RWLock

matlab与vc联合编程实例 实现图形在vc中的显示(joint programming and matlab examples vc in vc in the realization of graphics display)

复杂网络matlab工具包，很好用的哦,用了会说好的，方便易懂(complex network matlab)

this is a file that about matlab this is a file that about matlab

这是大学毕业时设计的失真度检测仪论文，由模拟陷波器实现的剔除几波，如果改进的话，可以用数字滤波器实现，不过成本更高(It is designed for university graduation thesis distortion detector by analog notch filter removed to achieve a few waves, if improved, you can use digital filters to achieve, but higher costs)

numerical code for matlab analytical bisec differentiation F FALSEPOS fixedpoint

微分方程网格生成 计算传热学 离散方法 自适应网格(The differential equation of grid generation)

卷积编码器g1=111,g2=101 x为输入的待译码序列 x=[1,0,1,0,0,1,0,0,0,1,0,1,1,1] x=[1,1,0,1,0,1,1,0,0,1] x=[1,1,1,0,0,0,1,0,1,1] a=size(x) 输入序列的长度 s=a(2)/2 译码后的m序列长度为x的一半 m=zeros(1,s) 最终结果存放 ma=zeros(1,s+1) 存放Fa路径的 mb=zeros(1,s+1) 存放Fb路径的 mc=zeros(1,s+1) 存放Fc路径的 md=zeros(1,s+1) 存放Fd路径的(viterbi decoder)

Texas A&M大学Lihong Wang教授编写的经典，用蒙特卡罗模型模拟光在组织、复杂介质、溶液中的传播。附带详细说明文件。(Classics Professor Lihong Wang Texas A & M University, prepared using Monte Carlo simulation model of light in the organization, the complexity of the medium, the solution spread. With detailed documentation.)

说明：  ：Mean—shift算法是一种非参数密度估计算法，可以实现快速的最优匹配，在目标的实时跟踪领域起着非常 重要的作用。为了有效的将Mean—shift算法应用到灰度图像中，采用了以方向直方图建立目标模型的策略，提出了在灰 度图像中以Mean—shift为核心的目标跟踪算法。实验结果表明，该算法具有不受光照条件影响的优点，在低对比度的情 况下仍能实现稳定、实时的跟踪目标。(: Mean-shift algorithm is a nonparametric density estimation algorithm, the optimal matching can be fast, real-time tracking fields in the target plays an important role. In order to effectively Mean-shift algorithm will be applied to the gray image, the histogram used to establish the direction of the strategy target model is proposed in the gray image to Mean-shift tracking algorithm as the core. Experimental results show that the algorithm has the advantage of not lighting conditions, in the case of low contrast can still achieve stability, real-time tracking of targets.)

利用matlab进行频域低通和带通滤波,效果不错(Frequency domain using matlab low-pass and band-pass filtering)