MATLAB-diaozhi

基于信道的历史信息来预测不同信道的未来可用时间可以帮助CR选择一个最佳信道进行信息传递。不同的预测准则应用到周期或是随机的开关模式中。一个CR可以学习以往不同信道的模式。我们提出一个简单的分类和学习方法去检测模式的类型和收集需要的信息用于智能信道的选择。MATLAB仿真结果显示提出的方案在随机信道的随机和周期模式中都有优越的表现。随着时间的变化，新到的切换次数减少到55 ，并且延迟时间也相应减少，而吞吐量却在提高。(Prediction of future availability times of different channels based on history information helps a cognitive radio (CR) to select the best channels for control and data transmission. Different prediction rules apply to periodic and stochastic ON-OFF patterns. A CR can learn the patterns in different channels over time. We propose a simple classification and learning method to detect the pattern type and to gather the needed information for intelligent channel selection. Matlab simulations show that the proposed method outperforms opportunistic random channel selection both with stochastic and periodic channel patterns. The amount of channel switches needed over time reduces up to 55 , which reduces also the delay and increases the throughput.)

基于正交分量的OMP稀疏分解参考程序，要求分解信号分量具有正交性(Sparse orthogonal decomposition OMP component reference procedure that requires the signal components with the orthogonal decomposition)

说明：  MatlabGUI太阳辐射定标数据处理平台设计solar radiation data (MatlabGUI calibration of solar radiation data processing platform)

涵盖四种绘制三维图的方法，适合初学者，供参考(this zip consists of four methods for drawing 3D maps)

模糊pid仿真，先运行模糊推理系统设计程序a.m，并调入内存，然后运行模糊控制程序b.m,对pid控制参数进行整定。(Pid fuzzy simulation, Fuzzy Inference System to run the design process am, and transferred to memory, and then run the procedure of fuzzy control bm, of pid control tuning parameters.)

C/C++环境下BPSK调制信号在高斯信道下的性能仿真(BPSK modulation signal performance simulation in the Gaussian channel under C/C++ environment)

采用最小二乘逼近作为拟合实验数据的方法,利用F检验,确定实验数据拟合优度及最佳阶数,用编制的程序来拟合实验数据,得到了较好的结果(Least-squares fitting)

This file contains Least Square method program which is one of en bloc approaches to identifying a system. The target is calculating parameter vector of a system

SAR图像变化检测,可以对比同一地点不是时间的SAR图像变换，并聚类分析(SAR image change detection, you can compare the same place time of SAR image transformation and cluster analysis)

根据matlab的bvp4c函数的例子思想方法，求解特征值和特征函数，可以解变积分边界的问题，但是须给一个比较精确的初特征值。此为自编程序，已经标明注释。所附为bvp4c相关例子（此从matlab帮助文件节选）。(use the matlab solver bvp4c to obtain the both eigenvalues and eigenfunctions of BVPs, an exact initial eigenvalue is needed.)