一类二次Sigmoid神经元构建的分类器分类能力的理论分析
Theoretical Analysis on Classification Capability of Classifier Containing Quadratic Sigmoid Neurons
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摘要: 针对含二次Sigmoidal神经元的前向神经网络,研究了它的模式分类能力.通过分 析它在解决Dichotomy问题所需的规模,从而得到了这种神经元模型对神经网络分类器的分 类能力的改进程度.Abstract: This paper addresses the classification capability of network containing quadratic sigmoidal neurons. By analysing the size of the network required for solving Dichotomy problem, we can figure out the degree of the improvement on the classification capability of net- work by using quadratic sigmoidal neurons.
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Key words:
- Neuron model /
- dichotomy /
- threshold /
- classification capability
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