tomcat_dist

压缩采样中各种贪婪算法性能的matlab仿真比较，包括LS-MP，OMP，WMP，硬阈算法(Compression of various sampling greedy algorithm performance of matlab simulation comparison, including LS-MP, OMP, WMP, hard threshold algorithm )

基于高斯核密度函数的运动目标检测程序。参考文章是background and foreground Modeling Using kernel density Estimation for visual surveilence(This programe used in moving object detection, the programe refer to article background and foreground Modeling Using kernel density Estimation for visual surveilence)

信号在信道进行传输时，经常会出现串扰，采用基于最大似然序列估计（MLSE）的电子色散均衡器的方法，克服光纤通信中的由各种色散引起的码间干扰。 研究基于最大似然序列估计（MLSE）的均衡器，采用维特比算法实现，用matlab仿真出采用MLSE后的性能指标（眼图和误码率）的提升。 (Signal transmission channel, often occur crosstalk, based on the maximum likelihood sequence estimation (MLSE) method for electronic dispersion equalizer, overcome the optical fiber communication in a variety of dispersion caused by intersymbol interference. Research Based on the maximum likelihood sequence estimation (MLSE) equalizer, using the Vitby algorithm, the performance index using MLSE after matlab simulation (eye diagram and bit error rate) promotion.)

matlab中增量式PID控制(Incremental PID Control in MATLAB)

MIT 数据挖掘原理。。。。数据挖掘原理(MIT Data Mining Principles. . . . Principles of Data Mining)

本程序运用一阶扰动理论自适应特征值方法的跟踪信号子空间，然后运用ESPRIT算法 跟踪信源的时变DOA(this matlab code(program) apply the First-Order Perturbations trak the signal subspace and eigenvalues,and then perform the time-variant or time-invariant DOA through the subspace tracked via the First-Order Perturbations with ESPRIT algrithm.)

标准的粒子滤波器matlab程序，附有详细注释，可以帮助有效掌握粒子滤波算法。希望大家多提建议(Standard particle filter matlab program, with detailed notes, can help grasp the particle filter algorithm. I hope you more suggestions)

功能：本程序演示MATLAB常用命令的基本操作 用法：运行该程序后，切换到命令窗口，按提示进行操作(Function: This program demonstrates MATLAB basic operation of the common commands usage: run the program, switch to the command window and follow the prompts)

切削力系数程序，用于预测铣削加工过程中的切削力系数(Program of cutting force coefficient)

具有丰富的参数选项,基于欧几里得距离的聚类分析，非归零型差分相位调制信号建模与仿真分析 。( It has a wealth of parameter options, Clustering analysis based)