transformed to a pair of nonlinear ordinary differential equations. Subsequently they are reduced to a first order system and integrated using Newton Raphson and adaptive Runge-Kutta methods. The computer codes are developed for this numerical analysis in Matlab environment. Velocity
Premium Temperature Thermodynamics Heat
systems performing numerical computations and designed specifically for scientific applications. The best-known examples in the first category are Maple‚ Mathematica‚ Maxima‚ Axiom‚ and MuPad. The second category represents a larger market dominated by MATLAB. Scilab belongs to this second category. Scilab is an interpreted language with dynamically typed objects. Scilab can be used as a scripting language to test algorithms or to perform numerical computations. But it is also a programming language‚
Premium Control theory Signal processing
Conditional Expectation 8.1 Solutions 37 37 43 43 47 49 49 57 58 60 62 65 66 67 69 8 Appendix A R – A software tool for statistics Appendix B Introduction to MATLAB B.1 Working with vectors and matrices in the MATLAB environment B.2 MATLAB graphics B.3 Solving equations and computing integrals B.4 Statistics in MATLAB B.5 Using MATLAB to solve linear and quadratic programming problems Appendix C Introduction to AMPL C.1 Running optimization models in AMPL C.2 Mean-variance efficient portfolios in
Premium Random variable Probability theory Normal distribution
skills that I have gained from my undergraduate degree is the use of MatLab software for programming. I used MatLab for my undergraduate dissertation to construct a program that produced Cumulative Seismic Moment graphs. With the help of the program‚ I managed to conclude my research in finding the maximum magnitude of an earthquake in San Andreas Fault‚ California and also determined the waiting time. Similarly‚ I did a MatLab programming project that modelled an environmental process that was the
Premium Geology
4.2 Technology Used 4.2.1 Matlab Matlab is defined as a high level programming language which supports all kinds of operation like preprocessing of the data. Then based on the preprocessed information analysis of data takes place and the analyzed data can be represented either statistically
Premium Management Education Project management
Popular Analysis Software Includes Excel‚ Visual Basic‚ MATLAB and LabVIEW Examples MADE EASY Copyright Tektronix Inc. All rights reserved. Licensed software products are owned by Tektronix or its suppliers and are protected by United States copyright laws and international treaty provisions. LabVIEW and LabWindows™/CVI are trademarks of National Instruments Corporation. Mathcad is a registered trademark of MathSoft‚ Inc. MATLAB is a registered trademark of The MathWorks‚ Inc. Microsoft
Premium Microsoft Excel Graphical user interface
2000 Introduction Matlab and its applications in analysis of continuous-time signals and systems has been discussed in part 1 and 2 of this series of practical manuals. The purpose of part 3 is to discuss the way Matlab is used in analysis of discrete-time signals and systems. Each section provides a series of worked examples followed by a number of investigative problems. You are required to perform each of the worked examples in order to get familiar to the concept of Matlab environment and its
Premium Signal processing Digital signal processing
this project. His class lectures made my concepts clear in image processing and made me familiar with the various image processing techniques and the various operations that can be performed on images. This helped me implement my desired task using MATLAB and so I was able to complete my mini-project on “Image denoising and feature extraction using spatial filters” successfully. ABSTRACT: In image processing‚ the quality of any image gets badly corrupted by noise whether it be any kind of noise
Premium Image processing Normal distribution Noise
To accomplish this‚ we loaded the beam at 1/3 span with 1200 psi in five load increments in both the upright (9.46 inch side vertical) and flat (9.46 inch side horizontal) orientations. We then used three different leastsquare methods (utilizing Matlab and Kaleidagraph) on the data for each orientation to fit the data‚ resulting in the following: E: Upright Orientation Units Method One Method Two Method Three E: Flat Orientation 10 ksi 103 ksi 3 0.981 ± 0.100 1.253 ± 0.198 1.065 ± 0.247
Premium Beam Vermiform appendix Cantilever
”problem1.txt”(accessible on professor’s website)‚ there are 500 pairs of data‚ where the first column is X and the second column is Y. The regression model is Y = β0 + β1 X + a. Draw 20 pairs of data randomly from this population of size 500. Use MATLAB to run a regression model specified as above and keep record of the estimations of both β0 and β1 . Do this 200 times. Thus you will have 200 estimates of β0 and β1 . For each parameter‚ plot a histogram of the estimations. b. The above 500 data are
Premium Regression analysis Linear regression