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Noise Suppression by Artificial Neural Networks

Published: 13 November 2017 Publication History

Abstract

In this research paper, noise suppression ability of associative memories (e.g. Hopfield neural network) is briefly summarized. Motivated by this fact, noise suppression abilities of trained convolutional network are discussed. Introducing the concept of null vectors, noise suppression ability of Single Layer Perceptron, Multi-Layer Perceptron and Extreme Learning Machine are discussed.

References

[1]
J. Bruck and M. Blaum, Neural Networks, Error Correcting codes and polynomials over the binary cube, IEEE transactions on Information Theory, vol.35, no.5, September 1989.
[2]
G.Rama Murthy, Optimal Robust Filter Models of Synapse: Associated Neural Networks, Proceedings of International Conference on Soft Computing and Intelligent Systems, December 27-29, 2007.
[3]
G. Rama Murthy, Hybrid Neural Networks, Proceedings of International Conference on Power System Analysis, Control and Optimization (PSACO-2008), 13th-15th March 2008.
[4]
https://math.stackexchange.com/questions/786108/explicit-formula-for-inverse-ofupper-triangular-toeplitz-matrix-inverse.
[5]
Murthy, G. Rama. Multidimensional Neural Networks: Unified Theory. New Age International, 2008.
[6]
Huang, Guang-Bin, Qin-Yu Zhu, and Chee-Kheong Siew. "Extreme learning machine: theory and applications." Neurocomputing 70.1 (2006): 489--501.
[7]
Cortes, Corinna, and Vladimir Vapnik. "Support vector machine." Machine learning 20.3 (1995): 273--297.
[8]
Yegnanarayana, B. Artificial neural networks. PHI Learning Pvt. Ltd., 2009.
[9]
Rosenblatt, Frank. "The perceptron: A probabilistic model for information storage and organization in the brain." <rk-italic> Psychological review</rk-italic> 65.6 (1958): 386.

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AWICT 2017: Proceedings of the Second International Conference on Advanced Wireless Information, Data, and Communication Technologies
November 2017
116 pages
ISBN:9781450353106
DOI:10.1145/3231830
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  • CNRS: Centre National De La Rechercue Scientifique

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 November 2017

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Author Tags

  1. Artificial Neural Networks
  2. Hybrid Neural Networks
  3. Multi-Layer Perceptron
  4. Nulls

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