band_PC

有关OFDM时域和频域同步的硬件实现，在FPGA,DSP和ASIC上实现，并做了对比。(On the OFDM time domain and frequency domain synchronization hardware implementation, in the FPGA, DSP and ASIC to achieve, and has done a comparison.)

simulink real-time workshop for dragon12 development board from (simulink real-time workshop for dragon12 development board from)

matlab 批量读DBF文件，非常好用，需要下载一个dbfread函数文件(matlab batch read DBF files, very easy to use, need to download a dbfread function file)

代码实现了最小均方差和迫零均衡器的误码率仿真图，并且通过对比理论曲线，验证了代码的正确性。(Code implements the MMSE and zero forcing equalizer BER simulation diagram, and by comparing the theoretical curves to verify the correctness of the code.)

它主要介绍了独立分量分析法的步骤以及matlab实现所调用的函数。还有一些例子。(It mainly covers the steps and independent component analysis method to achieve the matlab function call. There are also examples.)

matlab最优化程序在数学建模中的应用教程(matlab optimization program in the application of mathematical modeling tutorial)

可以用来求相应图的强连通分支，属于图论组合数学上的算法编程题(a programing of combinatoral optimation optimization)

stbc alamouti code with all modulation scheme

Code to obtain the filtering function polynomials F(s), E(s) and P(s), and the constants eps and eps_r from transmission zeros, with Cameron s method.

A Novel Image Reconstruction Algorithm Based on Concatenated Dictionary This paper presents a novel method for image reconstruction, which decomposites the image by concatenating a redundant dictionary of several bases and then reconstruct the image efficiently by means of Matching Pursuit algorithm. The proposed method constructs the concatenated dictionary with cosine bases, wavelet bases and contourlet bases, which will lead to a better approximation of the original image. The experimental results show that the proposed algorithm can greatly reduce the computational complexity and generate a better reconstruction effect compared with previous methods.(A Novel Image Reconstruction Algorithm Based on Concatenated Dictionary This paper presents a novel method for image reconstruction, which decomposites the image by concatenating a redundant dictionary of several bases and then reconstruct the image efficiently by means of Matching Pursuit algorithm. The proposed method constructs the concatenated dictionary with cosine bases, wavelet bases and contourlet bases, which will lead to a better approximation of the original image. The experimental results show that the proposed algorithm can greatly reduce the computational complexity and generate a better reconstruction effect compared with previous methods.)