Signal Processing Aspects of Signal

Acoustic signal extraction and identiication in the underwater environment is best achieved by adaptive methods as the signals encountered are generally non-stationary and corrupted by unpredictable noise sources, such as man-made noise, biological and seismic noises. While classical methods often fail in such an environment, the recent use of mul-tiresolution methods like the adaptive wavelet transform and its dual, the cosine packet transform, provides a promising alternative. This paper introduces three applications where wavelet and cosine transforms are used for denoising and signal identiication. Signal decomposition on these two sets of functions provide diierent representations, which are each speciic to a certain noise type. The third application achieves background pink noise ltering along with a high signal compression rate, which can be used to optimize signal identiication.