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Author:

Shi, Yunhui (Shi, Yunhui.) (Scholars:施云惠) | Ruan, Qiuqi (Ruan, Qiuqi.)

Indexed by:

EI Scopus

Abstract:

In this paper, we propose a new type of continuous wavelet transform. However we discretize variables of integral a and b, any numerical integral has a high resolution, and a does not appear in the denominator of the integrand. Furthermore, we give two discrezitation methods of the new wavelet transform. For the one-dimensional situation, we give quadrature formula of the discretized inverse wavelet transform. For the multi-dimensional situation, we develop the commonly wavelet network based on the discretized inverse wavelet transform of the new wavelet transform. Finally, the numerical examples show that the continuous wavelet transform constructed in this paper has higher computing accuracy compared with the classical continuous wavelet transform.

Keyword:

Integral equations Neural networks Wavelet transforms Functions Fourier transforms Mathematical models Algorithms

Author Community:

  • [ 1 ] [Shi, Yunhui]College of Computer Science, Beijing University of Technology, Beijng, 100022, China
  • [ 2 ] [Ruan, Qiuqi]Institute of Information Science, Beijing Jiaotong University, Beijng, 100044, China

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Source :

Year: 2004

Volume: 1

Page: 207-210

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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