A neural network approach to the detection problem using joint time-frequency distributions

A neural network algorithm for the detection and classification of transients in noise is described. The inputs are time-frequency representations modified so their entry location into the network of nodes is independent of the starting time of the transient. The algorithm is three-layered and feedforward, and is capable of training or testing in a single pass.<
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