A fast learning method using cost matrices for morphological neural networks

SISY 2005 - 3rd Serbian-Hungarian Joint Symposium on Intelligent Systems

Volumn , Issue , 2005, Pages

  Nobuhara, Hajime ^a   Bede, Barnabas ^b   Hirota, Kaoru ^a  

^a TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

^b BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

Author keywords

Gradient method; Mathematical morphology; Max plus algebra; Neural networks

Indexed keywords

ALGEBRA; GRADIENT METHODS; INTELLIGENT SYSTEMS; LEARNING SYSTEMS; MATHEMATICAL MORPHOLOGY; NEURAL NETWORKS;

ARTIFICIAL TRAINING; COMPUTATION TIME; COST MATRICES; FAST LEARNING; IDEMPOTENT; MAX-PLUS ALGEBRA; MIDDLE LAYER; MORPHOLOGICAL NEURAL NETWORKS;

MATRIX ALGEBRA;

EID: 84943422144     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

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3. J. V. Oliveira: Neuron inspired learning rules for fuzzy relational structures, Fuzzy Sets and Systems, Vol. 57, No. 1, 1993, pp. 41 - 53
4. J. L. Davidson and G. X. Ritter: A Theory of Morphological Neural Networks, SPIE, Vol. 1215, 1990, pp. 378 - 388
5. G. X. Ritter, D. Li and J. N. Wilson: Image Algebra and its Relationship to Neural Networks, SPIE, Vol. 1098, 1989, pp. 90 - 101