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说明：  一种新的盲源分离方法 Injecting noise for analysing the stability of ICA components (Injecting noise for analysing the stability of ICA components)

This is matlab code for simulation pdf of Nakagami

四轮转向两自由度模型，测质心侧偏角和横摆角速度(Four-wheel steering two degree of freedom model of center of mass of side-slip Angle and yawing angular velocity measurement)

CDMA中DSSS直序扩频仿真代码，采用了移位寄存器产生扩频码(DSSS simulation in CDMA system)

运动目标跟踪程序-MATLAB源代码,利用camshift和meanshift实现运动目标的跟踪(Moving target tracking program - MATLAB source code, using camshift and meanshift to achieve tracking of moving targets)

回归分析的matlab实现(Regression analysis matlab realize)

this is about pattern recognition.

RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。该代码是求解RPCA的一种数值算法——Exact ALM（Exact Augmented Lagrange Multiplier）(The most basic form of the exact ALM function is [A, E] = exact_alm_rpca(D, λ), and that of the inexact ALM function is [A, E] = inexact_alm_rpca(D, λ), where D is a real matrix and λ is a positive real number. We solve the RPCA problem using the method of augmented Lagrange multipliers. The method converges Q-linearly to the optimal solution. The exact ALM algorithm is simple to implement, each iteration involves computing a partial SVD of a matrix the size of D, and converges to the true solution in a small number of iterations. The algorithm can be further speeded up by using a fast continuation technique, thereby yielding the inexact ALM algorithm.)

利用Canny的方法实现边沿检测，核函数采用高斯核，sigma大小可以任意调节，阈值也可以任意选。界面优美。(Does the method of using Canny edge detection, the function USES the gaussian kernel, sigma size can be adjusted, and the threshold can be arbitrarily chosen. Beautiful interface.)

提出了一种新的算法结构,通过建立“局部环境因数”模型,利用集中式处理模式,动态 分配全局勘探和局部开采子种群比例,有效地实现分工目的,平衡算法的局部和全局搜索能力。将其 应用到两个不同类型的实际工程约束优化问题中进行验证,并与其他文献的改进算法进行了对比。 实验结果表明,该算法比其他改进算法在计算精度、效率、鲁棒性上都有很大的提高(Anewalgorithmarchitecturewasproposed. Inorder to adjust effectively the ratioof exploration subgroup versusexploitationone, the algorithmadopted the centralizedprocessingtechnique toconstruct the local environment factor, andbalancedthe local andglobal searchcapabilitiesof the algorithm. Furthermore, comparedwithother improvedintelligent algorithms, experimental results got from the application and verification of real constrained engineering design problem indicate that the algorithmperformsbetter intermsof accuracy, efficiencyandrobustness)