Pointing04-Proceedings

说明：  IBR算法在图像匹配上的应用，我也在学习中(Image matching based on IBR)

Some Matlab CS Reconstruction Algorithm Codes such as greedy pursuit_OMP,COSaMP,SP Convex Optimization _BP algorithm,LP,IHT and TVq algorithm, TVqc. We use one picture to Check these Algorithm.

Gaussian noise refers to its obey gaussian probability density function (i.e., normal distribution) of the noise. If a noise, its amplitude distribution obeys the gaussian distribution, and its power spectral density is uniformly distributed, has described it as a gaussian white noise. Were not associated with the second order moments of the gaussian white noise, a moment is constant, 所谓高斯噪声是指它的概率密度函数服从高斯分布（即正态分布）的一类噪声。如果一个噪声，它的幅度分布服从高斯分布，而它的功率谱密度又是均匀分布的，则称它为高斯白噪声。高斯白噪声的二阶矩不相关，一阶矩为常数，是指先后信号在时间上的相关性。高斯白噪声包括热噪声和散粒噪声。 (Gaussian noise refers to its obey gaussian probability density function (i.e., normal distribution) of the noise. If a noise, its amplitude distribution obeys the gaussian distribution, and its power spectral density is uniformly distributed, has described it as a gaussian white noise. Were not associated with the second order moments of the gaussian white noise, a moment is constant, refers to the correlation of signal in time. White gaussian noise including thermal noise and shot noise. )

绕射系数的matlab程序 (matlab raoshexishu)

小波包分析提取振动信号中的特征频率，包括 MUSIC算法，ESPRIT算法 ROOT-MUSIC算法，用蒙特卡洛模拟的方法计算美式期权的价格以及基本描述。( Wavelet packet analysis to extract vibration signal characteristic frequency, Including the MUSIC algorithm, ESPRIT algorithm ROOT-MUSIC algorithm, Monte Carlo simulation method of calculating the American option price and basic description.)

通过拟合数据结果分析，半参数在变形分析数据中的应用(Fitting the data by analyzing the results of semi-parametric analysis of the data in the deformation of)

VC与matlab接口，来实现小波分解，对于学习VC和matlab混合编程的有很大帮助！(VC and matlab interfaces to achieve the wavelet decomposition, for the study of VC and matlab programming mix of great help!)

经典的leach算法，参考sep原文更容易看懂(the classic wsns algorithm，leach)

Chapter 2 - Animation

Chroma Feature Analysis and Synthesis Chroma features are an interesting and powerful representation for music audio in which the entire spectrum is projected onto 12 bins representing the 12 distinct semitones (or chroma) of the musical octave. Since, in music, notes exactly one octave apart are perceived as particularly similar, knowing the distribution of chroma even without the absolute frequency (i.e. the original octave) can give useful musical information about the audio and may even reveal perceived musical similarity that is not apparent in the original spectra.