Welcome to IOU Digital Library

An edited collection presenting state‑of‑the‑art research at the intersection of signal processing, machine learning, and computer science. The book emphasizes methods for knowledge extraction and heterogeneous information fusion — especially for challenging real‑world problems involving low signal‑to‑noise ratios, nonstationarity, and complex multichannel data. It includes contributions on topics such as adaptive filtering, independent component analysis (ICA), empirical mode decomposition, support vector machines, sensor fusion, multimodal imaging, environmental and biomedical signal analysis, and wireless‑network data fusion, offering both theoretical foundations and practical applications

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245: $a: Signal Processing Techniques for Knowledge Extraction and Information Fusion
245: $b:
082: $a:
100: $a: Danilo Mandic & Martin Golz & Anthony Kuh & Dragan Obradovic & Toshihisa Tanaka
650: $a: Signal Processing
250: $a:
440: $v:
250: $b: Springer Science+Business Media
250: $c: 2008
020: $a: 9780387743660
300: $a: 320