This book comprehensively and deeply introduces the artificial neural network theory and its application. The book consists of three sections: the foundation of neural network, artificial neural network theory, the design and practical application of neural network. First section mainly includes the theoretical basis of biological neural network, the review of artificial neural network and the mathematical foundation of artificial neural network. Second section includes some artificial neural network theory and algorithm, such as Perceptron, BP neural network, RBF neural network, Adaline neural network, Hopfield neural network, deep convolutional learning neural network, generative adversarial network, AdaBoost neural network, Elman neural network and SOFM neural network. Third section is the design and practical application of artificial neural network including the artificial neural network modeling based on Simulink, and artificial neural network design based on GUI using Matlab and Python.
This book can be used as a textbook for undergraduate and graduate students who are engaged in the theory, design and application of artificial neural network. It can also be used as a self-study and reference book for professional engineers.