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The Handbook of Neural Network Signal Processing provides a thorough, modern, account of the subject from a practical, engineering perspective. Chapters contributed by some of the world's top researchers and engineers cover basic principles, modeling, algorithms, architectures, and implementation procedures. Focusing on neural network paradigms that have been successfully applied to solve real-world problems and complete with well-designed simulation examples, this handbook describes a broad range of neural network solutions for statistical signal processing and for applications in speech, video, and biomedical signal processing.
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