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Data Pattern Recognition Based on Ultra-High Frequency Sigmoid and Trigonometric Higher Order Neural Networks

Data Pattern Recognition Based on Ultra-High Frequency Sigmoid and Trigonometric Higher Order Neural Networks

Copyright: © 2021 |Pages: 43
ISBN13: 9781799835639|ISBN10: 1799835634|ISBN13 Softcover: 9781799835646|EISBN13: 9781799835653
DOI: 10.4018/978-1-7998-3563-9.ch011
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MLA

Ming Zhang. "Data Pattern Recognition Based on Ultra-High Frequency Sigmoid and Trigonometric Higher Order Neural Networks." Emerging Capabilities and Applications of Artificial Higher Order Neural Networks, IGI Global, 2021, pp.455-497. https://doi.org/10.4018/978-1-7998-3563-9.ch011

APA

M. Zhang (2021). Data Pattern Recognition Based on Ultra-High Frequency Sigmoid and Trigonometric Higher Order Neural Networks. IGI Global. https://doi.org/10.4018/978-1-7998-3563-9.ch011

Chicago

Ming Zhang. "Data Pattern Recognition Based on Ultra-High Frequency Sigmoid and Trigonometric Higher Order Neural Networks." In Emerging Capabilities and Applications of Artificial Higher Order Neural Networks. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-3563-9.ch011

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Abstract

This chapter develops a new nonlinear model, ultra high frequency sigmoid and trigonometric higher order neural networks (UGT-HONN), for data pattern recognition. UGT-HONN includes ultra high frequency sigmoid and sine function higher order neural networks (UGS-HONN) and ultra high frequency sigmoid and cosine functions higher order neural networks (UGC-HONN). UGS-HONN and UGC-HONN models are used to recognition data patterns. Results show that UGS-HONN and UGC-HONN models are better than other polynomial higher order neural network (PHONN) and trigonometric higher order neural network (THONN) models, since UGS-HONN and UGC-HONN models can recognize data pattern with error approaching 10-6.

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