RKF78_2

EBMA and HBMA using MATLAB

日常开支记录器,能够满足日常的记账需求，很不错的小软件(Daily expenses recorder, able to meet the daily accounting needs of a very good small software)

用历史日成交量去预测今日成交量的统计分析~~~~~~~~~~~~~~~~~~~~~~~~~~~~~(statistic of history turnover volume)

Introduction to the Issue on Cooperative Communication and Signal Processing in Cognitive Radio Systems

teaching image processing with matlab program

说明：  1. 应用window的moveTo和moveBy编写一程序实现窗口的移动和定位(1. Application window of the moveTo and moveBy write a program to achieve the movement and positioning of the window)

说明：  介绍了二级倒立摆的建模，并结合极点配置方法和LQR方法进行了仿真，有详细的过程。(Introduced the double inverted pendulum modeling, combined with pole placement method and LQR method of simulation, a detailed process.)

Demonstration of Bisection Root Finding of a functiony

根据所点击选择的三个点，进行自动画圆的程序。(Click to select the three points, the program automatically draw a circle.)

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)