本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hid

人工蜂群ABC算法的VC++源代码，在四个基准目标函数下，经仿真测试可成功运行，对刚接触ABC的初学者很有帮助-ABC VC++ artificial bee colony algorithm source code, in the four benchmark objective function, the simulation tests can be run successfully, very helpful for beginners new to ABC

This package includes a C++ class with several tracking methods based on the Kernelized Correlation Filter (KCF) [1, 2]. It also includes an executable to interface with the VOT benchmark.