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Showing 1 to 4 of 4 for “"Vigilance Parameter"”.
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VECTOR QUANTIZATION USING ODE BASED NEURAL NETWORK WITH VARYING VIGILANCE PARAMETER
Vector Quantization importance has been increasing and it is becoming a vital element in the process of classification and clustering of different types of information to help in the development of machines learning and decisions making, however the different techniques that implements Vector …
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An Ordinary Differential Equation Based Model For Clustering And Vector Quantization
… patterns. The proposed system includes a dynamic parameter, called vigilance parameter. This parameter approximately reflects the radius of the generated valleys. Through several examples of different pattern clusters, it is shown that the model can successfully quantize/cluster these types of …
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Neuroengineering of Clustering Algorithms
… a family of multi-criteria ART models: dual vigilance fuzzy ART and distributed dual vigilance fuzzy ART (both of which are capable of detecting complex cluster structures), merge ART (aggregates partitions and lessens ordering effects in online learning), and cluster validity index vigilance …
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REAL-TIME CLASSIFIER BASED ON ADAPTIVE COMPETITIVE SELF-ORGANIZING ALGORITHM
… of clusters, and they are defined with their parameters such as depth, width and vigilance parameter. These control parameters are effective on convergence speed, the accuracy of labeling, etc. We are going to study the level of effectiveness of those parameters on clustering assignments with …