Adaptive filtering neural network classifier

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395 22, 395 23, G06F 1518

Patent

active

057613834

ABSTRACT:
An adaptive filtering neural network classifier for classifying input signals, includes a neural network and one or more adaptive filters for receiving input analog signals to be classified and generates inputs for the classifier. Each adaptive filter is characterized as having a predetermined number of operating parameters. An analog to digital converter converts each input signal into a digital signal before input to the neural network. The neural network processes each digital signal to generate therefrom a plurality of weighted output signals in accordance with the type of network implemented. One of the weighted output signals represents a class for the input signal, and an error signal representing a difference between the weighted output signals and a predetermined desired output is also generated by the network. A control device responsive to the error signal generates a further set of operating filter parameters for input to each of the adaptive filters to change the operating response thereof and minimize the error signal.

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