In a two-class, three-dimensional classification problem, the feature vectors in each class are normally distributed with...

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In a two-class, three-dimensional classification problem, the feature vectors in each class are normally distributed with covariance matrix 0.3 0.1 0.1 2 = 0.1 0.3 -0.1 0.1 -0.1 0.3 The respective mean vectors are [0,0,01" and [0.5,0.5, 0.51". Derive the corresponding linear discriminant functions and the equation describing the decision surface. In a two-class, three-dimensional classification problem, the feature vectors in each class are normally distributed with covariance matrix 0.3 0.1 0.1 2 = 0.1 0.3 -0.1 0.1 -0.1 0.3 The respective mean vectors are [0,0,01" and [0.5,0.5, 0.51". Derive the corresponding linear discriminant functions and the equation describing the decision surface.

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