apolloeq

有限差分法解二维电场，里面有正方形，矩形，正六边形以及二维无限场域问题(Finite difference method solution of two-dimensional electric field, which has a square, rectangle, regular hexagon, as well as infinite two-dimensional field problems)

可以在matlab上点击，获得点击的坐标值(failed to translate)

neural network based speech detection

BP学习算法应用——模式分类 应用动量BP学习算法对UCI提供的经典数据库——鸢尾属植物数据库进行分类，速度快，精度高。iris.arff为数据库文件，可用Weka数据挖掘软件打开。Iris.csv为源代码读取的数据文件，通过Weka软件转换得到。 将源文件Iris_classify.m和Iris.csv文件放入matlab的work文件夹中直接运行即可。(BP learning algorithm applications- the application of pattern classification momentum BP learning algorithm to provide a classic UCI database- iris database classification, high speed and accuracy. iris.arff for the database file that can be used to open Weka data mining software. Iris.csv for the source code to read the data files have been converted through Weka software. Iris_classify.m the source document and document Iris.csv Add matlab folder of work can be directly run.)

不同频率正弦信号产生，可用于生成DDS中的ROM(Sinusoidal signals of different frequencies generated can be used to generate the ROM DDS)

正确率可以达到98％，利用matlab写成的窄带噪声发生，使用高阶累积量对MPSK信号进行调制识别。( Accuracy can reach 98 , Using matlab written narrowband noise occurs, Using high-order cumulants of MPSK signal modulation recognition.)

用线性插值法求单摆运动周期的近似解,及做图比较.(Find by linear interpolation of the approximate solution pendulum movement cycle, and do Charts.)

This program is desiged to evaluate the space-frequency codes According to our desgn criteria for space-frequency codes used in OFDM system

运用星座图重排策略的HARQ方案，与chhase combined 方案的比较仿真 (Using constellation rearrangement strategy HARQ scheme, comparing simulation program chhase combined)

说明：  差分进化算法(Differential Evolution Algorithm，DE)是一种高效的全局优化算法。它也是基于群体的启发式搜索算法，群中的每个个体对应一个解向量。差分进化算法的进化流程则与遗传算法非常类似，都包括变异、杂交和选择操作，但这些操作的具体定义与遗传算法有所不同(Differential evolution algorithm (DE) is an efficient global optimization algorithm. It is also a heuristic search algorithm based on population. Each individual in the group corresponds to a solution vector. The evolution process of differential evolution algorithm is very similar to genetic algorithm, including mutation, hybridization and selection operations, but the specific definition of these operations is different from that of genetic algorithm)