AN INTRODUCTION TO NEURAL NETWORKS
Anderson, James A
AN INTRODUCTION TO NEURAL NETWORKS - New Delhi PHI Pub. 2009 - 650p.
Introduction. Acknowledgments. Properties of Single Neurons. Synaptic Integration and Neuron Models. Essential Vector Operations. Lateral Inhibition and Sensory Processing. Simple Matrix Operations. The Linear Associator: Background and Foundations. The Linear Associator: Simulations. Early Network Models: The Perceptron. Gradient Descent Algorithms. Representation of Information. Applications of Simple Associators: Concepts Formation and Object Motion. Energy and Neural Networks: Hopfield Networks and Boltzmann Machines. Nearest Neighbor Models. Adaptive maps. The BSB Model: A Simple Nonlinear Autoassociative Neural Network. Associative Computation. Teaching Arithmetic to a Neural Network
9788120313514
Properties of Single Neurons , Synaptic Integration and Neuron Models
006.32 AND-I
AN INTRODUCTION TO NEURAL NETWORKS - New Delhi PHI Pub. 2009 - 650p.
Introduction. Acknowledgments. Properties of Single Neurons. Synaptic Integration and Neuron Models. Essential Vector Operations. Lateral Inhibition and Sensory Processing. Simple Matrix Operations. The Linear Associator: Background and Foundations. The Linear Associator: Simulations. Early Network Models: The Perceptron. Gradient Descent Algorithms. Representation of Information. Applications of Simple Associators: Concepts Formation and Object Motion. Energy and Neural Networks: Hopfield Networks and Boltzmann Machines. Nearest Neighbor Models. Adaptive maps. The BSB Model: A Simple Nonlinear Autoassociative Neural Network. Associative Computation. Teaching Arithmetic to a Neural Network
9788120313514
Properties of Single Neurons , Synaptic Integration and Neuron Models
006.32 AND-I