首先给出一种在线修改遗忘因子的模糊辨识方法。
This paper first presents a fuzzy identification method with forgotten factor on line revised.
最后，探讨了模糊辨识方法在系统预测方面的应用。
Finally, the application of fuzzy identification to predication behavior of systems is discussed.
过程的模糊模型和逆模糊模型均可由模糊辨识获得。
The fuzzy model and its inverse fuzzy model can be obtained by fuzzy identification.
在第一部分，提出了一种改进的广义交叉验证模糊辨识方法。
In the first block, a modified generalized Cross validation blur identification method was proposed.
并探讨了模糊辨识方法在预测复杂系统行为方面的两个重要问题。
Two important issues about the fuzzy model for the predication behavior of complex systems are discussed.
该文提出了一种基于最差子空间分解聚类的非线性系统模糊辨识方法。
This paper proposed a fuzzy identification method for nonlinear systems which were based on decomposing clustering of the worst subspace.
提出了一种新的基于遗传模糊软分类和卡尔曼滤波方法的模糊辨识算法。
A method of fuzzy identification based on genetic soft fuzzy clustering and Kalman filtering method is proposed.
将该辨识器用于一类非线性系统的模糊辨识，仿真结果验证了所提出方法的有效性。
The identifier is applied to the fuzzy identification for a class of nonlinear systems, and the simulation results demonstrate the effectiveness of the proposed identification methods.
本文提出用灰色模糊辨识来确定粮食的相关因子，这是判断各种因子相关性的新机理。
In this paper, the correlative factor of grain is determined via grey fuzzy i-dentification.
在建立模糊规则时，应用了专家经验与模糊辨识相结合的方法，使规则更加合理可信。
By combination of expert experience and fuzzy identification, the fuzzy rules become more reliable.
在此基础上，系统地综述模糊辨识领域存在的理论与实际问题，并探讨了今后的研究方向。
Based on the discussion, the paper also summarizes systematically fuzzy identification theory and practical problems, and points out the research trends in the future.
针对一类多输入多输出不确定非线性系统，提出一种基于模糊辨识的混合鲁棒自适应控制方法。
A hybrid robust adaptive control based on fuzzy identification for a class of multiple-input -multiple-output nonlinear systems was proposed with plant unknown and external disturbances.
针对复杂非线性动态系统的模糊建模问题，基于T -S模型提出一种自组织模糊辨识算法。
In view of modeling problems of nonlinear and dynamic system, a self organizing fuzzy identification algorithm (SOFIA) is presented based on t s model in this paper.
提出一种基于新的模糊模型和加权递推最小二乘算法(WRLSA)的非线性系统模糊辨识方法。
A fuzzy identification method for nonlinear systems is suggested based on a new fuzzy model and weighted recursive least square algorithm (WRLSA).
先通过基于模糊竞争学习确定一种在线模糊辨识算法，并给出递推模糊竞争学习算法收敛性证明。
First of all, an on-line fuzzy identifying algorithm is confirmed by means of fuzzy competitive learning, and the convergence about a recursive algorithm of fuzzy competitive learning is proved.
针对多输入多输出非线性系统，把自适应模糊控制和自适应模糊辨识结合起来，提出了一种间接自适应模糊控制方案。
Combining the adaptive fuzzy control with the adaptive fuzzy identification, this paper presents an indirect adaptive fuzzy control scheme for MIMO nonlinear systems.
先验模糊辨识方法是先获得点扩展函数的信息后再进行图像恢复，而迭代盲目反卷积方法是同时估计出清晰图像和点扩展函数。
Priori Blur Identification gets the PSF before restoration implementation, while Iterative Blind Deconvolution estimates the true image and the PSF at the same time.
该文提出一种用于复杂的非线性未知系统辨识的混合神经网络模型—自适应模糊神经网络(AFNN)。
This paper presents a compound neural network model, i. e., adaptive fuzzy neural network (AFNN), which can be used for identifying the complicated nonlinear system.
在被调整模糊系统基础上，提出了一种非线性系统在线估计参数的在线辨识算法。
Moreover, based on this modified fuzzy system, the paper presents an on line identifying algorithm with which the on line parameter estimation of nonlinear system is realized.
模糊系统辨识是模糊系统建模的主要手段，优化的模糊系统结构是模糊系统辨识的关键。
Fuzzy system identification is one of the main approaches of fuzzy system modeling. Optimized fuzzy system structure is the key of fuzzy system identification.
自适应算法中，不但跟踪误差而且辨识误差都参与模糊逻辑系统中的参数调节。
In the adaptive algorithm, the parameter adjusting laws of the fuzzy logic systems are derived by the tracking error and the identification error.
本文在李雅普·诺夫稳定性意义下，提出了一种辨识模糊关系模型的学习算法。
A learning algorithm based on Lyapunov stability is derived to fuzzy relational model identification in this paper.
运用索赔风险的模糊综合与辨识模型分析索赔风险，可以迅速而准确地解决这一难题。
The analysis of claims risk by the fuzzy comprehensive and identity model can get this difficult problem solved quickly and accurately.
在交易中，当新发现了市场数据和行为之间的关系时，这种积极的感觉是模糊的，不容易辨识的。
With trading, the connection can be obscured and more difficult to recognize as a result of the positive feelings being generated from discovering new relationships in market data and behavior.
针对单输入单输出非线性系统的自适应控制问题，提出了一种在线自适应模糊神经网络辨识与鲁棒控制的方法。
An online adaptive fuzzy neural network identification and robust control approach were proposed for the adaptive control problem of SISO nonlinear system.
仿真研究表明，SVM具有优良的逆模型辨识能力，基于模糊控制补偿的支持向量机逆控制系统的动态性能好、跟踪精度高、鲁棒稳定性强。
Simulations demonstrate that SVM has good nonlinear approximation capability for inverse model, and the proposed control system has good dynamic and static performances as well as good robustness.
根据电液伺服系统的故障特点，本文提出了采用模糊神经网络做在线辨识器的容错控制方案。
According to fault characteristic of the electro hydraulic servo system, this paper has proposed a fault tolerant project that USES the fuzzy neural network as an identifier on-line.
该方法利用模糊似然函数对样本数据进行聚类，并使模糊模型的结构辨识和参数辨识能同时完成，从而实现模糊模型的在线辨识。
The proposed method can accomplish the structure identification and the parameter identification of the fuzzy model in the same time, and implements the on-line identification of the fuzzy model.
该方法利用模糊似然函数对样本数据进行聚类，并使模糊模型的结构辨识和参数辨识能同时完成，从而实现模糊模型的在线辨识。
The proposed method can accomplish the structure identification and the parameter identification of the fuzzy model in the same time, and implements the on-line identification of the fuzzy model.
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