About the Book
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 101. Chapters: Artificial neural network, Self-organizing map, Sigmoid function, Cellular neural network, Neuroplasticity, Neural oscillation, Synaptic plasticity, Radial basis function network, Types of artificial neural networks, Perceptron, Cultured neuronal network, Neural coding, Recurrent neural network, Memory-prediction framework, Boltzmann machine, Biological neural network, Artificial neuron, Neural cryptography, Oja's rule, Feedforward neural network, Group method of data handling, Backpropagation, Adaptive resonance theory, Long short term memory, Neuroevolution of augmenting topologies, Multilayer perceptron, Neural backpropagation, Spiking neural network, Winner-take-all, Neural gas, Hopfield net, Feed-forward, Leabra, Growing self-organizing map, Confabulation, Cortical column, Evolutionary Acquisition of Neural Topologies, Cerebellar Model Articulation Controller, Activation function, Modular neural networks, Delta rule, Generalized Hebbian Algorithm, Pulse-coupled networks, Liquid state machine, HyperNEAT, Random neural network, Artificial Intelligence System, The Emotion Machine, Early stopping, Promoter based genetic algorithm, Semantic neural network, Synaptic weight, NETtalk, Universal approximation theorem, Learning Vector Quantization, Autoassociative memory, Softmax activation function, Optical neural network, Rprop, Infomax, Neural Information Processing Systems, Compositional pattern-producing network, ALOPEX, Auto-encoder, Bidirectional associative memory, Neocognitron, ADALINE, Cover's theorem, Hybrid neural network, Competitive learning, MoneyBee, Committee machine, Phase-of-firing code, Quantum neural network, U-Matrix, Neurally controlled animat, Echo state network, Cascade correlation algorithm, Reservoir computing, Canopy clustering algorithm, Madaline, Time delay neural network, Helmholtz machine...
