Principles of Artificial Neural Networks: Basic Designs to Deep Learning
Daniel Graupe · 2019
Introduction and role of artificial neural networks -- Fundamentals of biological neural networks -- Basic principles of ANNs and their structures -- The perceptron -- The madaline -- Back propagation -- Hopfield networks -- Counter propagation -- Adaptive resonance theory -- The cognitron and neocognition -- Statistical training -- Recurrent (time cycling) back propagation networks -- Deep learning neural networks : principles and scope -- Deep learning convolutional neural network -- LAMSTAR neural networks -- Performance of DLNN : comparative case studies