OFDM-channel-estimation-BER

MATLAB常用函数整理，希望能对MATLAB初学者有所帮助(MATLAB functions used order, hoping to be helpful to MATLAB for beginners)

说明：  是个关于matlab算法比的实验及其实验报告(About matlab algorithm is compared with experiment and lab report)

我自己编写的基于自动细胞机的图像分割算法的源程序，也叫小世界竞争算法。(I have written automated cell-based machine of the source image segmentation algorithms, but also the world叫小competition algorithm.)

一种基于图像内容的分割，该压缩包内含有与该分割方法相关的英文文献，可以好好研究，(effcient Graph-Based Image Segmentation)

COPULA to simulate a speckle pattern

说明：  摘 要 盲图像恢复的主要困难是信息不足，而为了恢复图像和确定点扩散函数需要适当的先验知识。解决这个问题的法、 法以及正则化方法等。但是这些方法的计算量都太大，针对上述方法的不足，文章提出了一种恢复图方法有图像的新算法，它通过恢复残差的最小化和后验概率的最大化来估计参数和恢复图像。其中，巧妙地利用了最陡梯度法和 共轭梯度法的迭代求解。对由于运动造成的模糊图像，可以明显地改善图像的质量，实验结果证明，在对模糊操作没有严格限制的情况下，仍可得到较好的恢复图像。(： : 2$*/<$ I?E L691/6@ F9MM9G:0=@ R9=? S092F 91/DE 6EC=76/=972 9C 92C:MM9G9E2= 92M761/=972$I?9C G/00C M76 L67LE6 92G76L7 （ ） =972 7M/L69769 U27R0EFDE /S7:= =?E 91/DE /2F =?E L792=8CL6E/F M:2G=972 &[ $RE008U27R CL/GE8/F/L=9OE 6ED:0/69</= 1E=?7F /2F 3+ 1E=?7F M76 91/DE 6EC=76/=972 /6E E =E2FEF =7 /FF6ECC =?9C L67S0E1$] 2ER 1E=?7F 9C L67L7CEF =7 6EC= S0:6 91/DE :C92D+5 /2F 5E/C=V:/6EC 1E=?7F$W= :CE 192919<E/G7C= M:2G=972 /2F 1/ 919<E &[ M:2G=972 =7 6EC= =?E 91/DE /2F 9FE2=9M@ =?E L/6/1E=E6C$I?9C 1E=?7F :CE C=EELEC= FECGE2= /2F G72Q:D/=E D6/F9E2= 1E=?7FC =7 192919<E ， G7C= M:2G=972 /2F 1/ 919<E L7C=E69769 L67S/S909=@ =7 91L67OE =?E S0:6 91/DE X?9G? 9C /0C7 =7 91L67OE =?E 91/DE V: =@ 92 C71E FED6EE R9=? 27 C=69G= 0919=/=972$)

FEM solution for microstrip

模型参考自适应 状态完全可测，基于Lyapunov稳定性理论的MRAC法(Model reference adaptive state fully measured, based on Lyapunov stability theory MRAC)

steps - 1. run DigitRecognizer.m 2. mode to run a. Test Mode input pad will open with axes having a red dot. left-click mouse and drag(dont unclick) mouse to draw a numeric digit. if you unclick mouse it won t draw anything. if you want to continue drawing, click again on any red place on axes and start dragging. once done, click submit. it will give you result. b. Training Mode input pad will open with axes having a red dot. draw a number and click submit. when promted, enter the value you drawn. if you wish to continue training, click YES and repeat. if you click No, a feedforward neural network will be trained and saved, you can test it.

带有smith预估器的PID控制 matlab仿真程序(The smith predictor PID control matlab simulation program)