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4 September 1998 Active biosonar systems based on multiscale signal representations and hierarchical neural networks
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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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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