基于区间分段思想，将极化曲线非线性参数辨识转化为两个线性最小二乘辨识子问题。
The nonlinear parameter identification of fuel cell polarization curve was converted into two sub-problems of linear least square identification based on interval segmentation technique.
此无模型控制方法非常适用于实际的模型参数难以辨识，且是时变的非线性系统。
The model-free control is especially useful for real nonlinear systems whose model parameter are very difficult to be identified and time varying.
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.
研究了非线性连续—离散系统极大似然估计方法的实现及其在飞行器气动参数辨识中的应用问题。
The implementation of maximum likelihood estimation method to the nonlinear continuous ?discrete systems and application to aerodynamic parameter identification for vehicle are studied.
利用听觉频率非线性特性的美尔倒谱作为语音识别的特征参数，来辨识说话人提供的输入口令。
Also, since MFCC represent hearing frequency nonlinear characteristic, we utilize MFCC to be another speak recognition characteristic parameter to distinguish the input passwords.
所提出的辨识新方法，以递推最小二乘（RLS）参数估计与非线性规划（BFGS）为主体。
The new identification method for nonlinear systems is presented, which combinesrecursive least-square (RLS) parameter estimation with nonlinear programming (BFGS).
对非线性系统建立T-S模糊模型，并用正交最小二乘法（OLS）对模糊规则的后件参数进行辨识。
T S fuzzy model is constructed for nonlinear system in this paper, and orthogonal least squares (OLS) method is used to identify the parameters of fuzzy ruler consequents.
详细叙述了用能量法对建模的非线性方程进行线性化，并且利用总体最小二乘法对此类方程进行参数辨识。
A scheme utilizing is presented that energy method linearizes nonlinear equations which are acquired by modeling and the equations are solved by the total least squares.
本文研究了一类非线性分布参数系统的模型辨识及其状态观测器的设计方法，为这类系统的研究提供了新的途径。
A method of identification and state observer design of a nonlinear distributed parameter system is studied in this paper. A new approach for this kind of systems is proposed.
准确辨识油气悬架的非线性特征参数有利于提高车辆的乘坐舒适性和操纵性能。
To improve ride and handling performance of a vehicle, the exact knowledge of the nonlinear characteristics of the hydragas suspension is very important.
利用该平台验证了提出的变负载直流电机双闭环调速系统的非线性状态空间模型及其参数辨识方法的有效性。
The platform verified that the proposed variable load DC Motor Speed Control System with nonlinear state space model and parameter identification method is effectiveness.
然后根据选定的量测方案建立观测方程，并按极大似然原理导出非线性动力学系统的参数辨识算法。
According to the selected scheme an equation is constituted for the observation. Identification algorithm for the nonlinear dynamic system, is deduced following the maximum likelihood principle.
在模型辨识方面，我们专门研究了参数线性的非线性模型结构的选择技术及其算法。
On the aspect of model identification, we specially study the selection techniques for nonlinear model structure with linear parameters and the corresponding algorithms.
本文围绕励磁系统参数辨识这一题目进行研究，进行了励磁系统线性环节和非线性环节的参数型或非参数型的辨识。
This thesis carries out studies around the parameter identification of excitation system and carries out parameter identification of liner circle and nonparametric identification of nonlinear circle.
这种方法能够保证辨识出的参数是最佳的；而且不用求解对应的非线性最小二乘问题，只需求一元多项式的根，从而大大减少计算量。
This approach can guarantee that the identified parameters are optimal, by solving a one-dimensional polynomial equation instead of a nonlinear least square problem.
通过典型算例仿真分析表明这两种方法都可以有效跟踪非线性时变结构系统参数变化，并一定程度地提高了辨识精度。
The above method is validated by the simulation of a few nonlinear time-varying structural systems. The results show that the identification precision has been improved.
对基于静力位移结构识别问题的参数分组及可辨识性标准进行了讨论，建立了基于模拟退火-单纯形的完全非线性识别算法。
Then the parameter group and identifmbility criterions were discussed . the identification algorithm based on the simulated annealing - simplex shape algorithm was proposed.
该方法是在原有模糊聚类法的基础上，推导出的在线自适应模糊推理算法，可应用在时变非线性系统参数在线辨识中。
The method is a kind of on line adaptive fuzzy reasoning which is deduced based on fuzzy clustering method. The method can be used in parameters identification of time-varying system.
该模型用非线性刚度和非线性复合阻尼机理构造，模型中的参数由试验数据辨识。
The model is constructed by a nonlinear combination of dynamic nonlinear stiffness and dynamic nonlinear complex damping mechanisms.
该模型用非线性刚度和非线性复合阻尼机理构造，模型中的参数由试验数据辨识。
The model is constructed by a nonlinear combination of dynamic nonlinear stiffness and dynamic nonlinear complex damping mechanisms.
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