LFM_radar

基于MATLAB编写的SVM多分类算法程序(Based on MATLAB prepared multi-SVM classification algorithm procedure)

一个简单的GUI小程序，可以实现几种三维曲线的绘制与画等高线。(A simple GUI program, several three-dimensional curve drawing and painting contour.)

说明：  启发因子，信息素的重要程度 期望因子，城市间距离的重要程度 信息素增强系数 蚂蚁数量 表示每条边的能见度 参数可修改(heuristic factor, the importance of pheromone Expectation factor, the importance of distance between cities Pheromone enhancement coefficient Ant number Indicates the visibility of each side Parameters can be modified)

演示matlab如何实现通信遥控等,其中涉及到一些通信方面的知识,请查阅相关资料.()

unscented kalman filter

改进单纯形法在matlab中的实现。通过该程序可以实现优化目标。(Improved simplex method is implemented in matlab.Through the program can realize the optimization goal. )

说明：  通过并行压缩进行二维信号压缩，提出了一种利用并行压缩传感技术对二维信号进行压缩的新方案。根据这个原理，译码器的重新构造可以并行进行。通过对二维信号进行某些排列，可以确保所有列具有大致相同的密度级别，并且可以使用相同的测量矩阵进行采样。这样可以避免二维信号的矢量化，从而大大减小测量矩阵的尺寸。我们证明，如果排列良好，重建均方误差的上限会更紧。为了说明这一方案，我们将其应用于视频压缩并使用不同帧的排列有两种：参考帧的基于Z字形扫描的排列和非参考帧的基于块测试的排列。仿真结果表明，在相同的压缩比下，峰值信噪比比比在无置换情况下可提高3-7db左右。(we propose a new scheme to compress 2D signals using parallel compressed sensing. According to this seheme, the reeonstruction at the decoder can be performed in parallel. By performing certain permutation on a 2D signal, all columns are insured to have approximately the same density level and can be sampled using the same measurement matrix. In this way, vectorization of a 2D signal can be avoided, and thus the size of the measurement matrix can be dramatically reduced. We prove that with a good permutation, we can have a tighter upper bound on reconstruction mean square error. To illustrate this scheme, we apply it to video compression and use two kinds of permutations for different frames: the zigzag-scanbased permutation for reference frames and the block-test-based permutation for non-reference frames. Simulation results show that under the same compression ratio, the peak signal-to-noise ratio can be improved by approximately 3-7 dB compared to the case without permutation.)

Image Watermarking using DWT algorithm

实现信号的eemd分析，呈现其波动趋势，是继小波分析之后的又一信号分析利器(Emd achieve signal analysis, showing its fluctuation, wavelet analysis is the second after another signal analysis tool)

说明：  This is the worked example of using MOESP, the example found in: Subspace Methods for System Identification, written by: Tohru Katayama , "Springer 2005", page 160 example 6.6.