BDProtocal

使用遗传算法和蚁群算法求解TSP问题，并且 实时地将计算结果和所用时间等信息显示在界面上，很直观。(The use of genetic algorithms and ant colony algorithm for TSP problem, and real-time results and the use of the time information is displayed in the interface is very intuitive.)

VC_与MATLAB混合编程在语音处理中的应用(VC_ mixed with the MATLAB programming in Speech Processing)

说明：  c语言例题程序，还有最小二乘法支持向量机的MATLAB调试测试运行(Example programs c language, as well as least squares support vector machines to run MATLAB Debugging and Testing)

基于Matlab对表面肌电信号时频域分析处理的GUI界面程序(Surface EMG frequency domain analysis of the GUI interface program based on Matlab)

用matlab编写的卡尔曼滤波程序，一个文件(Kalman filter using matlab programs written in)

capture sound port compared matlab own to capture signal biological

Turbo Convolution Code

说明：  遗传算法是计算数学中用于解决最佳化的搜索算法，是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题，一定数量的候选解（称为个体）的抽象表示（称为染色体）的种群向更好的解进化。传统上，解用二进制表示（即0和1的串），但也可以用其他表示方法。进化从完全随机个体的种群开始，之后一代一代发生。在每一代中，整个种群的适应度被评价，从当前种群中随机地选择多个个体（基于它们的适应度），通过自然选择和突变产生新的生命种群，该种群在算法的下一次迭代中成为当前种群。(Genetic algorithm (GA) is a search algorithm used to solve optimization in computational mathematics. It is one of evolutionary algorithms. Evolutionary algorithms were originally developed by borrowing phenomena in evolutionary biology, such as heredity, mutation, natural selection and hybridization. Genetic algorithms are usually implemented as a computer simulation. For an optimization problem, an abstract representation of a certain number of candidate solutions (called individuals) (called chromosomes) evolves towards a better solution. Traditionally, solutions are represented in binary (that is, strings of zeros and ones), but other representations are possible. Evolution begins with a population of completely random individuals, and it happens from generation to generation.)

非对称的贝塞尔光束的分布！以及光的自旋和轨道角动量对他的影响！(Bessel beams)

pv module characteristics which depends from ambient temp and irradiance