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|Title:||Evolutionary computation for statistical pattern recognition||Authors:||Wang, Xiao||Keywords:||DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition||Issue Date:||2006||Source:||Wang, X. (2006). Evolutionary computation for statistical pattern recognition. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||Evolutionary computation as a general problem-solving technique has been extensively applied in statistical pattern recognition. Typically, evolutionary algorithms are developed to solve complex optimization and search problems involved in different folds of designing a recognition system, e.g. feature extraction, supervised classification and clustering. These problems are often characterized by high-dimensional search spaces with convoluted landscape, noisy data, and little information about the objective functions. Traditional optimization methods are not efficient in dealing with them and evolutionaryalgorithms are therefore introduced.||Description:||139 p.||URI:||https://hdl.handle.net/10356/39128||DOI:||10.32657/10356/39128||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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