Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Principal Component Neural Networks: Theory and Applications

Principal Component Neural Networks: Theory and Applications

Diamantaras, K. I.
Kung, S. y.

Hardcover

Series: Adaptive and Cognitive Dynamic Systems: Signal Processing, L, Book 4

Technology & EngineeringGeneral Computers

ISBN10: 0471054364
ISBN13: 9780471054368
Publisher: Wiley-Interscience
Published: Mar 8 1996
Pages: 272
Weight: 1.25
Height: 0.72 Width: 6.37 Depth: 9.48
Language: English
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.

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