despread

xwch_test.m是主测试文件；biaoji.mat存放滤波器系数；xiangweicha.m用FFT计算相位差。 仿真框架为： 1.标记信号和双音信号续接作为发送信号； 2.对双音中一个频率分量的相位做偏移，再经过一个低通滤波器（引入线性相位，模拟收发不能同步测量现象）后，作为收到的信号； 3.用一个检测信号对收发信号进行相关运算； 4.画出收发信号以及相关处理后的信号。找出相关信号的那个尖点，从而推算出收发双音信号0相位点； 5. 输入0相位点位置，计算相对相位差。(xwch_test.m is the main test file biaoji.mat store filter coefficients xiangweicha.m calculated using FFT phase difference. Simulation framework: 1. Mark signals and then as a two-tone signal continued to send signals 2. On a two-tone frequency components of the phase shift to do, and then through a low pass filter (the introduction of linear phase, simulation can not simultaneously send and receive measuring the phenomenon), the as received signal 3. using a detection signal of the transceiver signal correlation operation 4. draw send and receive signals and related processed signal. Correlated signal of the cusp, which calculate the two-tone signal transceiver 0 phase point 5. Enter 0 phase point position, calculate the relative phase difference.)

u"+u=sinx, 0<x<1 u(0)=0, u(1)=0

tracking of ellipse by wheeled mobile robot

单纯型法，用于解决求解线性规划，用于求解问题的最优值的方法(simplex method)

自己编写的OFDM发生程序，做仿真的同学可用作源信号，很短，易读，需用matlab工具箱(I have written procedures for OFDM occurred, make simulation the students can be used as a source of signal, very short, easy-to-read, require matlab toolbox)

说明：  EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精度。 (EKF only uses non-linear function of the first-order Taylor expansion of some partial derivatives (ignoring higher order terms), often leading to the posterior distribution of the state estimates to generate large errors affect the performance of filtering algorithms, which affect the whole tracking system performance. Recently, the field of adaptive filtering algorithms and the emergence of new- and tasteless transform Kalman filter (Unscented Kalman Filter-UKF). EKF UKF filter is different from the idea that it points through the design of a small amount of σ by σ point spread through the nonlinear function to calculate the random vector first and second order statistical properties of the transmission. Therefore it is better than the EKF filter nonlinear characteristics equation of state approach, which is more than the EKF filter estimation accuracy.)

assmbly fot gears motor

用最邻近数据关联算法实现目标跟踪，对研究目标跟踪领域的朋友有用(With the nearest neighbor data association algorithm for target tracking)

自己写的一个基于肤色的人脸检测代码 用matlab做得 (face detection based on the skin colour)

power law transformation code