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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© 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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DOI: https://doi.org/10.1007/3-540-45554-X_79
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