastic matrices. Example of 1984 telecom companies ATT, MCI, SPRINT with discrete dynamical system u(n+1)=A u(n). Matrix A is stochastic. EXAMPLE: [ 6 1 5 ] [ a(t) ] 10 A = [ 2 7 1 ] u(t) = [ m(t) ] [ 2 2 4 ] [ s(t) ] Meaning: 60% stay with ATT and 20% switch to MCI, 20% switch to SPRINT. 70% stay with MCI and 20% switch to SPRINT, 10% switch to ATT. 40% stay with SPRINT and 50% switch to ATT, 10% switch to MCI. Powers of A and the meaning of A^n x_0 for the telecom example.Google AlgorithmLawrence Page's pagerank algorithm, google web page rankings. Eigenanalysis and powers of A.: Lawrence Page's pagerank algorithm (0.7 K, txt, 06 Oct 2008)TextReferences for Eigenanalysis and Systems of Differential Equations.: Algebraic eigenanalysis (187.6 K, pdf, 04 Mar 2012)Slides: What's eigenanalysis 2008 (174.2 K, pdf, 04 Mar 2012)Slides: What's eigenanalysis, draft 1 (152.2 K, pdf, 01 Apr 2008)Slides: What's eigenanalysis, draft 2 (124.0 K, pdf, 14 Nov 2007)Slides: Cayley-Hamilton-Ziebur method for solving vector-matrix system u'=Au. (152.9 K, pdf, 04 Mar 2012)Slides: Laplace resolvent method (88.1 K, pdf, 04 Mar 2012)Slides: Laplace second order systems (288.1 K, pdf, 04 Mar 2012)Slides: Systems of DE examples and theory (785.8 K, pdf, 16 Nov 2008)Manuscript: Home heating, attic, main floor, basement (109.8 K, pdf, 04 Mar 2012)Slides: Lawrence Page's pagerank algorithm (0.7 K, txt, 06 Oct 2008)Text: History of telecom companies (1.9 K, txt, 04 Apr 2013)TextSystems of Differential Equations references: Cable hoist example (73.2 K, pdf, 21 Aug 2008)Slides: Sliding plates example (105.8 K, pdf, 21 Aug 2008)SlidesExtra Credit Maple Project: Tacoma narrows. Explore an alternative explanation for what caused the bridge to fail, based on the hanging cables.: Optional Maple Lab 9. Tacoma Narrows (33.7 K, pdf, 04 Dec 2012)MAPLELaplace theory references: Laplace and Newton calculus. Photos. (200.2 K, pdf, 04 Mar 2012)Slides: Intro to Laplace theory. Calculus assumed. (163.0 K, pdf, 19 Mar 2012)Slides: Laplace rules (160.3 K, pdf, 04 Mar 2012)Slides: Laplace table proofs (169.6 K, pdf, 04 Mar 2012)Slides: Laplace examples (149.1 K, pdf, 04 Mar 2012)Slides: Piecewise functions and Laplace theory (108.5 K, pdf, 03 Mar 2013)Slides: Maple Lab 7. Laplace applications (156.0 K, pdf, 04 Dec 2012)MAPLE: DE systems, examples, theory (785.8 K, pdf, 16 Nov 2008)Manuscript: Laplace resolvent method (88.1 K, pdf, 04 Mar 2012)Slides: Laplace second order systems (288.1 K, pdf, 04 Mar 2012)Slides: Home heating, attic, main floor, basement (109.8 K, pdf, 04 Mar 2012)Slides: Cable hoist example (73.2 K, pdf, 21 Aug 2008)Slides: Sliding plates example (105.8 K, pdf, 21 Aug 2008)Slides: Heaviside's method 2008 (186.8 K, pdf, 20 Oct 2009)Manuscript: Laplace theory 2008 (351.3 K, pdf, 09 Apr 2013)Manuscript: Ch10 Laplace solutions 10.1 to 10.4 (1068.7 K, pdf, 28 Nov 2010)Transparencies: Laplace theory problem notes S2013 (17.2 K, txt, 03 Dec 2012)Text: Final exam study guide (8.2 K, txt, 05 Dec 2012)Text