Neuronal networks for pattern recognition
Manfred Rueff, Manfred Schmutz · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
To make efficient practical use of the attractive properties of standard neural network models it seems reasonable to com bine a recognition network with appropiate conventional preprocessing. In this contribution we describe the current research at IPA concerning such a hybrid approach to acoustic pattern recognition. The inputs of the recognition network are feature vectors consisting of local frequency characteristics extracted from the Wigner representation of the patterns. Simulations show that the system is capable to recognize individually learned objects in a scene.