Mechanical-Design-Analysis-AAD

舰载雷达海杂波背景下动目标检测，很不错，自己编写的，非常有用。(jianzaileida)

说明：  计算方法的上机编程题，计算方法的上机编程题。计算方法的上机编程题(Method of calculation-on programming problems, the calculation-on programming problems. Programming-on method of calculation problems)

matlab for communication

matlab离散信号时域分析，和频域分析实例，适合基础者使用。（来源课堂个人实验）(Matlab discrete time-domain signal analysis and frequency domain analysis of the examples, the use of suitable infrastructure. (Source individual classroom experiment))

code for jack knifing

采用matlab解微分方程，讲解比较详细，值得看看(Using matlab for solving differential equations, to explain in more detail, is worth a look)

测量稀土元素的光谱的matlab程序,可以作图，十分简单方便(REE spectra measurements matlab program, you can plot is very simple and convenient)

BP神经网络容易陷于局部极小值，PSO算法在无约束非线性函数优化方面性能优越，通常可以直接找寻到全局最优解，即使不能搜多到全局最优解，也距离全局最优点不远。当然，基本PSO算法陷入局部极值也是有的。对于这个缺点目前还没有找到比较有效、省市的解决方案。本案例实现利用PSO算法和BP算法共同训练神经网络，先将网络进行PSO算法训练，然后BP算法接着进行小范围精细搜索，PSO算法训练神经网络的本质就是将输出误差函数（即能量函数）看成目标函数，PSO对能量函数进行全局寻找最小值。(BP neural networks are prone to local minimum values. The PS algorithm has superior performance in the optimization of unconstrained nonlinear functions. It can usually find the global optimal solution directly. Even if it can not find more global optimal solutions, it is not far from the global best. Of course, there is also a local extreme of the basic PO algorithm. For this shortcoming, there is no more effective, provincial and municipal solution. This case realizes the use of the SO algorithm and the BP algorithm to train the neural network. First, the network is trained in the SO algorithm, and then the BP algorithm is followed by a small range of fine searches. The essence of the PO algorithm training neural network is to regard the output error function(ie, the energy function) as the objective function, and the PO seeks a global minimum value for the energy function.)

计算成组滑动的滑窗检测器的最佳门限已知: 击中数N = 128, 组宽n = 8，PF = 10¡ 6，PD = 90 假设以下条件: (a) 信号不起伏 (b) 忽略天线波束调制 1 (c) 计算PD时忽略目标区以外噪声的影响 组门限(第二门限)为K=8 滑窗的门限(第三门限)为L=16 (滑窗中包含的组数为16) 求解: 最佳的KOPT 和LOPT，对这题做了具体仿真实现。需要的朋友，一定知道很有用。(Optimal threshold calculated as group slidable window detector is known: hit number N = 128, the group width n = 8, PF = 106, PD = 90 assuming the following conditions: (a) signal is not undulation ( b) ignore the antenna beam modulation 1 (c) the calculation of PD ignored outside the target area noise of impact group door limit (the second door limit) for K = 8 sliding window of the door limit (third door limit) for L = 16 (sliding window contains group 16) to solve: the best of the KOPT the LOPT, these questions do specific simulation to achieve. A friend in need, we must know to be useful.)

说明：  k-means算法实现以及Iris数据集(Implementation of K-means algorithm and Iris data set)