The Minimum Entropy Network
نویسنده
چکیده
Some researchers in pattem recognition theory claim thal for pattem recognition and classification dustering Iransfonnations are needed which reduce the intra-class entropy. This is implemented for Gaussian sources by a linear transfonnation using the eigenvectors with the smallest eigenvalues. This paper shows thal using ru basic building block a linear neuron with an Anti-Hebb rule and restricted weights, an asymmetric network which computes the eigenvectors in the rucending order of their co"esponding eigenvalues can be build. The conditions for their convergence are obtained and demonstrated by simulations.
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