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To construction of the correct algorithm for pattern recognition tasks over fuzzy neuro-operator model

机译:模糊神经算子模型的模式识别任务的正确算法

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The developed approach allows to construct an algorithm which theoretically gives exact solution of pattern recognition problem if some conditions on input data of the problem hold. For the crisp model the conditions are conditions of solvability for the operator equation and they are the conditions of the correctness of an special algebra over pattern recognition (p.r.) tasks. The approach is not connected with a functional minimization and this is new aspect which differs from classical approaches to neural network constructions including fuzzy models also. The last means that the similar conditions can be given for the appropriate fuzzy recognition model.
机译:开发方法允许构建一种算法,如果问题保持的输入数据上的某些条件,理论上理论上的算法,如果有一些条件。对于脆模型,条件是操作员方程的可动化条件,并且它们是特殊代数在模式识别(P.R.)任务中的特殊代数的正确性条件。该方法没有与功能最小化连接,这是与包括模糊模型的神经网络结构不同的新方面。最后意味着可以给出适当的模糊识别模型的类似条件。

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