Titlebook: Neural Networks and Statistical Learning; Ke-Lin Du,M. N. S. Swamy Textbook 2019Latest edition Springer-Verlag London Ltd., part of Spring

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Clustering I: Basic Clustering Models and Algorithms,on a number of competitive learning-based neural networks and clustering algorithms. We describe the SOM, learning vector quantization?(LVQ), and ART models, as well as .-means, subtractive, and fuzzy clustering algorithms.

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Compressed Sensing and Dictionary Learning, dictionary (a fixed collection). Sparse coding has become a popular paradigm in signal processing, statistics, and machine learning. This chapter introduces compressed sensing, sparse representation/sparse coding, tensor compressed sensing, and sparse PCA.

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Introduction,This chapter gives a brief introduction to the history of neural networks and machine learning. The concepts related to neurons, neural networks, and neural network processors are also described. This chapter concludes with an outline of the book.