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说明：  几个VC++源代码，使用C-MEX文件来实现VC++与MATLAB的混合编程。(Several VC++ source code, the use of C-MEX file to achieve the VC++ and MATLAB programming mixed.)

matlab 一维小波变换，可以得到垂直、水平、对角线的对比图。(matlab one-dimensional wavelet transform, can be vertical, horizontal, diagonal comparison chart.)

可直接运行的matlab代码，Asift算法，比SIFT找到的特征点多很多。(Can be directly run matlab code, Asift algorithm, more than SIFT to find the feature points.)

自适应卡尔曼滤波的详细论述，附有卡尔曼滤波的程序实现，(Adaptive Kalman filter in detail, the procedures for implementation with Kalman filtering,)

毕业设计。用MATLAB实现BPSK编程。(Graduation project. Using MATLAB for BPSK.)

说明：  时间序列的自回归预测模型，是一个利用前期若干时刻的随机变量的线性组合来描述以后某时刻随机变量的线性回归模型(The autoregressive prediction model of time series is a linear regression model that describes random variables at a later time by using the linear combination of random variables at some earlier time.)

包含所有约束优化问题中涉及的matlab源程序。包含Rosen梯度法求解约束多维函数的极值，外点罚函数法解线性等式约束，外点罚函数法解一般等式约束，内点罚函数法，混合罚函数法，混合罚函数加速法，乘子法，坐标轮换法及复合形法(Contains all the constrained optimization problem involves matlab source. Contains Rosen gradient method for solving constrained multi-dimensional function extremum, external point penalty function method for solving linear equality constraints, external point penalty function method for solving general equality constraints, interior point penalty function method, mixed penalty function method, mixed penalty function acceleration method , multiplier method, the coordinate rotation method and complex method)

边缘检测对于图像理解、目标检测、跟踪等问题非常重要，该代码实现了canny算子做边缘检测(Edge detection for image understanding, target detection, tracking a very important issue, the code implementation of the canny edge detection operator to do)

OFDM链路级的仿真器场景是单小区单用户，信号从发送端发送，在接收端进行信号估计。估计误差可以从接收和发送信号的不同得到。仿真器的输出是BLER/BER vs SNR。(OFDM Link-level simulator focus on a single-cell single-user scenario, where signal is transmitted from tx, and estimated at rx. Comparing the difference in tx/rx signal, the error rate can be found out. The output of the link-level simulator is the BLER/BER vs. SNR mapping table。)

Pass the specification values to the object rather than accepting the default values for N, Fc1, and Fc2. Include the sampling frequency Fs as the final input argument. Design the filter and plot the results.