[PDF.16wg] Applied Artificial Higher Order Neural Networks for Control and Recognition (Advances in Computational Intelligence and Robotics)

Applied Artificial Higher Order Neural Networks for Control and Recognition (Advances in Computational Intelligence and Robotics)

[PDF.qt00] Applied Artificial Higher Order Neural Networks for Control and Recognition (Advances in Computational Intelligence and Robotics)

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 |  2016-05-05 | Original language:English |  11.02 x1.19 x8.50l,3.36 | File type: PDF | 511 pages

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||About the Author||Ming Zhang received a M.S. degree in information processing and a Ph.D. degree in the research area of computer vision from the East China Normal University, Shanghai, China, in 1982 and 1989, respectively. He held Postdoctoral Fellowshi

In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless.

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