Complex-valued function approximation using an improved BP learning algorithm for feed-forward networks

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 2251-2258

  Savitha, R ^a   Suresh, S ^b   Sundararajan, N ^a   Saratchandran, P ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b INRIA   (France)

Author keywords

Complex valued elementary transcendental functions and its derivatives; Fully complex valued networks; Multi layer perceptron; Split complex network

Indexed keywords

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; EDUCATION; LEARNING SYSTEMS; MEDICAL IMAGING; NEURAL NETWORKS; OPTIMAL CONTROL SYSTEMS; OPTIMIZATION; POLYNOMIAL APPROXIMATION; PROBABILITY DENSITY FUNCTION;

ACTIVATION FUNCTIONS; BP LEARNING ALGORITHMS; COMPARATIVE ANALYSIS; COMPLEX NETWORKS; COMPLEX-VALUED ELEMENTARY TRANSCENDENTAL FUNCTIONS AND ITS DERIVATIVES; FULLY COMPLEX-VALUED NETWORKS; IMAGING APPLICATIONS; INITIAL WEIGHTS; LEARNING RATES; MULTI-LAYER PERCEPTRON; SPLIT COMPLEX NETWORK; VALUED FUNCTIONS; XOR PROBLEMS;

LEARNING ALGORITHMS;

EID: 56349140713     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634109     Document Type: Conference Paper

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