A comparison between the performance of feed forward neural networks and the supervised growing neural gas algorithm

Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Volumn 389, Issue 1-2, 1997, Pages 274-277

  Berlich, Rüdiger ^a,b   Kunze, Marcel ^a  

^a RUHR UNIVERSITY BOCHUM   (Germany)

^b MAX PLANCK INSTITUT FÜR PHYSIK   (Germany)

Author keywords

Crystal barrel; Evolutionary strategies; MLP; SGNG

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA STRUCTURES; FUNCTIONS; MATHEMATICAL TECHNIQUES; PERFORMANCE;

EVOLUTIONARY STRATEGY TRAINING; FUNCTION MAPPING; SUPERVISED GROWING NEURAL GAS ALGORITHM;

FEEDFORWARD NEURAL NETWORKS;

EID: 0031124436     PISSN: 01689002     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0168-9002(97)00085-5     Document Type: Article

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