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Showing 1 - 5 of 5 matches in All Departments
Knowledge-Based Intelligent Techniques in Character Recognition presents research results on intelligent character recognition techniques, reflecting the tremendous worldwide interest in the applications of knowledge-based techniques in this challenging field. This resource will interest anyone involved in computer science, computer engineering, applied mathematics, or related fields. It will also be of use to researchers, application engineers and students who wish to develop successful character recognition systems such as those used in reading addresses in a postal routing system or processing bank checks. Features
Fuzzy set theory - and its underlying fuzzy logic - represents one of the most significant scientific and cultural paradigms to emerge in the last half-century. Its theoretical and technological promise is vast, and we are only beginning to experience its potential. Clustering is the first and most basic application of fuzzy set theory, but forms the basis of many, more sophisticated, intelligent computational models, particularly in pattern recognition, data mining, adaptive and hierarchical clustering, and classifier design.
Knowledge-Based Intelligent Techniques in Character Recognition presents research results on intelligent character recognition techniques, reflecting the tremendous worldwide interest in the applications of knowledge-based techniques in this challenging field.
In the last two decades the artificial neural networks have been
refined and widely used by the researchers and application
engineers. We have not witnessed such a large degree of evolution
in any other artificial neural network as in the Adaptive Resonance
Theory (ART) neural network. The ART network remains plastic, or
adaptive, in response to significant events and yet remains stable
in response to irrelevant events. This stability-plasticity
property is a great step towards realizing intelligent machines
capable of autonomous learning in real time environment.
In the last two decades the artificial neural networks have been
refined and widely used by the researchers and application
engineers. We have not witnessed such a large degree of evolution
in any other artificial neural network as in the Adaptive Resonance
Theory (ART) neural network. The ART network remains plastic, or
adaptive, in response to significant events and yet remains stable
in response to irrelevant events. This stability-plasticity
property is a great step towards realizing intelligent machines
capable of autonomous learning in real time environment.
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