25. The system defined in claim 15 , said processing unit further comprises a pseudorandom vector generating means for generating a pseudo-random vector in accordance with said probability distribution produced by said estimation means, said pseudorandom vector being output from said processing unit as a label of said third feature vector.
25. The system defined in claim 15 , said processing unit further comprises a pseudorandom vector generating means for generating a pseudo-random vector in accordance with said probability distribution produced by said estimation means, said pseudorandom vector being output from said processing unit as a label of said third feature vector. 26. The system defined in claim 25 , said processing unit further comprising unsupervised learning means for adjusting, in response to a sixth feature vector input to said processing unit, said at least one first expansion correlation matrix by using at least one outer product of a weighted sum of a vector with components all equal to 1 and a label of said sixth vector and a sixth orthogonal expansion of a subvector of said sixth feature vector, said sixth orthogonal expansion comprising components of said subvector of said sixth feature vector and a plurality of products of said components of said subvector of said sixth feature vector, wherein said label of said sixth feature vector is a pseudo-random vector generated by said pseudo-random vector generating means as a label of said sixth feature vector.