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https://hdl.handle.net/10356/39128
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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WangXiao2006.pdf | Main report | 18.13 MB | Adobe PDF | ![]() View/Open |
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