Title :
Non-linear Class-Modeling Using Artificial Neural Networks
Author :
Marini, Federico
Author_Institution :
Dept. of Chem., Sapienza Univ. of Rome, Rome, Italy
Abstract :
A new pattern recognition algorithm for class-modeling based on coupling an autoassociator artificial neural network with a SIMCA-like criterion is presented and discussed. The algorithm has been tested on different real and simulated datasets with promising results.
Keywords :
algorithm theory; neural nets; pattern recognition; SIMCA like criterion; artificial neural networks; autoassociator coupling; nonlinear class modeling; pattern recognition algorithm; simulated datasets; Algorithm design and analysis; Artificial neural networks; Chemistry; Feedforward systems; Fuzzy systems; Multi-layer neural network; Pattern analysis; Pattern recognition; Probability distribution; Testing; Class-modeling; SIMCA; artificial neural networks;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.805
