KODE-DCT-SVD-WATERMARK

A novel algorithm for sparse approximation in redundant dictionaries, called the M-Term Pursuit (MTP). This algorithm decomposes a signal into a linear combination of atoms that are selected in order to represent the main signal components.

说明：  贝叶斯压缩感知 用于稀疏信号重建，基于贝叶斯理论(Adaptive compressive sensing, Bayesian model selection, compressive sensing (CS), experimental design, relevance vector machine (RVM), sparse Bayesian learning.)

Using BPSK modulation scheme,in MIMO system, alamouti code & both OSTB code for a rayleigh fading channel . for 2*1, 2*2, for 4*4, for 8*8

求解常微分方程组的bvp解算器的使用说明和教程和实例(tutorial and documentary and examples for ODE bvp)

Data Clustering with Normalized Cuts

说明：  单向感应电动机的仿真模型，内有7个仿真文件。具体实现功能和仿真结果图文件夹里有一个PPT文件进行讲解。(One-way induction motor simulation models, there are seven simulation files. Concrete realization of functional and simulation results map folder there is a PPT file to explain.)

A.2 Open Image Files This function looks for x-ray images (.tif) in directory ‘dname’ and creates a movie of I(q) versus q and saves the corresponding 3D matrix. ‘TempA’ and ‘TempB’ are the slope and y-intercept of the ramp temperature profile, respectively. Variables ‘timeA’ and ‘timeB’ are the slope and y-intercept of the time dependence on the frame number. ‘IC1A’ and ‘IC1B’ are the slope and y-intercept of the IC1 value (prior to sample) dependence on the frame number. It load background matrices ‘B’ which should be double-format and corrected for IC1 and any difference for acquisition time. This function calls radialintegrationBNL A.4 Lorentz Correction This function creates and saves the Lorentz-corrected intensity matrix calculated the intensity matrix created in A.2. It also saves each frame as a separate ascii file for crystallinity uation in Origin or other software.

展示了HSPA系统中PDSCH信道的基本测试以及CQI测试的基本参数和过程(HSPA system shows the basic test PDSCH channel and the CQI process of testing the basic parameters and)

model predictive control lmi tutorial

A Rayleigh distribution is often observed when the overall magnitude of a vector is related to its directional components.