Coherent optical neural network that learns desirable phase values in the frequency domain by use of multiple optical-path differences.

@article{Kawata2003CoherentON,
  title={Coherent optical neural network that learns desirable phase values in the frequency domain by use of multiple optical-path differences.},
  author={Sotaro Kawata and Akira Hirose},
  journal={Optics letters},
  year={2003},
  volume={28 24},
  pages={2524-6}
}
A coherent optical neural network is proposed that has the learning ability to achieve desirable phase values in the frequency domain. It is composed of multiple optical-path differences whose lengths are different from one another. The system learns a phase value at each discrete position in the frequency domain by obeying the complex-valued Hebbian rule. The learning curve also agrees with theoretical evolution. 
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