rake

virtual force matlab代码 求无线传感器网络的覆盖率~~~~(virtual force matlab coverage)

外点罚函数法，用于求解非线性优化问题，适用于matlb程序(Outside the penalty function method for solving nonlinear optimization problems for matlb program)

this is Laplace 2D . i solve with Jacobi Iteration method ,Point Gauss-seidel Interation method,Line Gauss-Seidel Iteration method ,Point Successive Over-Relaxation method (PSOR),Line Successive Over-Relaxation method (LSOR)

高速铁路路基沉降是一个复杂的系统过程,涉及不同时期、不同工况,选用单一的预测模型不足以反映路基整体的变形规律.Logistic模型及Verhulst模型的曲线均为S形,可以反映全过程的地基沉降与时间的关系.针对路基填筑期和降水期两个时段利用MATLAB软件编制程序计算模型参数,得到Logistic模型和灰色Verhulst模型,进而求得两者的最优加权组合模型.对比结果表明:在路基填筑期由两者的最优加权组合模型预测得到的结果与实测结果较吻合,拟合精度高于单一模型 而在降水期Verhulst模型的预测值更接近实测值,平均相对误差约为1.75％,拟合精度较高.(High-speed railway subgrade settlement process is a complex system involving different times and in different conditions, the choice of a single forecasting model does not adequately reflect the overall deformation of roadbed. Curve Logistic model and Verhulst models are S-shaped, the whole process can be reflected foundation settlement versus time. against roadbed construction period of two hours and precipitation using MATLAB software programming model parameters, the Logistic model and gray Verhulst model, and then get the optimal model of a weighted combination of the two. comparative results indicate : results and experimental results in the roadbed construction period by the weighted combination of the best of both models predicted than the anastomosis fitting accuracy than a single model precipitation predicted value of Verhulst model closer to the actual value of the average relative error approximately 1.75 fitting accuracy.)

matlab并行计算 很好很系统的讲诉并行计算在matlab是如何操作的(matlab parallel computing good system v. matlab parallel computing is how to operate)

Model Reference Adaptive Control

inverse kinematic for human robot

一种新的退避算法，用matlab仿真来实现该算法(a new way to complete the BP_decode)

Matlab program for tasting IIR filters: Butterworth, Chebishev 1, Chebishev 2 and eliptic filter

In this paper, we consider the use of Modulation Spectra for voice pathology detection and classification. To reduce the high-dimensionality space generated