Performance Analysis of Blind Signal Separation Algorithms
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With rapid development in Communication technology, Network technology and Computer technology we have advanced in to a digital and information era, with digital signal processing as one of the key links. Blind Signal Separation being an emerging technology is very attractive option for use in many fields such as voice processing, sonar and seismic signal processing, biomedical engineering, mobile communications and remote sensing image processing applications. In real-world applications most measured signals are contaminated by additive noise influencing reduction in signal separation algorit...
With rapid development in Communication technology, Network technology and Computer technology we have advanced in to a digital and information era, with digital signal processing as one of the key links. Blind Signal Separation being an emerging technology is very attractive option for use in many fields such as voice processing, sonar and seismic signal processing, biomedical engineering, mobile communications and remote sensing image processing applications. In real-world applications most measured signals are contaminated by additive noise influencing reduction in signal separation algorithm performance. In this book, the performance metrics such as signal mean square error , signal to noise ratio of BSS and wavelet based denoising algorithms were studied and analysed. Further, these performances were studied under different noise conditions and models. Modified existing denoising and BSS algorithms to enhance their performance under noisy conditions.
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