Applications of Neural Networks in Underwater Acoustic Signal Processing
It is well known that underwater acoustic channels are particularly complicated and difficult for typical signal processing procedures due to the time-varying, homogeneous volume, rough boundaries, and the abundance of interference noise sources in these channels. Most traditional methods of statistical signal processing employ simplified assumptions (linear, stationary, Gaussian) for the sake of mathematical tractability that inevitably lead to inadequate performance.
KeywordsNeural Network Radial Basis Function Network Systolic Array DOAs Estimation Hopfield Network
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