ID3

仅供学习中的朋友进行matlab实验指导书的教学实验源代码(Learning for friends matlab experiment experimental teaching guide book source code)

Hu7不变矩 (hu7 moment invariant )

FLOW AROUND A SQUARE FDM is used to solve Vorticity Stream Function

各算法对应的问题如下： 　　PSO 用基本粒子群算法求解无约束优化问题 　　YSPSO 用带压缩因子的粒子群算法求解无约束优化问题 　　LinWPSO 用线性递减权重粒子群优化算法求解无约束优化问题 　　SAPSO 用自适应权重粒子群优化算法求解无约束优化问题 　　RandWPSO 用随机权重粒子群优化算法求解无约束优化问题 　　LnCPSO 用学习因子同步变化的粒子群优化算法求解无约束优化问题 　　AsyLnCPSO 用学习因子异步变化的粒子群优化算法求解无约束优化问题 　　SecPSO 用二阶粒子群优化算法求解无约束优化问题 　　SecVibratPSO 用二阶振荡粒子群优化算法求解无约束优化问题 　　CLSPSO 用混沌粒子群优化算法求解无约束优化问题 　　SelPSO 用基于选择的粒子群优化算法求解无约束优化问 　　BreedPSO 用基于交叉遗传的粒子群优化算法求解无约束优化问 　　SimuAPSO 用基于模拟退火的粒子群优化算法求解无约束优化问题(13 PSO algorithms and coursewares)

knn 只是个函数实现 需要其它函数的引用(k-nearest neighbor u need to import this function to other functions to run it)

OFDM的仿真程序，可以下载共大家学习哦！！(OFDM simulation program, you can download a total learning Oh! !)

用matlab的mesh命令画出所要求解的大量数据文件的图形(The mesh command using matlab draw large amounts of data required for solution of graphic files)

还可以了电动饿了丰富额份额分积分二分法而非(it can den edfjief ef efef efe ff f )

“Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。(In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal relationships between the object of interest and its local context based on a Bayesian framework, which models the statistical correlation between the low-level features (i.e., image intensity and position) from the target and its surrounding regions. The tracking problem is posed by computing a confidence map, and obtaining the best target location by maximizing an object location likelihood function. The Fast Fourier Transform is adopted for fast learning and detection in this work. Implemented in MATLAB without code optimization, the proposed tracker runs at 350 frames per second on an i7 machine. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods in terms of efficiency, accuracy and robustness.)

HIgh pass FIR filter. Can be applied to one dimensional signal.