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A new algorithmic framework for sparse underwater acoustic channel estimation under the presence of Symmetric α-Stable (SαS) noise is proposed. The framework is inspired by the low-complexity affine projection algorithm (APA) and employs a novel cost function that includes robust methods for impulsive noise suppression and a sparseness constraint. The constraint exploits the non-isotropic (Riemannian)...
We present a bio-inspired distributed algorithm which is a fusion of two distinct animal behaviours to solve three different underwater search missions. One of the two constituent control modules is called target-drive which models the hypothesized behaviour of a fish-larva searching for a coral reef using acoustic cues. Target-drive helps a single Autonomous Underwater Vehicle (AUV) to adjust its...
A novel adaptive algorithm is derived for sparse channel identification in the presence of Symmetric α-Stable (SαS) noise. The algorithm is based on the minimization of a new cost function, which is the sum of two terms. The first term is the distance between the previous and the current channel estimate. The distance metric is Riemannian, the same as in the improved-proportionate normalized least-mean-square...
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