Analog-modulation

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$)

这是梅林矩的MATLAB源代码,代码质量较好,可供研究图像图形处理和水印技术方面的朋友参考!(This is the Mellin moments of MATLAB source code, source better quality for the study of image and graphics processing and technical aspects watermark friends reference!)

code for Pegasis protocol in wireless sensor network wsn

鲁棒的典型性分析方法仿真程序，亲测程序可用(Robust analysis method simulation program)

分别用改进的Euler方法和四阶Runge-Kutta方法求解。 (Were improved Euler method and fourth-order Runge-Kutta method.)

说明：  精通matlab综合辅导与指南，详细介绍了Matlab的操作与编程。(proficient Matlab comprehensive counseling and guidance, details of the operation and Matlab programming.)

matlab 详细说明书，学习matlab的好帮手，包括内容，常用函数，语音信号分析，进阶的绘图功能 频道滤波 等(Matlab detailed brochures, learning Matlab's helping hands, including the contents of commonly used functions, Voice Signal Analysis, advanced mapping functions such as channel filtering)

this is chapter 2 this is chapter number 2

直接序列扩频通信系统仿真程序，使用matlab语言设计的程序。(direct sequence spread spectrum communication system simulation, the use of Matlab language design process.)

An ad-hoc network with a sender, a destination and a third station act- ing as a relay is analysed. The channels are modelled containing thermal noise, Rayleigh fading and path loss. Di® erent combining methods and di- versity protocols are compared. The amplify and forward protocol shows a better performance than the decode and forward protocol, unless an error correcting code is simulated. To combine the incoming signals the chan- nel quality should be estimated as well as possible. Information about the average quality shows nice bene¯ ts, and a rough approximation about the variation of the channel quality increases the performance even more.