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hessian matrix相关的网络例句

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与 hessian matrix 相关的网络例句 [注:此内容来源于网络,仅供参考]

And the Levenberg-Marquardt iteration, which can avoid to compute Hessian matrix, is adopted as the learning rule to train the samples of this feedforward network.

针对传统的梯度下降优化算法收敛速度慢的特点,采用可避免计算Hesse矩阵的Levenberg-Marquardt算法来训练神经网络。

In order to perform an accurate navigation, the centerline of the model must be extracted. In this paper, a new centerline extraction algorithm based on Hessian Matrix is proposed.

要想快速准确地进行虚拟内窥漫游,一个首要的步骤是要先提取出模型的中心线以指导视点的移动。

Compared to perturbation method, the influences of many factors on voltage stability margin are considered and Hessian matrix of control parameters is not necessarily calculated. The method has high calculation speed and accuracy.

相对于摄动方法而言,该方法将各种因素对于电压稳定域的影响考虑在内,且不需要求取控制参数的海森矩阵,具有计算速度快、精度高的特点。

The Hessian matrix of every function in this model is constant, so it will be calculated once in the entire optimal process based on interior point method, which speeds up each iteration.

该新模型的海森矩阵是精确的常系数矩阵,在内点法迭代过程中只需要计算一次,从而缩短了每次迭代的计算时间。

In Chapter 5, a new method with direct partitioned column updates of cholesky factorization for solving large scale sparse unconstrained optimization problems is proposed, which depends on a consistent partition of the columns and cholesky factorization of the Hessian matrix.

第5章基于稀疏Hesse阵的列的相容分划,并在其Cholesky分解的基础上建立了求解大型稀疏无约束优化问题的直接校正Cholesky因子算法。

3Several semicontinuous phase transitions in SC model by tracing the Hessian matrix and the corresponding phase diagram in BC model.

4对一些在SC模型下的不连续相变,我们直接在BC模型下进行了计算。

Next, define the constant elements hij of the n×n hessian matrix H.

其次,定义n×n海赛矩阵H的常数元数为hij。

In the modified method, we use orthogonal decomposition so as to delete items which lead to linear dependence of gradient in active constraints. Therefore the Hessian matrix of the DQP subproblem is positive definite.

在改进算法中,我们通过正交分解删去了有效约束函数中引起梯度线性相关的项,从而保证了DQP子问题中的目标函数中的Hesse阵正定。

In Chapter 4, a symmetric triangular partitioned secant method for solving large scale sparse unconstrained optimization problems is constructed, which is a combination of a secant method and a finite difference method, and depends on a consistent partition of the columns of the lower triangular part of the Hessian matrix; it reduces the number of gradient evaluations required by Powell and Toints algorithm (the indirect lower triangular substitution algorithm) by one at every iterative step.

此算法是基于稀疏Hesse阵的下三角部分的列的相容分划的基础上建立起来的,把割线法和有限差分法有机的结合在了一起,在每次迭代中,把由Powell和Toint的算法所需要的梯度赋值次数减少了一。

It exploits the structured of the Hessian matrix of the objective function sufficiently. An attractive property of the structured BFGS method is its local superlinear/quadratic convergence property for the nonzero/zero residual problems.

它们充分利用了目标函数的Hesse矩阵的结构以提高算法的效率,该算法的显著优点是对于零残量问题具有二阶收敛性而对于非零残量问题具有超线性收敛性。

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