MATLAB

说明：  用于SAR计算仿真，计算方便快捷，仿真数据全面完整，适合各种类型仿真计算(Used for SAR calculation and simulation, convenient and fast calculation, comprehensive and complete simulation data, suitable for various types of simulation calculation)

首先，你应该确保你的系统中已经建立了交叉编译环境，如果没有或者是还有什么问题可以搜索相关的内容， 本文是教你在嵌入式系统痛中如何移植minigui1.3, 关于2.0版本是付费的版本，跟1.3版本有很大的差别，所以本文的方法只能适合在1.3和1.6的移植当中， 下面开始。。。。。。。。。。。。。。。。。。。。。。。》 -First, you should ensure that your system has established a cross-compiler environment, If not, or is there any problem can search the contents, This article is to teach you in Embedded Systems pain minigui1.3 how to transplant, Version 2.0 of the payment is the version with the 1.3 version of a great difference. Therefore, the method can only be suitable for the 1.3 and 1.6 of the transplant, the following start. . . . . . . . . . . . . . . . . . . . . . . "

说明：  超宽带探地雷达回波形成双曲线，对双曲线灰度图进行matlab仿真，模拟回波图象（自己写的，很水）(The echo of UWB GPR forms hyperbola. The hyperbola gray-scale image is simulated by MATLAB to simulate the echo image)

LDPC码的编译码原理，详细完整，是了解LDPC码基础知识的很好的材料(LDPC code encoding and decoding principles, detailed and complete, is to understand the basics of LDPC codes of good material)

微带滤波器仿真模型，适合于新手学习，建议下载使用。(The simulation model of microstrip filter is suitable for novice learning, and it is recommended to download and use.)

this is a nice web interface for linux systems which runs asterisk

说明：  基于matlab中simulink模块箱的双向dcdc仿真程序(Simulation program of bidirectional dcdcdc based on Simulink module box in MATLAB)

一个简单的通迅录Ｃ++源码，不过很有用，可以值得参考一下。(A simple communication the recorded C++ source, however useful, can be worth considering.)

This ducument contains useful information about stokes hypothesis

说明：  我们描述了所提出的方法对超声（US）信号的压缩多路复用的直接应用。该技术利用压缩多路复用器架构进行信号压缩，并依靠频域中US信号的联合稀疏性进行信号重建。由于换能器元件具有压电特性，因此可以获得有关US信号频率支持的准确先验知识，并且可以在联合稀疏算法中使用。 我们在数值实验中验证了所提出的方法，并显示了它们在秩次缺陷情况下相对于最新方法的优越性。我们还证明，与没有已知支持的重建相比，该技术可显着提高体内颈动脉图像的图像质量。(We describe a direct application of the proposed methods for compressive multiplexing of ultrasound (US) signals. The technique exploits the compressive multiplexer architecture for signal compression and relies on joint-sparsity of US signals in the frequency domain for signal reconstruction. Due to piezo-electric properties of transducer elements, accurate prior knowledge of the frequency support of US signals is available and can be used in joint-sparse algorithms. We validate the proposed methods on numerical experiments and show their superiority against state-of-the-art approaches in rank-defective cases. We also demonstrate that the techniques lead to a significant increase of the image quality on in vivo carotid images compared to reconstruction without known support.)