针对多输入-多输出(MIMO)非线性系统基于模糊基函数向量提出了一种新的自适应控制方法。
In this paper, a novel adaptive control approach based on fuzzy basis function vector is presented for Multi input and Multi output (MIMO) nonlinear systems.
给出了基于TS模型的模糊基函数网络(FBFN),并提出了一种基于FBFN的未知系统故障信息检测通用方法。
Fuzzy basis function network (FBFN) based on t s fuzzy model is given. A general approach for fault information detection in unknown systems using FBFN is present.
通过一种新学习算法的导出,并结合模糊逻辑系统中的模糊基函数,给出了一种带有通用规则库的模糊滑模自适应控制器。
Universal optimization for adjustable parameters of fuzzy based function is realized by using GA and finding adjust law of parameters in general designing adaptive controller is replaced.
在学习过程中通过同时调整小波基函数的平移因子和隶属度函数的形状,使得模糊小波网络的精度和泛化能力大大提高。
By adjusting the translation parameters of the wavelets and the shape of membership functions, the accuracy and generalization capability of FWN can be remarkably improved.
为了在该情况下进行实例匹配,基于隶属度和贴近度的概念,构造了靶实例与基实例的模糊相似度函数,从而以统一形式同时处理上述两类数据。
In order to match the case in this situation, a fuzzy similarity function between case-target and Case-base was constructed based on the conception of membership degree and closeness degree.
这种模糊神经网络利用了小波基函数作为隶属函数,可在线根据误差调整隶属函数的形状,使模糊神经网络具有更强的学习和适应能力。
This fuzzy neural network USES wavelet basis function as membership function whose shape can be adjusted on line so that the networks have better learning and adaptive ability.
针对文本自动分类问题,提出了一种基于模糊向量空间模型和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.
文本提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
A classification method based on fuzzy vector space model and radial basis function network is presented in this paper.
针对模糊神经网络控制器难于设计的问题,提出了一种免疫进化算法用于径向基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.
由于RBF网络和模糊推理系统具有函数等价性,采用模糊经验值方法选取网络中心值和基函数数目。
Due to the function equivalence between RBF neural networks and fuzzy inference system, fuzzy experience method is adopted to select the centers and the numb er of basis function networks.
在标准模糊系统的基础上提出了以正规二次多项式和正规三角函数为基函数的两类标准模糊系统。
This paper establishes the standard fuzzy systems with partition of normal quadratic polynomial membership functions and normal trigonometric membership functions.
提出了一种基于自适应模糊系统的径向基高斯函数系统辨识方法,与传统的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.
提出了一种基于自适应模糊系统的径向基高斯函数系统辨识方法,与传统的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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