Neural Networks
Neural network is the abstraction and modeling of human brain or biological neural network, which studies the essence and ability of non procedural, adaptive and brain style information processing. It is an important part of intelligent science and computational intelligence. Based on the research results of brain science and cognitive neuroscience, it expands the methods of intelligent information processing and provides an effective way to solve complex problems and intelligent control.
This course systematically discusses the basic principles, methods, techniques and applications of neural networks. The main contents include the basic principle of neural information processing, perceptron, back propagation neural network, self-organizing network, recursive network, radial basis function network, kernel function method, neural network integration, fuzzy neural network, probabilistic neural network, pulse coupled neural network, neural field theory, neuron cluster, neural computer.
References
1. 史忠植. 神经网络. 北京：高等教育出版社， 2009
2. Zhongzhi Shi. Intelligence Science---Leading the Age of Intelligence. Elsevier and Tsinghua Univertity Press, 2021
3. Simon Haykin. Neural Networks and Learning Machines （3rd Edition). PHI Learning Private, 2010
4. 邱锡鹏. 神经网络与深度学习. 北京：机械工业出版社， 2020
