Band-QPSK-ber-simulation

说明：  采用面向对象的基本思想,MATLAB/SIMULINK环境下,开发出一个基于MATLAB的化工单元操作工具箱(ChET)并以此工具箱为基础进行了化工过程模拟的尝试。(Adopt the basic idea of object-oriented, MATLAB/SIMULINK environment, the development of a MATLAB-based toolbox of chemical unit operation (ChET) and to the toolbox as the basis for a chemical process simulation experiment.)

一维的求根多重信号分类算法Root-MUSIC，在matlab环境下实现(One-dimensional root finding multiple signal classification algorithm Root-MUSIC, in the matlab environment to achieve)

matlab code for machine learn duda

matlab用于导波光学中平板波导传播模式求解拟合程序(matlab for guided wave optics, planar waveguide propagation model for the fitting procedure)

QAM 4,16,64 OFDM DC useful

粒子群算法Griewankan实现寻优，利用一具体案例得出寻优结果(Particle swarm optimization algorithm Griewankan realized using a specific case optimization results obtained)

从曲线中检测到其峰值：先利用二次求导得到所有凸点，设置门限，去除过低的凸点，然后利用滑动窗的方法，在凸点中求得满足峰值要求的点(Detected from the curve to its peak: the first use of the second derivative method to get all the bumps, set the threshold too low to remove the bumps, and then use a sliding window, obtained in a bump to meet peak requirements of point)

TD-SCDMA小区搜索最为关键的sync-dl码同步的确定过程，即搜索DwPTS。(TD-SCDMA cell search of the most critical sync-dl code synchronization process of determining that the search DwPTS.)

说明：  k均值算法，社区划分算法中经典算法，WSN中分簇也可使用该算法。(K-means algorithm, classic algorithms in community partition algorithm, clustering can also use this algorithm in the WSN.)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。 BP（Back Propagation）神经网络是1986年由Rumelhart和McCelland为首的科学家小组提出，是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hidden layer)和输出层(output layer)。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm. BP (Back Propagation) neural network is a 1986 team of scientists headed by Rumelhart and McC)