PQchaoliuchengxu

sift的matlab代码，是最新的，效果很不错，大家可以(sift the matlab code, is the latest, the effect is pretty good, we can)

this is image filter design

This package implements fast compressed sensing using structurally random matrices (SRM) described in [1] and [2]. As the package is still under development any comments or bug reports are highly welcome.

绘制二维非线性系统的相图，MATLAB程序，自已编写，多多交流！(Phase diagram, drawing two-dimensional nonlinear system MATLAB program, written, more exchanges!)

this gives the basic idea on the placement of capacitor in distribution system.the allocation of capacitor reduces the power losses in the system.

律u律pcm编码 若输入A律PCM编码器的正弦信号为x(t)=sin(1600πt),采样序列为x(n)=sin(0.2πn),n=0,1,2,…,10，将其进行PCM编码，求出编码器的输出码组序列y(n)。 要求：1) 直接采用A律扩展器函数求解上述问题。 2）使用13折线法近似A律PCM 求解上述问题。 3）计算量化误差。(Law a law pcm coding If the input A-law PCM encoder is sinusoidal signal x (t) = sin (1600πt), for the sample sequence x (n) = sin (0.2πn), n = 0,1,2, ..., 10, it will be PCM coding to obtain the coded output code group sequence y (n). Requirements: 1) directly A-law expander function to solve the above problems. 2) using a 13 fold line approximation A-law PCM to solve the above problems. 3) calculating the quantization error.)

捷联惯性导航系统滤波程序，matlab源代码(Strapdown inertial navigation system, filtering procedures, Matlab source code)

16 进制QAM信号的GARDNER算法定时同步(timing Synchronize for16 QAM)

电扫阵列的Matlab建模与仿真，电扫阵列具有波束方向可控、扫描灵活、增益高的优势。(Electronically Scanned Arrays MATLAB Modeling and Simulation,Electronically scanned arrays (ESAs) provide the capability of commandable,agile,high-gain beams.)

汽车高斯曲面拟合 --- 2程序，以适应到表面二维高斯： 子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的 这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。 autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。 autoGaussianSurfGS（十一，彝，紫）的估计，通过指定数据的贝叶斯生成模型，然后采取通过从模型吉布斯抽样样本后ofthis模型参数。这种(Auto Gaussian Surface fit --- 2 routines to fit a 2D Gaussian to a surface: zi = a*exp(-((xi-x0).^2/2/sigmax^2+ (yi-y0).^2/2/sigmay^2))+ b The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters. autoGaussianSurfML(xi,yi,zi) fits the model parameters through maximum likelihood(least-squares). It first evaluates the quality of the model at many possible values of the parameters then chooses the best set and refines it with lsqcurvefit. autoGaussianSurfGS(xi,yi,zi) estimates the model parameters by specifying a Bayesian generative model for the data, then taking samples from the posterior ofthis model through Gibbs sampling. This method is insensitive to local minimain posterior and gives meaningful error bars (Bayesian confidence intervals))