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System for self-organization of stable category recognition codes for analog input patterns
System for self-organization of stable category recognition codes for analog input patterns
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机译：用于模拟输入模式的稳定类别识别代码的自组织系统
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摘要
A neural network includes a feature representation field which receives input patterns. Signals from the feature representative field select a category from a category representation field through a first adaptive filter. Based on the selected category, a template pattern is applied to the feature representation field, and a match between the template and the input is determined. If the angle between the template vector and a vector within the representation field is too great, the selected category is reset. Otherwise the category selection and template pattern are adapted to the input pattern as well as the previously stored template. A complex representation field includes signals normalized relative to signals across the field and feedback for pattern contrast enhancement.
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