LDPC_check_matrix.tar

examples of rna in matlab. PCA also.

TestPrinter implements TestRunner for Andriod.

current control of permanent magnet linear synchronous motor

fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!. Given the samples of a rayleigh distribution, the PDF parameter is found fits data to the probability of the form: p(r)=r*exp(-r^2/(2*s))/s with parameter: s format: result = fit_ML_rayleigh( x,hAx ) input: x - vector, samples with rayleigh distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields s - fitted parameter CRB - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type- ML

同样的MATLAB 教程 我想对学习MATLAB的人会有帮助的(The same MATLAB Tutorial MATLAB I would like to learn who will help)

分布式MIMO雷达的文献，有需要的，可以共享下(A closed-form expression for false alarm rate o fadaptive MIMO-GLRT detector with distributed MIMO radar)

一个较为广泛的离散小波变换的实现方法，值得新手练习使用。(A more extensive implementation of discrete wavelet transform, worth novice practice use.)

对KMEANS算法进行matlab实现，有数据支持(On KMEANS algorithm matlab realize, there are data to support)

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

异步电机转子磁场定向控制仿真模型，通过验证，好用!(FOC induction motor simulation models, easy to use!)