• 所以使用径向模糊滤镜创造出一种有趣的效果

    Instead, I used the radial blur filter which created an interesting effect.

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  • 文本提出一种基于模糊向量空间模型径向函数网络分类方法

    A classification method based on fuzzy vector space model and radial basis function network is presented in this paper.

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  • 利用模糊系统径向高斯函数网络一类非线性时变系统的状态进行估计

    Radial Gaussian function networks based on fuzzy systems is applied to the state estimation of nonlinear time varying systems.

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  • 仿真结果表明基于自适应模糊pid控制器电液伺服控制径向柱塞变量具有良好动态性能

    Simulation results show that the dynamic characteristic of electro-hydraulic servo controlling radial piston pump using this self-adapting fuzzy PID controller is very good.

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  • 针对模糊神经网络控制器难于设计问题,提出了一种免疫进化算法用于径向函数模糊神经网络控制器参数的优化设计。

    Aiming at the design difficulty for fuzzy neural network controller, an immune evolutionary algorithm is proposed to design the parameters of a radial basis function fuzzy neural network controller.

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  • 针对文本自动分类问题提出了基于模糊向量空间模型径向基函数网络的分类方法

    Aimed at the problems of document automatic classification, a classification method is proposed based on fuzzy vector space model and RBF network.

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  • 文中模糊函数理论为基础,分析了时分析产生交叉原因给出了径向高斯函数为核函数自适应时频分析优化算法

    This paper based on ambiguity function theory analyzes the cause of cross-components and gives the optimization algorithm of adaptive TFD with radially-gaussian kernel.

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  • 提出广义模糊推理概念基础上,提出并分析了广义模糊径向基(rbf)神经网络模型,给出了网络广义学习算法

    A new concept of generalized fuzzy inference and the generalized fuzzy RBF network model are presented. The generalized Lear ni ng algorithm of this network model is derived.

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  • 提出一种基于自适应模糊系统径向基高斯函数系统辨识方法传统系统辨识和仿真方法相比,更具有精确性与智能性

    The modeling based on the system recognition theory and using the least square method in the case of the partially linear relationship the simulation precision is greatly improved.

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  • 提出一种基于自适应模糊系统径向基高斯函数系统辨识方法传统系统辨识和仿真方法相比,更具有精确性与智能性

    The modeling based on the system recognition theory and using the least square method in the case of the partially linear relationship the simulation precision is greatly improved.

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