Soft computing for feature analysis Export

@article{citeulike:2148439, abstract = {With an introduction to soft computing we discuss how the three main ingredients, fuzzy logic, neural networks and genetic algorithms can play significant roles in the design of successful pattern recognition systems. Then we concentrate only on one aspect of pattern recognition, feature analysis, and discuss various methods using fuzzy logic, neural networks and genetic algorithms for feature ranking, selection and extraction including structure preserving dimensionality reduction. Finally, the methods are illustrated with both real and synthetic data.}, author = {Pal, N. R.}, citeulike-article-id = {2148439}, citeulike-linkout-0 = {http://www.ingentaconnect.com/content/els/01650114/1999/00000103/00000002/art00222}, keywords = {analysis, computing, feature, soft}, month = {April}, pages = {201--221}, posted-at = {2007-12-19 21:23:57}, priority = {2}, title = {Soft computing for feature analysis}, url = {http://www.ingentaconnect.com/content/els/01650114/1999/00000103/00000002/art00222} }

TY - JOUR ID - citeulike:2148439 L3 - citeulike-article-id:2148439 N2 - With an introduction to soft computing we discuss how the three main ingredients, fuzzy logic, neural networks and genetic algorithms can play significant roles in the design of successful pattern recognition systems. Then we concentrate only on one aspect of pattern recognition, feature analysis, and discuss various methods using fuzzy logic, neural networks and genetic algorithms for feature ranking, selection and extraction including structure preserving dimensionality reduction. Finally, the methods are illustrated with both real and synthetic data. EP - 221 TI - Soft computing for feature analysis SP - 201 KW - analysis KW - computing KW - feature KW - soft AU - Pal, NR UR - http://www.ingentaconnect.com/content/els/01650114/1999/00000103/00000002/art00222 ER -