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structural self organizing
相关语句
  结构自组织
     To improve the nonlinear approximating ability of cerebellar model articulation controller(CMAC), by introducing the Gauss basis functions and the similarity measure based addressing scheme, a new kind of fuzzy CMAC with Gauss basis functions(GFCMAC) was presented. Moreover, based upon the improvement of the self organizing feature map algorithm of Kohonen, the structural self organizing algorithm for GFCMAC(SOGFCMAC) was proposed.
     为提高CMAC的非线性逼近能力 ,通过引入Gauss基函数和基于相似测量的寻址策略 ,提出一种新的Gauss基函数模糊CMAC网络 (GFCMAC) ,并进一步在对Kohonen的自组织映射算法进行改进的基础上 ,提出了GFCMAC的结构自组织算法 (SOGFCMAC) .
短句来源
     Simulation results show that adopting the Gauss basis functions and fuzzy techniques can remarkably improve the nonlinear approximating capacity of CMAC. Compared with the traditional CMAC,CMAC with general basis functions and fuzzy CMAC(FCMAC), SOGFCMAC has the obvious advantages in the aspects of the convergent speed, approximating accuracy and structural self organizing.
     仿真结果表明 ,采用Gauss基函数和模糊技术可以显著提高CMAC算法的非线性逼近能力 ,与传统CMAC、广义基函数CMAC和FCMAC等算法相比 ,SOGFCMAC算法在收敛速度、逼近精度和结构自组织等多方面都具有明显的优越性 .
短句来源
  “structural self organizing”译为未确定词的双语例句
     A hierarchically structural self organizing learning method is given, and a state estimation method is proposed. The structure and characteristics of the observer are discussed. The results of estimation show that the proposed nonlinear state observer can observe real systems state satisfactorily.
     给出了一种递阶自组织在线学习算法,提出了非线性时变系统的自适应状态观测器,并对其结构及特征进行了讨论,仿真结果表明这种自适应状态观测器能很好地观测系统的状态。
短句来源
     Radial Gaussian function networks based fuzzy systems with adaptive capability,are applied to the state estimation and fault detection of nonlinear time varying systems . In order to extract fuzzy IF THEN rules from input and output sample data through learning,the Gaussian function is employed to represent the membership functions of the premise part of fuzzy rules ,and then a hierarchically structural self organizing learning method is given.
     利用模糊系统和径向高斯函数网络,设计一种具有自适应能力的模糊神经网络.用高斯函数表示模糊规则前件的隶属度函数,然后,构造一种递阶自组织在线学习算法,从输入输出样本数据中,通过学习提取模糊IFTHEN规则;
短句来源
  相似匹配句对
     New Structural Self-Organizing Fuzzy CMAC with Basis Functions
     一种新型的结构自组织基函数模糊CMAC(英文)
短句来源
     Self-organizing Information of Life
     生命自组织信息
短句来源
     Self-Organizing Isometric Embedding
     基于自组织的鲁棒非线性维数约减算法
短句来源
     clothing self always transmit cultural data according to organizing new structural features;
     服饰总是以一种对文化的新的组合方式传递着文化讯息;
短句来源
     Study of Self-adaptive Structural Compensators
     自适应结构补偿器的研究
短句来源
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Radial Gaussian function networks based fuzzy systems is applied to the state estimation of nonlinear time-varying system. A hierarchically structural self-organizing learning method is given, and a state estimation method is proposed. The structure and characteristics of the observer are discussed. The results of estimation show that the proposed nonliear state observer can observe real systems state statisfactorily.

利用模糊系统的径向高斯函数网络对一类非线性时变系统的状态进行了估计.给出了一种递阶自组织在线学习算法,提出了非线性时变系统的自适应状态观测器,并对其结构及特征进行了讨论,仿真结果表明这种自适应状态观测器能很好地观测系统的状态.

Radial Gaussian function networks based on fuzzy systems is applied to the state estimation of nonlinear time varying systems. A hierarchically structural self organizing learning method is given, and a state estimation method is proposed. The structure and characteristics of the observer are discussed. The results of estimation show that the proposed nonlinear state observer can observe real systems state satisfactorily.

利用模糊系统的径向高斯函数网络对一类非线性时变系统的状态进行了估计。给出了一种递阶自组织在线学习算法,提出了非线性时变系统的自适应状态观测器,并对其结构及特征进行了讨论,仿真结果表明这种自适应状态观测器能很好地观测系统的状态。

Radial Gaussian function networks based fuzzy systems with adaptive capability,are applied to the state estimation and fault detection of nonlinear time varying systems .In order to extract fuzzy IF THEN rules from input and output sample data through learning,the Gaussian function is employed to represent the membership functions of the premise part of fuzzy rules ,and then a hierarchically structural self organizing learning method is given.Based on this method of state estimation and...

Radial Gaussian function networks based fuzzy systems with adaptive capability,are applied to the state estimation and fault detection of nonlinear time varying systems .In order to extract fuzzy IF THEN rules from input and output sample data through learning,the Gaussian function is employed to represent the membership functions of the premise part of fuzzy rules ,and then a hierarchically structural self organizing learning method is given.Based on this method of state estimation and fault detect for nonliear systems is proposed .The structure and characteristics of the observer are discussed. The results of simulation show that the proposed nonliear state observer can observe real system state and detect system fault satisfactorily.

利用模糊系统和径向高斯函数网络,设计一种具有自适应能力的模糊神经网络.用高斯函数表示模糊规则前件的隶属度函数,然后,构造一种递阶自组织在线学习算法,从输入输出样本数据中,通过学习提取模糊IFTHEN规则;在此基础上,提出一种非线性时变系统的自适应状态观测器设计和故障检测方法,并对其结构及特征进行了讨论,仿真结果表明,这种自适应状态观测器能很好地观测系统的状态,并能有效地应用于系统的故障检测.

 
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