exp10pcm

现有的几个网络拓扑随机发生器，其实很难生成理想的网络拓扑结构，其主要原因在于很难控制节点的疏密和间距。我们提出来的这个改进算法，在随机抛撒节点的时候使用了K均值聚类，由本算法作为网络拓扑发生器，网络节点分布均匀且疏密得当，边的分布也比较均衡(The few existing random network topology generator, is in fact very difficult to generate the desired network topology, the main reason it is difficult to control the node density and spacing. We put forward the improved algorithm, throw in random nodes when using the K-means clustering, by the algorithm as a network topology generator, network nodes and spacing evenly distributed properly, the edge of a more balanced distribution of)

说明：  在神经网络中用迭代法对人脸图像进行压缩及恢复(Iteration in the neural network human face using image compression and restoration)

利用matlab来实现多项式的运算，及其各种符号的使用。例如求极限，数值积分，函数的求导等(Using matlab to achieve polynomial operations, and its various symbols are used. Such as finding the limit, numerical integration, function derivation, etc.)

去斜率（strech）参考信号与回波信号混频后得到中频输出信号S(t)=Aexp(j*2*pi*f0*t+phase) 其中f0与回波延时的关系为： f0=k*delay_t K为线性调频斜率，delay_t为回波延时 将s(t)采样，FFT变换即可得到目标距离与频谱的关系。 Strech 信号测距 输入混频后的中频信号（图一），经采样及FFT变换得到频谱（图二） 再根据频谱与距离的关系式R=Tcf/2B显示出距离(图三) (Go slope (strech) obtained after the reference signal and the echo signal mixer IF output signal S (t) = Aexp (j* 2* pi* f0* t+phase) f0 and echo delay relationship: f0 = k* delay_t K chirp slope, delay_t the echo delay sampling s (t), the FFT transform to the target distance spectrum of relations. Strech signal ranging input mixer IF signal (Figure 1), sampling and FFT transform spectrum (Figure 2) according the the spectrum distance relationship R = Tcf/2B shows the distance (Figure 3))

This the program for Generalized synchronization of fractional order Hyperchaotic chen system

本人写的中值和均值滤波的代码，主要用于SAR成像滤波，希望管理员给予通过(I wrote the median and mean filtering code, mainly for SAR image filtering, administrators hope to give through)

Optical flow or optic flow is the pattern of apparent motion of objects, surfaces, and edges in a visual scene caused by the relative motion between an observer (an eye or a camera) and the scene.[2][3] The concept of optical flow was first studied in the 1940s and ultimately published by American psychologist James J. Gibson[4] as part of his theory of affordance. Optical flow techniques such as motion detection, object segmentation, time-to-collision and focus of expansion calculations, motion compensated encoding, and stereo disparity measurement utilize this motion of the objects surfaces and edges.[5][6]

Lame波反对称部分的基本模态的matlab 程序(Antisymmetric part of the Lame wave )

仿真2PSK数字通信系统。信道中噪声模型为加性高斯白噪声。接收端有自适应滤波器。(Simulate 2PSK communication system. Noise in channel is ideal additive Gaussian white noise. Adaptive filter is designed at receiving terminal.)

ldmgi的MATLAB算法和相关的源程序(ldmgi of MATLAB algorithms and source code related to)