资源列表
polynomial_multiply_divide
- 用于多项式算法的乘法和除法，在数字信号处理中有很好的实用价值。-The program used for digital signal processing polynomial multiply and divide,it s the good references.
8745123132
- HIGHLIGHT TRUE #define NOHIGHLIGHT FALSE #define UPDATE TRUE #define NOUPDATE FALSE #define FORMAT TRUE #define NOFORMAT FALSE #define LEFT 0-HIGHLIGHT # define NOHIGHLIGHT TRUE FALSE UPDATE # define TRUE # # define FALSE de NOUPDATE fine
RobotSimulate
- 给定机器人臂长和关节角度,确定机器人在空间中的位置和姿态.-Given the robot arm length and joint angles to determine the position of the robot in space and orientation.
BF_phaseshift
- 数字波束形成技术，本文提供常规相移方法产生波束的技术-beam forming
romp
- 正则化正交匹配追踪算法的函数，用matlab编写，可以求解压缩感知的信号重构问题-Regularization function orthogonal matching pursuit algorithm, using matlab prepared, can solve problems compressed sensing signal reconstruction
ANNs
- 对BP神经网络进行训练然后预测，并绘制相应的误差图，计算命中率-BP neural network was trained and then predict and draw the corresponding error maps, calculate hit rate
rbf
- 多输入多输出的rbf神经网络，可以仿真出结果。-Multiple input multiple output of the RBF neural network, can the simulation results
pso_bp
- pso算法从随机解出发，通过迭代寻找最优解，通过适应度来评价解的品质，粒子群优化Bp网络源程序，仅供参考-pso algorithm random solutions, through iterative find the optimal solution, quality, particle swarm to uate the fitness solution by optimizing Bp network source code, for reference only
rbf_nn
- 類神經網路的RBF這對於任何研究都非常之友幫助歡迎下載內有說明-The RBF neural network for any research to help the Friends are welcome to download, there are notes
FLch6eg2
- 采用基于遗传算法的神经网络学习非线性函数。目标函数为：yp=1-exp(-i/2).-Genetic algorithm-based neural network learning of nonlinear functions. The objective function as: yp = 1-exp (-i/2).
TSP-simulated-annealing-algorithm
- 模拟退火算法是领域随机搜索算法的一种改进——加入概率接受准则，是十分简单的一种智能优化算法，本源码是用于求解TSP问题的模拟退火算法源程序-The simulated annealing algorithm is random search algorithm of field an improved-join probability accept criterion, it is very simple a kind of intelligent optimization algorithm,
ANN
- 用两层神经网络实现的分类器，一个小demo,随机产生数据并分类-Neural network of two layers is used to implement data classifier, a small demo