The Behavior of the Complex Integral Neural Network (original) (raw)

Abstract

In this paper, we introduce an Integral Neural Network based on complex domain. We describe the model of the neuron, analyze the behavior of the neuron, and indicate that in certain conditions it performs the calculation of Fourier Integration. Have studied on the neural network with hidden layers, we obtain the following facts: 1. This kind of structure can memorize a time variant function; 2. It calculates the convolution of input series and the function the neural network memorized; 3. This neural network structure also can calculate the correlation function; 4. In the case of many hidden layers, it can perform the Fourier Transform with many variants.

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Author information

Authors and Affiliations

  1. Institute of Computing Technology, Tongji University(West Campus), 200331, Shanghai
    Pan Yong
  2. Suzhou Railway Teachers College, Suzhou, 215009, Jiangsu
    Shi Hongbao & Li Lei

Authors

  1. Pan Yong
  2. Shi Hongbao
  3. Li Lei

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina Regina, S4S 0A2, Saskatchewan, Canada
    Wojciech Ziarko & Yiyu Yao &

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© 2001 Springer-Verlag Berlin Heidelberg

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Yong, P., Hongbao, S., Lei, L. (2001). The Behavior of the Complex Integral Neural Network. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X\_79

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