广义非线性模型又称指数族非线性模型，它是普通正态非线性模型的推广。
The generalized nonlinear models (GNLMs), i. e. exponential family nonlinear models are the natural generalization of ordinary nonlinear models.
对非线性不等式约束最优化问题进行了讨论，借助广义投影建立求解问题的一个含系列自由参数的统一算法模型。
Optimization problem with nonlinear inequality constraints is discussed. With the help of the generalized projection, a unified algorithm model with a series of free parameters is presented.
建议的模型校正估计可以处理任何线性或非线性的工作模型，且在线性模型的情形下变为广义回归估计。
The proposed model-calibration estimators can handle any linear or nonlinear working models and reduce to the generalized regression estimators in the linear model case.
对于复杂的离散时间非线性系统，提出一种基于多模型的广义预测控制方法。
A multiple model based generalized predictive control is provided for complex nonlinear discrete time system.
考虑到粘弹性材料阻尼性能随环境的非线性变化，运用GRNN(广义回归网络)对粘弹阻尼材料动态力学性能函数进行逼近，并构建预测模型。
Considering the non-linear behavior of the viscoelastic material according to the change of environment, the GRNN is used to make a model to predict the dynamic property of the material.
将非线性广义有限元法应用到混凝土开裂问题的研究，采用弥散裂缝模型，研制了相应的程序。
Apply the nonlinear GFEM to study the concrete crack problem, develop the corresponding program using the smeared crack model.
用非线性车辆模型线性化方法，设计了基于广义卡尔曼滤波器和广义龙贝格观测器的质心侧偏角估计算法。
Through linearizing nonlinear vehicle model, vehicle side-slip Angle estimation algorithms based on generalized Kalman filter and generalized Luenberger observer are formulated.
结合广义非线性强度理论采用变换应力三维化方法简单、合理地使模型实现三维化。
Using transformed stress method, it is easy and reasonable to combine the model with the Generalized Non-linear Strength Theory to make the model describe complex stress states.
文中依据非线性舰船模型，应用模糊神经网络简化出适应于舵减横摇控制器设计的模糊线性模型，并设计了广义预测控制器。
According to the nonlinear model of ship, a predigested fuzzy linear model is built adapted to rudder roll stabilization using fuzzy neural networks.
文中依据非线性舰船模型，应用模糊神经网络简化出适应于舵减横摇控制器设计的模糊线性模型，并设计了广义预测控制器。
According to the nonlinear model of ship, a predigested fuzzy linear model is built adapted to rudder roll stabilization using fuzzy neural networks.
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