Boolean Neural Network Design Using Set Covering in Hamming Geometrical Space

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概要

• 論文の詳細を見る

• Some novel learning strategies based on set covering in Hamming geometrical space are presented and proved, which are related to the three-layer Boolean neural network (BNN) for implementing an arbitrary Boolean function with lowcomplexity. Each hidden neuron memorizes a set of learning patterns, then the output layer combines these hidden neurons for explicit output as a Boolean function. The network structure is simple, reliable and can be easily implemented by hardware.

• 社団法人電子情報通信学会の論文
• 1999-10-25

著者

• Zhang Zhaozhi

  Southeast University

• MA Xiaomin

  Information Security Center, Beijing University of Posts & Telecommunications

• YI Xian

  Information Security Center, Beijing University of Posts & Telecommunications

• ZHANG Zhaozhi

  Institute of Systems Science, Academia Sinica

• Yi Xian

  Information Security Center Beijing University Of Posts & Telecommunications

• Ma Xiaomin

  Information Security Center Beijing University Of Posts & Telecommunications

• Zhang Zhaozhi

  Institute Of Systems Science Academia Sinica

関連論文

• A Built-in Reseeding Technique for LFSR-Based Test Pattern Generation(Timing Verification and Test Generation)(VLSI Design and CAD Algorithms)
• A Built-in Reseeding Technique for LFSR-Based Test Pattern Generation
• Boolean Neural Network Design Using Set Covering in Hamming Geometrical Space
• Bounds on the number of hidden neurons in three-layer binary neural networks

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