3D Gradient Vector Flow Matlab Implementation Gradient Vector Flow (to the right) calculated on the volume to the left. Gradient Vector Flow (GVF) is a feature-preserving diffusion of gradient information. It was originally introduced by Xu and Prince to drive snakes‚ or active contours‚ towards edges of interest in image segmentation. But GVF is also used for detection of tubular structures and skeletonization. In this post I present a simple Matlab implementation of GVF for 3D images which
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..... 18 4.1 State space models 4.2 Relation with transfer function models 4.3 Properties of state space models 4.3.1 Time-domain solution 4.3.2 Controllable canonical form 4.3.3 Diagonal canonical form Review Problems 5. Analysis of PID Control Systems
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Numerical Simulation of Marangoni-Driven Boundary Layer Flow Over a Flat Plate with an Imposed Temperature Distribution Abstract: A numerical algorithm is presented for studying Marangoni convection flow over a flat plate with an imposed temperature distribution. Plate temperature varies with x in the following prescribed manner: where A and k are constants. By means of similarity transformation‚ the original nonlinear partial differential equations of flow are transformed to a pair of nonlinear
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Market Structure Simulation Quasar Computers When industries are selling similar products this makes up market structure. I will be discussing economic profit that Quasar computer is able to make. The market structure is made of the following pure monopoly‚ pure competition‚ monopolistic competition‚ and oligopoly. In the simulation I learn about pricing and non pricing strategies and understanding the diverse market structure. Quasar put out a new first all-optical notebook that is called
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ASSISTANT PROFESSOR CONTENTS: 1)Experiment 1: INTRODUCTION WITH MATLAB SOFTWARE 2) Experiment 2: GENERATION OF BASIC CONTINUES SIGNALS / BASIC DISCRETE SIGNALS 3) Experiment 3: IMPULSE RESPONSE OF AN LTI SYSTEM 4) Experiment 4: CONVOLUTION OF TWO SEQUENCE AND PROPERTIES OF CONVOLUTION 5) Experiment 5: CORRELATION- AUTOCORRELATION 6) Experiment 6: read and display digital image using MATLAB 7) Experiment 7: remove noise using spatial filters. 8) Experiment 8: edge detection
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Serial Communication between Arduino and MATLAB ByAman Mangal IIT Bombay June 6‚ 2012 Aman Mangal‚ IIT Bombay Serial Communication between Arduino and MATLAB 1/36 Prerequisite Serial data transfer in Arduino. Follow the link to learn more1 2 http://arduino.cc/en/Reference/serial http://www.ladyada.net/learn/arduino/lesson4.html http://users.ece.gatech.edu/bonnie/book/TUTORIAL/ tut_1.html http://www.mathworks.in/help/techdoc/matlab_ product_page.html MATLAB programming. To learn more‚ go to1
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Use Matlab to get an intuitive understanding of bonds valuation. 1. Basic knowledge: 1.1 The price equation and its six contributing factors As we know‚ there are six factors that determine the expected price of bonds: the par value(F)‚ the maturity(n) the yield to maturity(y)‚ the coupon interest(CF)‚ the interest payment frequency(m)‚ and the interest rates for each period(ri). We assume that the coupon interest is fixed‚ then the price of bonds(P)is the discounted cash flows
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SUMMARY UG NX7.5 Motion Simulation Training Package Unigraphics Solutions Company (UGS) is the world famous MCAD suppliers‚ mainly for the automotive and transportation‚ aerospace‚ general machinery and electronics industries. Through its Virtual Product Development (VPD) philosophy‚ UGS supply software product and services to company of multipolarity‚ collective‚ enterprise. Its main products are UG CAD. This UG motion simulation training package mainly introduces some basic knowledge
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CHAPTER 1 INTRODUCTION 1.1 Background of Study Coordinate systems form a common frame of reference for description of positions and on the other hand‚ coordinates are simply an ordered set of numbers that are used to describe the positions or features in coordinate system. Transformation parameters are required to move from one system to another. Also‚ new technologies like global positioning system have provide new methods of coordinates determination the map production‚ update
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MATLAB EXERCISES UEMH3163 / UECS2053 ARTIFICIAL INTELLIGENCE 1. Run the MATLAB code: a = 1:5; d = a+i*a; e = d’ f = d.’ g = mod(5‚4) 2. Given A = [1 2 4; 1 1 1; 2 3 1] and B = [2 2 2; 2 2 2; 2 2 2]. Run the MATLAB code: a=A>B b=A>1 3. Given A = magic(4). Run MATLAB code : DiagElement = diag(A) DiagMatrix = diag(diag(A)) SuperDiagElement = diag(A‚2) 4. Run the MATLAB code: name = upper(’matlab’) fun = strrep(’hahaha’‚’a’‚’i’) greet = ’Welcome’; where = ’to Joan’’s’; party = ’birthday
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