Abstract
Signal processing algorithms optimized for Gaussian noise may degrade significantly in a non-Gaussian noise environment. Therefore it is important to characterize the noise accurately before including its structure in the formulation of algorithms. A generic distribution suitable for modeling non-Gaussian ambient noise in the kurtosis range 1.8 >
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