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Applied Artificial Higher Order Neural Networks for Control and Recognition

Lee

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English | 511 pages | IGI Global; 1st edition (May 5, 2016) | 1522500634 | PDF | 10.42 Mb

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.
Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emeg research, practice, and real-world implementation, this ly reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and eeering students.



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