Preface -- 1 The structure of neural networks -- 1.1 The structure of a single neuron -- 1.2 Transmission of neural signals -- 1.3 Neural circuits, CNS and ANN -- 2 Dynamic models of networks -- 2.1 Biological models -- 2.2 Signal functions -- 2.3 General models and network architectures -- 3 Simple networks -- 3.1 Outstars: pattern learning -- 3.2 Instars: pattern recognition -- 3.3 Lateral inhibition: noise-saturation dilemma -- 3.4 Recurrent ON-CTR OFF-SUR networks: signal enhancement and noise suppression -- 3.5 Determining synaptic weights -- Appendix. Grossberg's Learning Theorem -- 4 Content-addressable memory storage -- 4.1 Parallel memory storage by competitive networks -- 4.2 Convergence in networks with a nonsymmetric interconnection matrix -- 4.3 Implementation of CAM: Hopfield networks -- 4.4 Generic convergence in monotone networks -- 5 Signal transmission delays -- 5.1 Neural networks with delay and basic theory -- 5.2 Global stability analysis -- 5.3 Delay-induced instability -- 5.4 Hopf bifurcation of periodic solutions -- 5.5 A network of two neurons: McCulloch-Pitts nonlinearity -- 5.6 Delay-induced transient oscillations -- 5.7 Effect of delay on the basin of attraction -- 5.8 Synchronized activities -- 5.9 Desynchronization, phase-locked oscillation and connecting orbits -- Bibliography -- Index.