NASA - 10/28/2009 Matlab Lecture 10 > Lectures >...

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>> Lectures >> Matlab 10 Navigator 10.1 Probability Distributions This section discusses two basic probability density functions and probability distributions: uniform and normal , Gaussian mixture models, and GMM curve fitting. 10.1.1 Common PDFs Uniform probability density functions can be generated using function unifpdf . Given a range x, and a left and right endpoint, unifpdf distributes probabilities uniformly over x. unifpdf(x, a, b) : x = vector of range (including granularity), a = left endpoint, b = right endpoint x = -10:10; pdfUniform = unifpdf(x, -5, 5); plot(x, pdfUniform); Figure 10.1 Click to enlarge Normal probability density functions are generated using function normpdf . Characteristic of a normal distribution are mean and standard deviation. normpdf(x, mean, std) : x = vector of range (including granularity) 10/28/2009 Matlab Lecture 10…/page2.html 1/7
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x = -15:0.1:25; mu = 3; sigma = 4; pdfNormal = normpdf(x, mu, sigma); plot(x, pdfNormal); Figure 10.2 Click to enlarge 10.1.2 Randomly generated PDFs unifpdf and normpdf generate "perfect" densities; however, typical data observations only fit these distributions approximately. To simulate these situtations, Matlab offers functions for random number generation for both uniform and normal distributions. Function
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This note was uploaded on 02/17/2012 for the course EGN 3420 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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NASA - 10/28/2009 Matlab Lecture 10 > Lectures >...

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