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a. Generate and plot a data set of N = 1,000 two-dimensional vectors that stem from three equiprobable classes modeled by normal distributions with mean vectors m₁ = = [1, 1]ª, m² = [7, 7]″, m3 = [15, 1] and 20 covariance matrices S₁ 12 0 0 i].S2 = 31.53 8 32 S3 = [2] 02 b. Repeat (a) when the a priori probabilities of the classes are given by the vector P = [0.6, 0.3, 0.117.

a. Generate and plot a data set of N = 1,000 two-dimensional vectors that stem from three equiprobable classes modeled by normal distributions with mean vectors m₁ = = [1, 1]ª, m² = [7, 7]″, m3 = [15, 1] and 20 covariance matrices S₁ 12 0 0 i].S2 = 31.53 8 32 S3 = [2] 02 b. Repeat (a) when the a priori probabilities of the classes are given by the vector P = [0.6, 0.3, 0.117.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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a. Generate and plot a data set of N = 1,000 two-dimensional vectors that stem from three equiprobable classes modeled by normal distributions [1, 1], т2 %3D [12 0 [7, 7]', m3 = [8 3] S3 [15, 1] and 2 0 with mean vectors m1 %3| covariance matrices S1 %3D %3D 3 2 02 b. Repeat (a) when the a priori probabilities of the classes are given by the vector P = [0.6, 0.3, 0.1].
Transcribed Image Text:a. Generate and plot a data set of N = 1,000 two-dimensional vectors that stem from three equiprobable classes modeled by normal distributions [1, 1], т2 %3D [12 0 [7, 7]', m3 = [8 3] S3 [15, 1] and 2 0 with mean vectors m1 %3| covariance matrices S1 %3D %3D 3 2 02 b. Repeat (a) when the a priori probabilities of the classes are given by the vector P = [0.6, 0.3, 0.1].
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