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

机译:基于模糊神经算子模型的模式识别任务正确算法的构建

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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:如果问题的输入数据中的某些条件成立,则所开发的方法允许构造一种算法,该算法从理论上给出模式识别问题的精确解决方案。对于明快模型,条件是算子方程的可解性条件,并且是特殊代数对模式识别(p.r.)任务的正确性的条件。该方法与功能最小化无关,这是一个新的方面,它与包括模糊模型在内的神经网络构造的经典方法不同。最后意味着可以为适当的模糊识别模型提供相似的条件。

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