Increase the validity of positional-binary recognition of cyclic signals with application of radial-basis functional neural network

For increase of validity of a positional-binary method of cyclic signals recognition it is offered to use the radial-basis functional neural network allowing in the recognition process essentially to differentiate analyzed cyclic signals under time characteristics of their positional-pulse-width components locations.