| Metacognitive Learning in a Fully Complex-Valued Radial Basis Function Neural Network. | |
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MedLine Citation:
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PMID: 22168554 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Recent studies on human learning reveal that self-regulated learning in a metacognitive framework is the best strategy for efficient learning. As the machine learning algorithms are inspired by the principles of human learning, one needs to incorporate the concept of metacognition to develop efficient machine learning algorithms. In this letter we present a metacognitive learning framework that controls the learning process of a fully complex-valued radial basis function network and is referred to as a metacognitive fully complex-valued radial basis function (Mc-FCRBF) network. Mc-FCRBF has two components: a cognitive component containing the FC-RBF network and a metacognitive component, which regulates the learning process of FC-RBF. In every epoch, when a sample is presented to Mc-FCRBF, the metacognitive component decides what to learn, when to learn, and how to learn based on the knowledge acquired by the FC-RBF network and the new information contained in the sample. The Mc-FCRBF learning algorithm is described in detail, and both its approximation and classification abilities are evaluated using a set of benchmark and practical problems. Performance results indicate the superior approximation and classification performance of Mc-FCRBF compared to existing methods in the literature. |
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Authors:
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R Savitha; S Suresh; N Sundararajan |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-12-14 |
Journal Detail:
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Title: Neural computation Volume: - ISSN: 1530-888X ISO Abbreviation: - Publication Date: 2011 Dec |
Date Detail:
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Created Date: 2011-12-15 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9426182 Medline TA: Neural Comput Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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School of Computer Engineering, Nanyang Technological University, 639798 Singapore savi0001@ntu.edu.sg. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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