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Neural Networks for Pattern Recognition Christopher M. Bishop
Publisher: Oxford University Press, USA

Argues that the underlying principles and neural networks that are responsible for higher-order thinking are actually relatively simple, consisting of hierarchies of pattern recognition modules which make up the neocortex. Artificial neural network classification of NMR spectra of plant extracts. Secaucus, NJ, USA: Springer-Verlag New York, Inc. The reader is struck by how similar backpropagation is to automatic differentiation. Pattern Recognition and Machine Learning (Information Science and Statistics). The article “A Functional Approach to Neural Networks” in the Monad Reader shows how to use a neural network to classify handwritten digits in the MNIST database using backpropagation. Particularly good for performance measures and feature selection. Neural Networks for Pattern Recognition textbook. Webb (2002) Statistical Pattern Recognition. Special-Purpose Architectures, Software and Hardware Tools Supporting Information Technologies for Pattern Recognition, Image, Speech and Signal Processing, Analysis and Understanding. The modern usage of the term often refers to artificial neural. Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks. Statistical Pattern Recognition (Webb). Pattern Recognition and Neural Networks (Ripley). December 10, 2008 | Computer | Tagged book, Computer, neural network, pattern, recognition, text, textbook.