A neural network learning for adaptively extracting cross-correlation features between two high-dimensional data streams

IEEE Transactions on Neural Networks

Volumn 15, Issue 6, 2004, Pages 1541-1554

  Feng, Da Zheng ^a   Zhang, Xian Da ^a   Bao, Zheng ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

Cross correlation features; Cross correlation neural network (CNN); Global asymptotic stability; Learning rate; Nonquadratic criterion (NQC); Stationary point; SVD

Indexed keywords

ASYMPTOTIC STABILITY; COMPUTER SIMULATION; CORRELATION METHODS; FEATURE EXTRACTION; LEARNING ALGORITHMS; MATHEMATICAL MODELS; MATRIX ALGEBRA; OPTIMIZATION;

CROSS CORRELATION FEATURES; CROSS CORRELATION NEURAL NETWORKS (CNN); GLOBAL ASYMPTOTIC STABILITY; LEARNING RATE; NONQUADRATIC CRITERION (NQC); SINGULAR VALUE DECOMPOSITION; STATIONARY POINT;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; EVALUATION; FEEDBACK SYSTEM; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; SIGNAL PROCESSING; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; FEEDBACK; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED; STATISTICS;

EID: 9244222211     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2004.838523     Document Type: Article

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