An Adaptive High-Order Neural Tree for Pattern Recognition

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 34, Issue 2, 2004, Pages 988-996

  Foresti, G L ^a   Dolso, T ^a  

^a UNIVERSITY OF UDINE   (Italy)

Author keywords

High order perceptrons (HOPs); Learning; Neural trees; Pattern recognition

Indexed keywords

COMPUTATIONAL COMPLEXITY; ERROR ANALYSIS; HIERARCHICAL SYSTEMS; INTELLIGENT AGENTS; LEARNING ALGORITHMS; LEARNING SYSTEMS; PROBLEM SOLVING; SENSITIVITY ANALYSIS; SPURIOUS SIGNAL NOISE; TOPOLOGY; TREES (MATHEMATICS);

HIGH ORDER PERCEPTRONS (HOP); NEURAL TREES;

PATTERN RECOGNITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; DECISION SUPPORT SYSTEM; EVALUATION; FEEDBACK SYSTEM; METHODOLOGY; NATURAL LANGUAGE PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DECISION SUPPORT TECHNIQUES; FEEDBACK; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NATURAL LANGUAGE PROCESSING; NEURAL NETWORKS (COMPUTER);

EID: 1842430911     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2003.818538     Document Type: Article

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