查询词典 regression function

In this paper, the performance of SVM based on Fourier kernel is studied which aims at the regression in signal processing questions, and the influence of parameter q on performance of SVM is analyzed. A conclusion is drew that the integral of Fourier kernel in one period is a constant and the concept of equivalent kernel function width is proposed.

本文针对信号处理中的回归问题，研究了基于傅立叶核函数支持向量机的性能，并分析了参数q对其性能的影响；根据推导得出傅立叶核函数在单个周期内积分为常数的结论，并提出了等效核宽度的概念；最后的仿真结果证实了，在信号处理领域，采用傅立叶核函数的支持向量机比采用径向基核函数的有着更好的性能。

In the second chapter, we mainly study the robust estimation of mean components in generalized semiparametric mixed models , including robust estimation of regression parameters and nonparametric function.

第二章主要研究了广义半参数混合效应模型均值部分的稳健估计问题，包括回归参数和非参数函数的稳健估计。

To avoid these shortcomings, this paper uses particle swarm optimization approach, instead of Gauss-Newtonian algorithm, to optimize projecting direction, and applies Hermite polynomial, instead of piecewise linear regression, to fit ridge function.

但一般投影寻踪回归算法构造技术较为复杂，采用多次局部光滑回归，计算量较大，外推较为繁杂，容易陷于局部解。

Because the genetic algorithms could search the optimization of objective function randomly, which via the evolution of groups, our work is based on the embedding/detecting way of "DWT-Based Audio Watermarking Using Support Vector Regression and Subsampling". And this method provides a preliminary discussion on the application of GA, which searching the individual with the highest fitness of attack-resistance in the aggregate of the optimal embedding strength. As an optimization solution of obtaining the optimal embedding strength, it could achieve an adaptive policy, and find a reasonable balance between the robustness and inaudibility of the watermark, just for the better robustness and inaudibility in the algorithm.

遗传算法是通过群体进化来随机搜索目标函数的最优化问题，对于前述基于支持向量回归机的小波域数字音频盲水印算法，进一步地探讨采用遗传算在嵌入强度集合中搜索对抗攻击能力适应度较高的个体，从而得到最佳嵌入强度的一个优化方案，以实现自适应策略，也使本算法能在水印的鲁棒性和不可感知性之间寻找到合理的平衡点，从而具有更良好透明性和鲁棒性。

Different from conventional MLLR, the regression classes of TMLLR are generated dynamically based on increment of target function and a multi layer feedback mechanism.

并且由于这种算法的特殊多层结构，减少了许多中间的冗余计算，算法在具有较高的自适应精度的同时还具有较快的自适应速度。

Different from conventional MLLR, the regression classes of TMLLR are generated dynamically based on increment of target function and a multi-layer feedback mechanism.

这种算法基於目標驱动的原则，引入反馈机制，根据目標函数似然概率的增加来动態决定MLLR变换的变换类，大大提高了系统的识别率。

The correlative coefficients of linear regression function for isochronous stress-strain curve are all higher than 0.92, and the ratio of long-term strength to instantaneous strength reaches 94.39%, which indicate that the whole creep of fine sandstone specimen is weak.

应力－应变等时曲线线性回归函数的相关系数均高于0.92，长期强度与瞬时强度之比达94.39%，证明细砂岩试样的整体蠕变特性不强。

A method is put forward to find the better ε of the ε-non-sensitive loss function based on the particle swarm optimization. The simulation result shows the regression support vector machines take far fewer times than using the way of latticework searching to get the desired result the efficience is improved greatly and optimal ε is obtained.

本文给出了一种基于粒子群优化算法的、对ε不敏感损失函数的ε参数寻优的方法，仿真结果表明：采用基于粒子群优化算法的寻优方法寻找ε参数，需要重复训练回归支持向量机模型的次数明显小于格点搜索方法，节省了大量的时间并且能找到较优的ε值。

For the case of linear function, a classification algorithm based on Rough Set and regression is presented.

另外我们给出了一个更一般的、根据连续属性的等价类定义，对线性的特殊情况，给出了基于粗糙集和回归分析的分类方法。

This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.

给出了线性回归模型中的加权最小二乘估计以及最优权数的选择。

It was just a normal day of school

那只是上学的普通一天

Which is a very good reference in this issue.

这是一个在这个问题上很好的参考。