Optical neural networks based on wavelet transforms

Chunling Fan; Zhihua Jin; Weifeng Tian

doi:10.1117/12.483237

16 September 2002 Optical neural networks based on wavelet transforms

Chunling Fan, Zhihua Jin, Weifeng Tian

Proceedings Volume 4929, Optical Information Processing Technology; (2002) https://doi.org/10.1117/12.483237
Event: Photonics Asia, 2002, Shanghai, China

Abstract

The Fourier transform has been widely applied in the optical signal processing, yet it is just fit for analyzing the stationary signals. By extending the Fourier transform into wavelet transform, a new type of filter is proposed and its analogy to neural networks is developed. Optical neural networks (ONNs) are the new type networks, which possess good capacity of super parallel processing, signal transmission and high-density connecting lines. Although neural networks' implementations have been limited by the availability of high-resolution optical devices, by virtue of simple optical architectures for the wavelet transforms, the new neural network is easy to implement in large-scale by applying photoelectric technology. In this paper, the basic principles of ONNs and optical wavelet transform (OWT) are presented respectively, and the principle and structure of their combination—optical neural networks based on the wavelet transform are also proposed. For the optical neural networks and optical wavelet transforms, their optical implementations have many unique superiority, yet theirs combination takes on characteristics better than such structures just using neural networks or wavelet transform. Furthermore, their application perspectives are predicted in the paper.

Citation Download Citation

Chunling Fan, Zhihua Jin, and Weifeng Tian "Optical neural networks based on wavelet transforms", Proc. SPIE 4929, Optical Information Processing Technology, (16 September 2002); https://doi.org/10.1117/12.483237

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KEYWORDS

Neural networks

Wavelet transforms

Fourier transforms

Signal processing

Neurons

Wavelets

Spatial light modulators

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