Meikang Qiu

Han Qiu

Cheng Zhang

Zongming Fei

Sun Yuan Kung

This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021. The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.

14th International Conference, KSEM 2021, Tokyo, Japan, August 14-16, 2021, Proceedings, Part II

Knowledge Science, Engineering and Management

K. I. Diamantaras

S. Y. Kung

Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectural aspects of principal component neural networks. Using a unified formulation, the authors present neural models performing PCA from the Hebbian learning rule and those which use least squares learning rules such as back-propagation. Examines the principles of biological perceptual systems to explain how the brain works. Every chapter contains a selected list of applications examples from diverse areas.

Theory and Applications

Principal Component Neural Networks

14th International Conference, KSEM 2021, Tokyo, Japan, August 14-16, 2021, Proceedings, Part III

Sun Yuan Kung

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