Principal Component Neural Networks: Theory and Applications (Adaptive and Cognitive Dynamic Systems: Signal Processing #4)

Description

Neural Network research studies how computers can be designed to emulate many of the logical and intelligent functions of the brain. The principles behind how the brain work are closely related to a statistical technique known as the Principal Component Analysis (PCA). PCA neural networks are systems that use this classical statistical technique to process information. Understanding biological perceptual systems is of great importance to engineers and computer scientists who wish to use this knowledge to develop artificial perceptual systems. This book examines the relationship between the technique of principal component analysis and neural networks. It provides a synergistic exploration of the mathematical, algorithmic, application and architectural aspects of these networks.