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The experimental data were trained by BP neural network, and the results were curve fitted to set up a fitting function which was used in the genetic algorithm process to reach the optimum.

首先利用BP神经网络来训练已有实验值,然后将训练后的神经网络作为知识源,通过曲线拟合与逼近求得设计变量与目标函数值的函数关系表达式,最后将这一函数表达式作为遗传算法的适应度函数进行遗传迭代寻找最优解。

As a direct application we show some results on the compression of gray scale digital images.

利用提出的方法给出了灰度图像逼近问题最直接的应用。

Then two algorithms for straight line generation are proposed. After that, the algorithms for generating lines in 3D and lines with grey scale are presented.

第二章首先提出了一个圆及椭圆最佳线逼近算法,其次提出了二个直线生成算法,然后提出了三维直线和多灰度直线的生成等算法。

Experimental results demonstrate that the proposed scheme is superior to the scheme based on wavelet modulus maxima by approximating better the edges of images.

实验结果表明,与基于小波模极大值的图像边缘检测方法相比,该文算法有较低的计算复杂度,所提取的边缘更加逼近图像真实边缘。

Simulation results obtained using both artificial and real data show that the estimation performance of the proposed method is a good approximation of the unknown function and the computation complexity is significantly reduced.

最后对人工和实际的样本进行了试验,结果说明了线性规划支持向量回归能较好地逼近被估计函数,且计算复杂度明显降低。

Simulation results for both artificial and real data show the generalization performance of our method is a good approximation of SVMs and the computation complexity is largely reduced by our method.

文中最后对人工和实际样本进行了实验,结果说明了线性规划支撑矢量机在推广能力上较好地逼近了原支撑矢量机,而在计算复杂度上明显低于原支撑矢量机。

Applying the triangular element to the stationary Stokes equation, we obtain error analysis and optimal convergent order of approximation solution.

对于各向异性三角形元和各向异性四面体元,我们分别讨论了它们的各向异性插值,将它们应用于定常Stokes方程,我们研究了有限元空间不满足散度条件的各向异性非协调有限元解法,同样得到了逼近解的误差分析和最优收敛阶。

With regard to the accuracy and smoothness of a set of discrete data points approximation, this paper gave a whole fairing and approximation algorithm of cubic Non-Uniform Rational B-Spline curve.

针对离散数据点序列的拟和精度及光顺度问题,提出了一种三次非均匀有理B样条曲线整体光顺逼近算法。

The performance of CDMA multiuser detectors with particle filter is close to that of optimum detectors, but with lower computational complexity, which is equal to that of some suboptimum detectors.

基于粒子滤波算法的多用户检测器在性能上逼近于最优多用户检测器,而计算复杂度远低于最优多用户检测器,与次优多用户检测器相当。

The iterative detect and decoding algorithm is a suboptimum joint receiver, can achieve the good trade off between the performance and complexity, and closing the Shannon limit performace.

次最优的迭代检测译码算法在性能和复杂度上可以取得折衷,并有效地逼近系统容量性能。

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