PFD50

matlab解线性方程组的直接法程序，里面包括了常用的matlab解线性方程组的直接法程序，包括手写的和matlab自还的函数。(matlab solving linear equations of the direct method procedures, which includes the commonly used matlab solving linear equations of the direct method procedures, including hand-written and self is also a function of matlab.)

本程序包里面代码用matlab编写，有三个demo，分别处理然后用CS重建1维，2维信号，最后一个是对大脑图像做CS重建对比(This package inside the code written in matlab, there are three the demo, be treated separately and then use the CS reconstruction of one-dimensional, two-dimensional signal, the last CS reconstruction compared brain images)

根据Lucas的论文建立偏微分的模型 并且求解PDE 该PDEs描述了固液分离的萃取过程(Lucas papers, the partial differential model and solve the PDE PDEs to describe the extraction process of the solid-liquid separation of)

参考文献《外辐射源定位跟踪技术的研究》(两步加权最小二乘法)以及 《a simple and efficient estimator for hyperbolic location》对Chan算法进行仿真；认定基站数目为5个； (The Chan algorithm in the TDOA location based on the CDMA cell network)

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.

Computers as components

this is gabor technique

两个16个阵元的平面阵波束形成。很好用的(16 element array of two plane array beamforming. Very good use)

Sugeno-type FIS output tuning

k-nearest neighbor algorithm