4.7 Article

Solving the XOR problem and the detection of symmetry using a single complex-valued neuron

期刊

NEURAL NETWORKS
卷 16, 期 8, 页码 1101-1105

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0893-6080(03)00168-0

关键词

complex-valued neuron; XOR problem; detection of symmetry; fading equalization problem; generalization; decision boundary; orthogonality; neural network

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This letter presents some results on the computational power of complex-valued neurons. The main results may be summarized as follows. The XOR problem and the detection of symmetry problem which cannot be solved with a single real-valued neuron (i.e. a two-layered real-valued neural network), can be solved with a single complex-valued neuron (i.e. a two-layered complex-valued neural network) with the orthogonal decision boundaries, which reveals the potent computational power of complex-valued neurons. Furthermore, the fading equalization problem can be successfully solved with a single complex-valued neuron with the highest generalization ability. (C) 2003 Elsevier Ltd. All rights reserved.

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