Function approximation using generalized adalines

IEEE Transactions on Neural Networks

Volumn 17, Issue 3, 2006, Pages 541-558

  Wu, Jiann Ming ^a   Lin, Zheng Han ^b   Hsu, Pei Hsun ^c  

^a NATIONAL DONG HWA UNIVERSITY   (Taiwan)

^b MINGDAO UNIVERSITY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Adalines; Generative models; Mean field annealing; Perceptron; Postnonlinear projection; Potts encoding; Supervised learning

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; DATA REDUCTION; INTEGER PROGRAMMING; LINEAR PROGRAMMING; OPTIMIZATION; PARAMETER ESTIMATION; RANDOM PROCESSES; STATE ASSIGNMENT; THRESHOLD LOGIC; TRANSFER FUNCTIONS; VECTOR QUANTIZATION;

GENERALIZED ADALINES; GRADIENT DESCENT METHODS; K-STATE TRANSFER FUNCTION; MEAN FIELD ANNEALING METHODS; POSTNONLINEAR PROJECTION; POTTS ENCODING; SUPERVISED LEARNING;

FUNCTION EVALUATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; INFORMATION RETRIEVAL; METHODOLOGY; SYSTEMS THEORY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; INFORMATION STORAGE AND RETRIEVAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; SYSTEMS THEORY;

EID: 33646496538     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/tnn.2006.873284     Document Type: Article

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