DCLAB

说明：  数据统计描述 第一节 数据分析中常用的统计量及其分布 第二节 频数变量数据特征描述 第三节 综述变量数据特征的描述 第四节 数据分析过程的记录与重现(Data described in section I of data analysis commonly used in statistics and their distribution in section II, the frequency characteristics of variable data variables described in Section III Summary data on the characteristics of the process of data analysis described in section IV of the record and reproduce)

simple dechirping example in typical RF systems

该程序能够实现合成孔径雷达中的RD成像算法(The program can be achieved in synthetic aperture radar imaging algorithm RD)

Oscillatory IMU tool. Use to convert MEMS sensor to moviment, with drift corrected

使用了JIT的高效的k均值算法，因为使用了JIT加速，所以在统计工具箱下，比一般的k均值要快许多(Efficient K-Means using JIT (Matlab code) This code uses the JIT acceleration in Matlab, so it is much faster than k-means in the Statistics Toolbox. It is very simple and easy to read. )

This function processes events from the main (single-algorithm) GUI screen

介绍了matlab在有限元方法求解中的应用，对于有限元求解有很大的帮助(Introduced in the finite element method matlab in the application of the finite element solution for the great help)

欧洲典型微网hatziargyriou_strunz_lv_benchmark_cigre05(European typical micro-mesh hatziargyriou_strunz_lv_benchmark_cigre05)

In this project, the standard particles swarm optimization - named here (MyPSO) is simulated and tested by five well-known benchmark functions (Sphere, Ackley, Rastrigin, Rosenbrock and Schwefel p2.26). Then, a new mechanism- named here (Improved MyPSO) is introduced to improve the performance of the standard particles swarm optimization to achieve better results and avoid stagnation at bad results. This new mechanism is also tested by the same benchmark functions. The results of improved PSO are then compared with those of standard PSO and different published improved PSO (SPSO, PSO-XD, CPSO-S and PSO-P5).

灰色系统预测，灰色系统的预处理，关联度分析(Grey system prediction, gray system pretreatment, association analysis)