SPH1.0

扩频通信仿真系统，包括各个模块的分析编码译码，以及跳频仿真，和同步模块分析(Spread spectrum communication simulation systems, including the analysis of each module)

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

应用matlab进行编程，利用R/S分析，计算Hurst指数(Application of matlab programming, using the R/S analysis to calculate the Hurst exponent)

rate range gyro balanced system control

Ant System algorithm solving classical Traveling Salesman Problems

sorce code for matlab voice recognition

Active and Reactive Power Flow Fuzzy Controller

SIMULATING THE LONG TERM EVOLUTION PHYSICAL LAYER

用粒子群优化算法进行特征选择和SVM参数优化(Using Particle Swarm Optimization algorithm of feature selection and SVM parameter optimization)

有源带通滤波器设计软件Filterlab中文使用参考资料(Active band-pass filter design software Filterlab Chinese use reference materials)