Signal processing with fractional lower order moments: stable processes and their applications
作者： M. Shao , C.L. Nikias
DOI: 10.1109/5.231338
关键词:
摘要: Non-Gaussian statistical signal processing is important when signals and/or noise deviate from the ideal Gaussian model. Stable distributions are among the most important non-Gaussian models. They share defining characteristics with the Gaussian distribution, such as the stability property and central limit theorems, and in fact include the Gaussian distribution as a limiting case. To help engineers better understand the stable models and develop methodologies for their applications in signal processing. A tutorial review of the …
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