medfilt2m

用Matlab实现的图像操作基本算子，实现的比较简单，欢迎大家支持(Matlab implementation of image manipulation with the basic operator)

In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete introductory discussion can be found in [Sorenson70], which also contains some interesting historical narrative.(In 1960, R. E. Kalman published his famous paper describ ing a recursive solution to the discretedata li near filtering problem [Kalman60]. Since that time, due in large part to advances in digital computi Vi, the Kalman filter has been the subject of extens ive research and application. particularly in the area of autonomous or assis ted navigation. A very "friendly" introductio n to the general idea of the Kalman filter can be f ound in Chapter 1 of [Maybeck79] while a more complete introductory discussion can be found in [Sorenson70] which also contains some interesting historic al narrative.)

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)

这种邻域插值的matlab源代码,学生需要可以下载使用(This neighborhood interpolation of matlab source code, students can download to use )

OFDM simulation, demodulation

自己建立的park变换模块，根据TI公司永磁电动机例程编写(park transform model created by myself,based on TI s permanent magnet motor routines)

说明：  详细的介绍用Matlab处理数字信号的方法(Detailed introduction of digital signal processing using Matlab method)

给出了基于MGA算法和SGA算法的结果比较，得到所要求的函数优化结果。(MGA algorithm is given based on comparison of the results and SGA algorithms, function optimization to get the required result.)

图像的双边滤波增强算法，效果不错 欢迎大家试用！(Image enhancement by bilateral )

利用matlab模拟光纤中的HE11模的模式分布图。(Using matlab to simulate the HE11 mode fiber mode distribution.)