D 生成泽尼克多项式的matlab代码

本程序实现了matlab与VC++的混合编程。主要实现了基本的matlab处理的一些功能。但方法比较重要，很有用处(A combined way of matlab and VC++ was realized and it is used to process the basic function of matlab. It is an important approaches.)

QPSK Transmitter and I/Q Correlator Receiver is based on the technique of queing the information in a bit stream and on the receving end using FFT and some additive filters, as the addition of noise is made to infuse the need of a filter. Necessarily a Baseband filter is used. Modulation acheived at the receiving end. (QPSK Transmitter and I/Q Correlator Recei ver is based on the technique of the infor queing mation in a bit stream and on the receving end usi ng FFT and some additive filters, as the addition of noise is made to infuse the nee d of a filter. Necessarily a Baseband filter is u sed. Modulation achieved at the receiving end.)

fusion of panchromatic and multispecral image using differet types of image fusion techniques

热泵机组运行时，作为四大件之一的压缩机计算模型(Operation of the heat pump units, as one of the big four calculation model of compressor)

最优化方法中的非线性规划的powell方法的matlab实现，可支持多维的参数，自己修改即可。(optimization of the nonlinear programming method of Matlab Powell realized, support multidimensional parameter can change themselves.)

说明：  根据turbo编码器的生成多项式对输入信息进行编码(turbo encoder)

可以对光子晶体光纤的光强分布仿真，极为有效(The light of the photonic crystal fiber distributed simulation, extremely effective)

state space model for induction machiine

全变差图像处理Matlab程序，for the paper: "Algorithms and Software for Total Variation Image Reconstruction via First-Order Methods, Numerical Algorithms"(Software for Total Variation Image Reconstruction (for Matlab Version 7.5 or later) "mxTV" is a software package for image reconstruction based on the Total Variation model, and including denoising, inpainting, and deblurring. The work was carried out as part of the project CSI: Computational Science in Imaging, funded by the Danish Research Council for Technology and Production Sciences, and headed by Prof. Per Christian Hansen, DTU Informatics. The collaborators are DTU Informatics, Dept. of Electronic Systems at Aalborg University, and MOSEK ApS. The underlying algorithms are based on recently published first-order methods developed by Nesterov, tailored specifically to the image restoration problems. These methods have O(1/ε) complexity, where ε is the accuracy of the solution. The core computational routines are written in C, with a mex interface to Matlab. The algorithms and the software are described in the paper: J. Dahl, P. C. Hansen, S. H. Jensen, and T. L. Jensen, Alg)

分别利用EMD和小波进行降噪，并进行对比分析，内附经典论文。(Were carried out using the EMD and wavelet noise reduction, and a comparative analysis, containing classic papers.)