chap3

Linear regression with regularization

This code is a solution for TSP problem with tabu search.

冈萨雷斯数字图像处理MATLAB版m代码源码(Gonzalez Digital Image Processing MATLAB source code version )

电力线通信是现在家用通信的一种，在PLC通信的研究中，对信道的研究是至关重要的。改代码主要包括多径信道和噪声模型matlab代码，是目前最常用的模型。(Power line communication is now a kind of home communication, in the PLC communication research, the channel research is essential. Change the code mainly include multipath channel and noise model matlab code, is the most commonly used model.)

仿真程序模拟产生理想点目标的回波，并采用频域相关方法（以便利用FFT）实现脉冲压缩。(Simulation program simulated the ideal point target echo, and the use of frequency-domain correlation method (to take advantage of FFT) to achieve pulse compression.)

right shift and info

测试可以跑，根据自己情况修改下函数即可. NSGA-III 首先定义一组参考点。然后随机生成含有 N 个（原文献说最好与参考点个数相同）个体的初始种群，其中 N 是种群大小。接下来，算法进行迭代直至终止条件满足。在第 t 代，算法在当前种群 Pt的基础上，通过随机选择，模拟两点交叉（Simulated Binary Crossover，SBX）和多项式变异 产生子代种群 Qt。Pt和 Qt的大小均为 N。因此，两个种群 Pt和 Qt合并会形成种群大小为 2N 的新的种群 Rt=Pt∪Qt。 为了从种群 Rt中选择最好的 N 个解进入下一代，首先利用基于Pareto支配的非支配排序将 Rt分为若干不同的非支配层（F1，F2等等）。然后，算法构建一个新的种群St，构建方法是从 F1开始，逐次将各非支配层的解加入到 St，直至 St的大小等于 N，或首次大于 N。假设最后可以接受的非支配层是 L层，那么在 L+ 1 层以及之后的那些解就被丢弃掉了，且 St FL中的解已经确定被选择作为 Pt+1中的解。Pt+1中余下的个体需要从 FL中选取，选择的依据是要使种群在目标空间中具有理想的多样性。(The test can run and modify the function according to its own situation. NSGA-III first defines a set of reference points. Then the initial population containing N individuals (preferably the same number of reference points as the original literature) was randomly generated, where N was the size of the population. Next, the algorithm is iterated until the termination condition is satisfied. On the basis of current population Pt, the algorithm simulates two-point crossover (SBX) and polynomial mutation to produce offspring population Qt by random selection.)

这是一个OFDM系统的信道估计仿真MATLAB，分析了基于训练序列的估计方法(This is an OFDM system channel estimation simulation MATLAB, analysis of the estimation method based on training sequence)

enhanced mapping algorith for loclaization and mapping problem

Mixed-Excitation Linear Predictive Coder - MELP codec demonstration