Pattern recognizers evolve across the sections into perceptrons, a layer of perceptrons, multiple-layered perceptrons, functional link nets, and radial basis function networks. Other networks covered in the process are learning vector quantization networks, self-organizing maps, and recursive neural networks. Backpropagation is derived in complete detail for one and two hidden layers for both unipolar and bipolar sigmoid activation functions.

The concept of pattern is universal in intelligence. This book recounts recent progress in pattern recognition using neural networks and functional networks, including wavelet transforms in the context of handwritten characters, gestures and signatures.

Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.

The concept of pattern is universal in intelligence. This book recounts recent progress in pattern recognition using neural networks and functional networks, including wavelet transforms in the context of handwritten characters, gestures and signatures.

This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.

The concept of pattern is universal in intelligence. This book recounts recent progress in pattern recognition using neural networks and functional networks, including wavelet transforms in the context of handwritten characters, gestures and signatures.

The revitalization of neural network research in the past few years has already had a great impact on research and development in pattern recognition and artificial intelligence. Although neural network functions are not limited to pattern recognition, there is no doubt that a renewed progress in pattern recognition and its applications now critically depends on neural networks. This volume specially brings together outstanding original research papers in the area and aims to help the continued progress in pattern recognition and its applications.