sigsys2

行尺度主元高斯消元法，算法由两部分组成，分解阶段和求解阶段(OK-scale principal component Gaussian elimination method, the algorithm consists of two parts, decomposition stage and the solution phase)

基于matlab的灰色预测的代码大全，能够实现不同的灰度预测结果，有利于初学者对灰度预测的把握，有利于学习练习和应用(Different gray forecast results can be achieved based on gray prediction matlab code Daquan, help beginners grasp grayscale forecast is conducive to learning exercises and applications)

说明：  关于matlab基带msk调制的理解，并加之载波，并用GUI界面实现测试(msk test based on matlab)

说明：  遗传算法包括基本算法的程序及其在优化函数方面的应用(genetic algorithms include basic algorithm for the optimization process and its function in the application)

《智能控制》第一版（刘金琨著）第五章程序源码(" Intelligent control" the first edition (Liu Jinkun a) Chapter V program source)

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)

利用时域有限差分法对基于表面等离子体的天线进行模拟(Use of finite difference time domain simulation method based on surface plasmon antenna)

it s a sample for initiaiton to matlab

Variable Neiborhood PSO Algorithm

对角加载波束形成算法，包含信噪比以及信干噪比的仿真图(Diagonally loaded beamforming algorithm, including simulation diagrams of signal-to-noise ratio and signal-to-interference-to-noise ratio)