hiding-audio-in-image

说明：  求光斑中心点坐标,对图像二值化。并且对其中心坐标求出(mean)

纹理特征提取 garbo小波技术实现纹理特征提取(texture based on Gabor)

关于matlab中的一些函数，以及对于函数的使用与说明(A document which is about the function in matlab)

Matlab界面编程的一个实例， Matlab2008a(A example of MATLAB GUI program)

实验要求：在一张图上绘制三种二进制信号（即反极性信号、开关信号和正交信号）的误码率。这三种信号可以在几何上用“信号空间”中的点来表示。在反极性信号情况下，信号是±s(t)，每个都有能量E。开关信号也是一维信号，所以两个信号为0和s(t)，正交信号我们上课已讲过。要求信噪比为0：12dB。(Experimental requirements: to draw a diagram of three binary signals (i.e., reverse polarity signal, the switching signal and quadrature signal) BER. These three signals can be in the geometric point in the signal space. In the reverse polarity signal case, the signal is s (t), each have energy E. The switching signal is also a one-dimensional signal, so the two signals is 0 and s (t), the quadrature signals teach us have talked. Signal-to-noise ratio to 0:12 dB.)

machine learning中最经典的图书(The most classic machine books learning)

传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这 一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表 示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的 语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优 于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method. )

parameter of dc motor

拉普拉斯特征映射算法，可实现高维信号降维或实现带内滤波降噪。(Laplace feature mapping algorithm, can achieve high dimensional signal dimensionality reduction or implement band noise filtering.)

用matlab编写的钟摆动画,可是实现钟摆的摆动和时针分针秒针的跳动(matlab)