Active biosonar systems based on multiscale signal representations and hierarchical neural networks

Gordon S. Okimoto; Reid Shizumura; David W. Lemonds

doi:10.1117/12.324204

4 September 1998 Active biosonar systems based on multiscale signal representations and hierarchical neural networks

Gordon S. Okimoto, Reid Shizumura, David W. Lemonds

Proceedings Volume 3392, Detection and Remediation Technologies for Mines and Minelike Targets III; (1998) https://doi.org/10.1117/12.324204
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

Signal features based on multiresolution short-time Fourier transforms (STFT) and the Morlet wavelet transform (MWT) have been developed to classify echo returns from targets ensonified by simulated dolphin echolocation clicks. Spectrogram features are obtained at different scales of resolution using analysis windows of different sizes. A method of compressing the highly redundant time-scale representations provided by the MWT has been developed based on multiscale edge analysis (MSEA) of wavelet local maxima. Neural networks are used to evaluate the efficacy of the various feature sets for target recognition. Hierarchical neural networks are used to combine different feature sets for improved classification performance.

Citation Download Citation

Gordon S. Okimoto, Reid Shizumura, and David W. Lemonds "Active biosonar systems based on multiscale signal representations and hierarchical neural networks", Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); https://doi.org/10.1117/12.324204

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