2d

基于形态学方法的图像分割文件，.m的源代码(Based on morphological image segmentation file,. M of the source code)

拉格朗日动力学方程自动求解：用于串联、并联、混联机械系统拉格朗日动力学方程建模时自动求解方程的系数(automatic solution of Lagrangian equation)

详述了物理层，LTE物理层信道与信号，以及整个物理层的过程。(Details of the LTE physical layer, LTE physical layer channel and the signal, and the entire physical layer process.)

卡尔曼滤波应用于线性预测仿真 MATLAB仿真程序(kalman filter uesed for LP)

说明：  标准粒子群优化算法的示例，程序主体附带大量讲解，简明扼要，适合初学者对粒子群算法结构进行研究(Standard particle swarm optimization example, the program attached to a large number of the main explanations, concise and suitable for beginners on the particle swarm algorithm to study the structure of)

针对混沌参数调制( C P M) 的电力线通信( P L C) 中谐波引起的窄带干扰， 两阶段动态估计方法根据最小 相空间体积( MP S V) 准则估计模型参数， 计算量大。为此， 提出将未知参数合并到增广状态矩阵的联合卡尔曼滤 波方法， 避免了专门的参数估计过程， 在提高增益性能的同时有效降低了计算量。方法的性能通过对混沌电力 线通信下的单音干扰和多音干扰的有效抑制得到了验证。 (For the chaotic parameter modulation (CPM) of the power line communication (PLC) in the narrow-band interference caused by harmonics, two-phase dynamic estimation methods with minimum phase space volume (MP SV) criterion estimate model parameters, calculation of volume. Toward this end, the unknown parameters into augmented state matrix of the joint Kalman filter, to avoid the special parameter estimation process, while improving the performance gain reduces the amount of calculation. Method of performance under the power line communication by chaotic multitone jamming tone interference and the effective suppression has been verified.)

说明：  DE算法 经典的算法，来自于英文文献，适于研究DE算法(Simple DE algorithm )

说明：  快速迭代收缩阈值算法，FISTA用一种更为聪明的办法选择序列{xk}，使得其基于梯度下降思想的迭代过程更加快速地趋近问题函数F(x)的最小值。FISTA的缺点是：Lipschitz常数L(f)不一定可知或者可计算。(Fast iterative contraction threshold algorithm, FISTA uses a more clever method to select the sequence{xk}, making its iterative process based on the gradient descent idea more quickly approach the minimum value of the problem function F(X). The disadvantage of FISTA is that the Lipschitz constant L(f) is not necessarily known or computable.)

基于D-J阈值的加性白噪声方差估计,两种算法的比较(D-J，noise,evaluation)

PSO code matlab psooooooooooooooooo