Optimization of parameters of functional transformations in a signal classification system

A concise mathematical statement of the signal classification problem is given. Within its framework, linear separability criteria are described for a set of points in a finite-dimensional space and then are generalized to an infinite-dimensional space. The problem of synthesis of both linear and nonlinear classification systems is also solved, for which an algorithm is formulated that chooses optimal structures of sequential and parallel functional transformations of uninformative coordinates in a feature vector.