comm_eg

运用MATLAB语言，构造了.bmp文件，其中包含了黑白，256色以及真彩图片，加强了对于 .bmp文件的理解，及MATLAB语言对于文件的读写(The use of MATLAB language, is constructed. Bmp file, which contains black and white, 256-color and true color images, enhanced for. Bmp files to understand, and the MATLAB language for the document to read and write)

selective mapping as a reduction technique for PAPR in OFDM systems

四叉树编码和测试的RGB图像解码方案，在matlab7.0中验证可行(Quadtree coding and testing of the RGB image decoding program, verify possible in matlab7.0)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

卡尔曼滤波 雷达对多维目标进行跟踪 并对装填方程进行预测 是入门的良好代码(Kalman filtering of radar target tracking and multi-dimensional equations to predict filling is good code entry)

This program is used for filtering and editing of image

gridd connected pv systems

图像分割的，cv水平集模型的matlab算法(Level Set cv)

M序列信号算法仿真在系统辨识中有着很大的应用前景。多谐差相方法辨识精度很高有着很苛刻的要求，要求已知辨识参数个数已知并且需要整周截断。而M序列信号的测试方法没有这个方面的要求。其辨识未知模型时，可以用最小二乘算法观察辨识系统的精度来确定模型的阶次。本算法里面不但给出了用于M序列生成的本原多项式计算方法，同时编写了M序列信号的生成算法，并编写了相关辨识方法的算法。(M sequence signal simulation algorithm for identification in the system have great application prospects. Identification of multi-harmonic differential phase method with high precision has very stringent requirements, demand parameters are known to identify the number of known and need to cut off the whole week. The M sequence signal testing methods do not have this requirements. Its identification unknown model, you can observe the identification system using least-squares algorithm to determine the accuracy of the model order times. This algorithm is used which not only gives the M sequence generated by primitive polynomial method of calculation as well as prepare the M sequence signal generation algorithm, and the preparation of the relevant identification method algorithms.)

MATLAB潮流计算(MATLAB flow calculation)