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lagrange multipliers method中文是什么意思

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  • 拉格朗日乘积因子法

例句与用法

  • The lyapunov theorem and lasalle invariance principle are applied to optimization sub - problem in augmented lagrange multiplier method
    参数不确定性和滞后特性在实际工业过程中广泛存在。
  • The lagrange multiplier method using rate and distortion information is then applied to optimal allocates bitrate for each frame in fine granular scalability substreams
    基于拉格朗日乘子法的最优化码率分配算法可以利用该模型中的率失真信息分配码率,在码率一定的条件下提供最好的视频效果。
  • This optimizing method had been used successfully in full - scale aircraft testing . 6 ) in the global equilibrating , a modified lagrange multiplier method had bring forward . this method can solve inequality constrained optimizer problems
    在整体平衡中,提出了改进的拉格朗日乘数法,成功地解决了含不等式约束条件的优化问题,该方法具有计算简单,收敛速度快等特点。
  • A spatial deployable truss structure was studied by the ways of multibody dynamics . the equation of multi body dynamics was set up with the lagrange multiplier method and the dynamics simulation models of deployable truss structures were built by adams and i - deas
    空间展开桁架结构属于多体动力学研究范畴,本文利用lagrange乘子法建立多体动力学方程,通过adams和i - deas建立空间展开桁架的多体动力学仿真模型,进行仿真计算。
  • A dynamical system is built which is satisfied to lyapunov function whose energy function is penalty function in augmented lagrange multiplier method . the dynamical system is global stable , and its stable solution is the optimization solution of sub - problem in augmented lagrange multiplier method according to lasalle invariance principle . finally a complete optimization algorithm is developed
    针对这种工业过程,本文基于一个lqr的性能指标(本性能指标和衰减系数和自然频率密切相关) ,提出应用本文提出的mmlaax优化算法,对不确定工业过程进行鲁棒pto控制器的设计,取得令人满意的效果。
  • The main achievements in this paper are summarized as follows . firstly , with the purpose of solving the low precision problem in the processing procedure of constraint condition , the augmented lagrange multiplier method is applied instead of the penalty function method . the practice indicates that the augmented lagrange multiplier method has a good effect on the enhancement of the precision
    本文的主要工作是:首先针对罚函数法处理约束所带来的约束条件满足精度不高的问题,尝试采用增广拉格朗日乘子法处理约束,并且实践证明,用该方法可以获得很好的效果,得到了能够更好满足约束指标的最优解。
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