PPT-Iterative Methods for Linear Systems

Goal is to solve the system Can use direct or iterative methods Direct Methods LU Decomposition QR Factorization Iterative Methods what we will use Jacobi GaussSeidel Successive Over RelaxationSOR. N is the process noise or disturbance at time are IID with 0 is independent of with 0 Linear Quadratic Stochastic Control 52 brPage 3br Control policies statefeedback control 0 N called the control policy at time roughly speaking we choo e Ax where is vector is a linear function of ie By where is then is a linear function of and By BA so matrix multiplication corresponds to composition of linear functions ie linear functions of linear functions of some variables Linear Equations Lecture 5: Software Development Models. Recap. Software development process model. . Waterfall model. . Advantages. . Disadvantages. . Usage. . Prototype model . . Advantages. . Disadvantages. N. icole Zelinsky - . University of California, . Merced . - nzelinsky@ucmerced.edu. Introduction and Motivation. Exploratory Factor Analysis. Analytic . tool which helps researchers develop scales, generate theory, and inform structure for a confirmatory factor . research progress. Last week : finalize dvc3D 1.0. Getting iterative method in dvc3D (in progress). Working on Candidacy plan. Past week. dvc3D 1.0 : . Getting it run inside Blender: can create joints, model object(done). A . Systems Engineering . Perspective. John M. Allen. 1. Presentation Overview. What is Agile?. Agile Methods. Systems Engineering and Agile. Why is Agile in a DoD Project a challenge?. The Earned Value Management (EVM) challenge. Computations. K-means. Performance of K-Means. Smith Waterman is a non iterative case and of course runs fine. Matrix Multiplication . 64 cores. Square blocks Twister. Row/Col . decomp. Twister. Algebra 2. Chapter 3. This Slideshow was developed to accompany the textbook. Larson Algebra 2. By Larson. , R., Boswell, L., . Kanold. , T. D., & Stiff, L. . 2011 . Holt . McDougal. Some examples and diagrams are taken from the textbook.. N. icole Zelinsky - . University of California, . Merced . - nzelinsky@ucmerced.edu. Introduction and Motivation. Exploratory Factor Analysis. Analytic . tool which helps researchers develop scales, generate theory, and inform structure for a confirmatory factor . Define . Iterative Patterns. …. Iterative Patterns follow a specific . RULE. .. Examples of Iterative Patterns:. 2, 4, 6, 8, 10, …. 2, 4, 8, 16, 32, …. 96, 92, 88, 84, 80, …. 625, 125, 25, 5, …. Iterative Local Searches. Martin . Burtscher. 1. and Hassan Rabeti. 2. 1. Department of Computer Science, Texas State University-San Marcos. 2. Department of Mathematics, Texas State University-San Marcos. Iterative Local Searches. Martin . Burtscher. 1. and Hassan Rabeti. 2. 1. Department of Computer Science, Texas State University-San Marcos. 2. Department of Mathematics, Texas State University-San Marcos. I ntegral Equations iterations are called as Half-Sweep Gauss-Seidel (HSGS) (QSGS) methods The outline of this paper is organized in following way. In Section 2, the formulation of the full-, half- a Linear Systems – Iterative methods Jacobi Method Gauss-Siedel Method 1 Iterative Methods Iterative methods can be expressed in the general form: x(k) =F(x(k-1)) where s s.t. F(s)=s is called a Fixed Point Hopefully: x(k)  s (solution of my