제어로봇시스템학회:학술대회논문집
- 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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- Pages.466-469
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- 1996
축합조건의 분석을 통한 Langevine 경쟁 학습 신경회로망의 대역 최소화 근사 해석과 필기체 숫자 인식에 관한 연구
A study of global minimization analaysis of Langevine competitive learning neural network based on constraction condition and its application to recognition for the handwritten numeral
초록
In this paper, we present the global minimization condition by an informal analysis of the Langevine competitive learning neural network. From the viewpoint of the stochastic process, it is important that competitive learning guarantees an optimal solution for pattern recognition. By analysis of the Fokker-Plank equation for the proposed neural network, we show that if an energy function has a special pseudo-convexity, Langevine competitive learning can find the global minima. Experimental results for pattern recognition of handwritten numeral data indicate the superiority of the proposed algorithm.