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信号分析 信号 分析 信号分析 -signal analysis

说明：  要研究一个新的重建算法-迭代软阈值算法，该算法根据所要解决的问题而确定一个阈值函数，并且可以将阈值算法和迭代算法有效的结合使用，明显的提高了重建信号的精度。本文主要对语音信号和带噪语音信号分别进行信号重建性能分析和研究。包括信号的稀疏性表示、观测矩阵的设计和选择、信号的重建过程及效果，通过实验仿真的波形图，进而对其和原语音信号不同之处进行了分析与对比。(To study a new reconstruction algorithm iterative soft threshold algorithm, this algorithm determines a threshold function according to the problem to be solved, and can effectively combine the threshold algorithm and iterative algorithm, which significantly improves the accuracy of reconstruction signal. In this paper, the performance of speech signal reconstruction is analyzed and studied. It includes the sparse representation of signal, the design and selection of observation matrix, the reconstruction process and effect of signal. Through the waveform of experimental simulation, it analyzes and compares its differences with the original voice signal.)

说明：  该.m文件使用分支定界法来求解TSP问题(Branch and bound method for TSP)

说明：  MIMO信道容量仿真，包括AWGN, Rayleigh, CorrRayleigh, Rice四种类型的信道。(MIMO channel capacity simulation, including AWGN, Rayleigh, CorrRayleigh, Rice four types of channels.)

金属圆柱体的RCS散射，采用矩量法编写，在TE波和TM波的情况(Metal cylinder RCS scattering, using moment method to prepare, in the TE wave and TM wave of)

弹簧阻尼单元，可用于有限元编程分析。仅供参考！(Spring-damper units, can be used for finite element analysis program. For reference only!)

说明：  在传统的蚁群算法上实现了改进，排序蚁群算法实现路劲规划(The traditional ant colony algorithm is improved, and the sorting ant colony algorithm is used to realize the road stiffness planning)

用于配电网的重构的混合整数二阶锥规划，利用yamilp工具箱，同时利用了cplex/mosek等求解器求解，配电网示例网架结构较简单。(The mixed integer two order cone programming is used in the distribution network reconfiguration, and the yamilp toolbox is used. At the same time, the cplex/mosek solver is used to solve the problem. The grid structure of the distribution network is simple.)

用户管理权限项目，使用java实现的版本，内有数据库脚本(User management privilege project, using the version implemented in java, with database scripts)

说明：  经验模态分解，求取本征模IMF，用于求解函数或者输出响应的时域分解，与FFt和小波分析不同，具有独特的优势。(Empirical mode decomposition (EMD) is used to solve the time domain decomposition of function or output response, which is different from FFT and wavelet analysis.)