IEC_sc

多种数学迭代方法，包括雅克比法、高斯-赛德尔迭代法、和广义理查德森迭代法。(A variety of mathematical iterative methods, including Jacobi method, Gauss- Seidel iterative method, and the generalized Richardson iterative methods.)

matlab, document how to use matlab

介绍matlab 的使用，以及数字信号处理，图像处理，还有通信系统(this is introduction about the matlab, digital signal process ,and digital picture process)

说明：  power flow forward backward

<matlab在电子信息中的应用>一书中个章节的配套源代码。(1 )

GMDH_main为GMDH主函数； variable_Combin为输入层初始变量选为x1,x1^2,x1*x2,x2^2,x2时的输入变量矩阵值 variable_select计算X_train训练输入数据,Y_train训练输出数据,X_test测试输入数据,Y_test测试输出数据 Combin为求变量的两两组合 Sym_Combin为求符号变量的两两组合 PE_AIC求每层各神经元的参数估计W，及训练数据在参数估计后估计的输出out_train，测试数据在参数估计后的估计输出out_test，还有与实际比较的误差平方和PESS， 以及准则值AIC sym_representation求最终的输入输出符号表达式 Criterion_value求准则值 (GMDH_main main function for the GMDH variable_Combin initial variables chosen for the input layer, x1, x1 ^ 2, x1* x2, x2 ^ 2, x2 the value of the input variable matrix calculation X_train variable_select training input data, Y_train training output data, X_test test input data, Y_test for the sake of the test output data Combin pairwise combination of variables for the sake of symbolic variables Sym_Combin pairwise combinations PE_AIC neurons find each parameter estimation of the W, and after the training data is estimated in the estimation of output out_train, test data After the parameter estimates of the output estimated out_test, also compared with the actual sum of squared errors PESS, as well as the final criterion value AIC sym_representation seek the input and output values ​ ​ of symbolic expressions Criterion_value find criteria)

该算法是以粒子群中粒子的收敛特性为基础,依据量子物理理论提出的,改变了传统粒子群算法的搜索策略,可使粒子在整个可行解空间中搜索寻求全局最优解。同时该算法的进化方程中不需要速度向量,而且进化方程的形式更简单,参数较少且容易控制。对两个算例进行仿真测试,证实该算法可有效解决经济负荷分配问题 性能对比显示,该算法求得的解优于已有的改进粒子群算法及其它优化算法所求得的解。(The algorithm is based on convergence particle swarm particle basis, according to the theory of quantum physics, particle swarm algorithm has changed the traditional search strategies, allow the particles throughout the feasible solution space search seek the global optimal solution. Meanwhile, the algorithm does not need velocity vector evolution equations, and evolution equations simpler and less parameters and easy to control. Two examples of simulation tests confirmed that the algorithm can effectively solve the economic load allocation performance comparison shows that the algorithm is superior to existing solutions obtained improved PSO algorithm and other optimization algorithms obtained solution.)

QAM调制与解调——包含了多种多进制的正交调制与解调(QAM modulation and demodulation- contains a variety of M-ary orthogonal modulation and demodulation)

小世界网络模型代码，可以求出邻接矩阵，度和度分布(Small world network model code, you can find the adjacency matrix, degree and degree distribution)

Restauration virtuelle de l’art pariétal paléolithique le cas de la grotte de Marsoulas