make_lidar_image

THE FASTEST WAY TO SORT N NUMBERS sortN library

说明：  模拟退火处理tsp问题，matlab 代码(tsp problem matlab code)

可以实现Gabor变换，其中包含了采用C语言和Matlab两种工具实现(can achieve Gabor transform, which contains the C language and tools to achieve both Matlab)

基于matlab的7-4线性分组器设计，简单易懂，有界面(7-4 matlab-based linear block design, easy to understand, interface)

使用MATLAB语言实现[0,1]随机序列的游程检验(Using the MATLAB language implementation [0,1] random sequence runs test)

charge pump phase-locked loop with digital phase-frequency detector(charge pump phase-locked loop with digital phase-frequency detector matalab model)

自适应信号处理基础知识，数字信号处理必备(Basic knowledge of adaptive signal processing, digital signal processing (DSP) necessary)

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.)

光谱匹配识别基本算法，包括SA、SCF、SCM、SCA等基本算法。程序可以直接调用，方便简洁。(Spectral matching to identify the basic algorithms, including SA, SCF, SCM, SCA and other basic algorithms. Program can be called directly, convenient and simple.)

使用K近邻算法分类的代码，可返回分类的识别率(KNN Classification)