OFDM_16QAM

Mean Shift 这个概念最早是由Fukunaga等人[1]于1975年在一篇关于概率密度梯度函数的估计中提出来的,其最初含义正如其名,就是偏移的均值向量,在这里Mean Shift是一个名词,它指代的是一个向量,但随着Mean Shift理论的发展,Mean Shift的含义也发生了变化,如果我们说Mean Shift算法,一般是指一个迭代的步骤,即先算出当前点的偏移均值,移动该点到其偏移均值,然后以此为新的起始点,继续移动,直到满足一定的条件结束. 用matlab实现mean shift算法仿真(Mean Shift the concept was first used by Fukunaga et al [1] in 1975 in an article on the probability density function estimation of gradient raised its original meaning, as its name implies, is the offset of the mean vector, where is the Mean Shift a noun, it refers to a vector, but with the Mean Shift the development of the theory, Mean Shift the meaning has changed, if we say that Mean Shift algorithm, generally refers to an iterative steps, namely, first calculate the current point Mean offset, move the shift points to its average, and then as a new starting point and continue to move until the end to meet certain conditions. realize using mean shift algorithm matlab simulation)

Multiple Access Channel with Generalized FeedBack rate region analysis MAtlab Code

分析写作，主要分析研究人类社会学对人类思维思路的影响，深入扩宽人的分析能力(anlsis writing)

基于LMS自适应时延估计算法，可以进行时间延迟估计。(Delay estimation algorithm based on LMS adaptive research based on the fractional lower order time delay estimation algorithm, including: covariation-based time delay estimation, based on the fractional lower order covariance delay estimation method, as well as the minimum norm when the average P delay estimation method.)

对图像进行中值滤波处理，没有用到matlab自带函数(Binary image processing, matlab built function is not used)

利用遗传算法优化RBF神经网络的结构，包括优化权值、高斯基的中心和宽度(The use of genetic algorithm to optimize the structure of RBF neural network, including the right to optimize the value of the Gaussian center and width)

this will u in HSPICE tools

这是一本描述随机过程在物理和生物系统中应用方面的书籍(Freund, J. A. et al.(eds)- stochastic processes in physics, chemistry, and biology- springer, 2000Springer.Verlag.Freund.Poeschel.(2002).Stochastic.Processes.in.Physics.Chemistry.and.Biology)

说明：  已经验证过的64点FFT的Matlab源代码(64 points of FFT algorithm by been verified through matlab tool)

计算赫斯特指数Calculates the generalized Hurst exponent H(q) of a stochastic variable x(t) (a time series) the scaling of the renormalized q-moments of the distribution <|x(t+r)-x(t)|^q>/<x(t)^q> ~ r^[qH(q)] The value of H(q) give indication about the fractal nature of the signal. H(q) = 0.5 corresponds to a Brownian motion, deviations form 0.5 and dependency on q are indications of multi-fractality and time-correlations.(Calculates the generalized Hurst exponent H(q) of a stochastic variable x(t) (a time series) the scaling of the renormalized q-moments of the distribution <|x(t+r)-x(t)|^q>/<x(t)^q> ~ r^[qH(q)] The value of H(q) give indication about the fractal nature of the signal. H(q) = 0.5 corresponds to a Brownian motion, deviations form 0.5 and dependency on q are indications of multi-fractality and time-correlations.)