搜索资源列表
用Welch法进行功率谱估计
- 考虑L的三个不同值:L=256(3个数据段),L=128(7个数据段)和L=64(15个数据段)。各自的谱估计图如上图所示。可以明显的看到,加窗明显的减小了频谱上的假谱峰,但也更加进一步平滑了谱峰。所以,对于L=64的情况,在ω=0.8π的谱线可以很确定的辨认,但是那两个靠近的谱峰不容易区分。对于L=128的情况,这种情况提供了在分离和检测间最好的均衡。当然,对于在L=256时的情况,效果是更好的,能够从谱估计图上明显的分辨出三条谱线的
ARMODEL
- 功率谱估计的应用范围很广,在各学科和应用领域中受到了极大的重视。在《现代信号处理》课程中讲述了经典谱估计和现代谱估计这两大类谱估计方法;经典谱估计是基于傅立叶变换的,虽然具有运算效率高的优点,但是频谱分辨率低同时旁瓣泄漏严重,对长序列有着良好的估计。为了克服经典谱估计的缺点,人们开展了对现代谱估计方法的研究。现代谱估计是以随机过程的参数模型为基础的,有最大似然估计法、最大熵法、AR模型法、预测滤波器法。现代谱估计对短序列的估计精度高,同
psd
- 计算ARMA(p,q)模型的功率谱密度。 形参说明: b——双精度实型一维数组,长度为(q+1),存放ARMA(p,q)模型的滑动平均系数。 a——双精度实型一维数组,长度为(p+1),存放ARMA(p,q)模型的自回归系数。 q——整型变量,ARMA(p,q)模型的滑动平均阶数。 p——整型变量,ARMA(p,q)模型的自回归阶数。 sigma2——双精度实型变量,ARMA(p,q)模型白噪声激励的方差
基阵信号处理
- 给定入射信号角度分别为 -22度 ,6度,18度时,不同信噪比情况下各种空间谱估计算法得到的曲线图-given incident signals point to-22 degrees, 6 degrees, 18 degrees, the signal to noise ratio under different space spectral estimation algorithm of the curve
用sa进行光谱图像的特征提取的matlab程序
- 用sa进行光谱图像的特征提取的matlab程序,该算法比用其他方法在性能方面高%15-with spectral images of the Matlab feature extraction procedure, the algorithm than other methods in high-performance
pujian
- 谱减法算法,可以用来对有噪声的语音去噪,提高识别率。-spectral subtraction algorithm can be used to the noise of a voice denoising, and improve recognition rates.
pujianfa
- 经典的功率谱减法,程序复杂度低,运算速度快-classic power spectral subtraction, the complexity of the procedure is low and fast.
exam1_sin
- 本程序用于实现求解并绘制正弦信号功率谱密度的功能-procedures used to achieve the solution and the mapping of sinusoidal signal power spectral density function
exam1_ami
- 本程序能够产生ami码,并且能够绘制其波形图和功率谱密度图-the procedure can have ami yards, and can draw its waveform and power spectral density map
meshpartdist.tar
- This toolbox contains Matlab code for several graph and mesh partitioning methods, including geometric, spectral, geometric spectral, and coordinate bisection. It also has routines to generate recursive multiway partitio
spectral_subm
- 一个很好的原创谱相减法matlab程序。(转)-a good original Spectral subtraction Matlab procedures. (Rpm)
Higher-Order_Spectral_Analysis_toolbox
- 高阶谱分析工具箱,强烈推荐,共计58个函数,实现了高阶谱估计的几乎全部功能。本人在这里上传的文件,仅仅为了学术交流。希望大家都有机会掌握高阶谱估计。互相切磋,共同进步!-higher order spectral analysis toolkit, strongly recommend, for a total of 58 functions, to achieve the high-end of the spectrum is est
speech_enhancement
- 自己编写的用谱相减,最小均方和维纳滤波实现语音增强的matlab文件-themselves with the preparation of spectral subtraction, the minimum mean square Wiener filtering and enhanced voice document Matlab
speech_enhancement_GUI
- 自己编写GUI界面实现语音增强,可在main.c中点击菜单debug中的run便可以运行程序,可分别实现谱相减、最小均方和维纳滤波语音增强-GUI interface to prepare themselves to achieve enhanced voice, in main.c which debug menu click the run will be operating procedures, can be achieved
periodogram
- 本程序是功率谱密度的仿真比较,关于三个信号源的具体情况参见《现代数字信号处理导论》上册,P202,习题5。 实验方法:周期图法、自相关法和协方差法。 -this procedure is the power spectral density of the simulation, 3 signal source on the specific circumstances, see the "modern digital
ModernSpectralEstmation
- 《现代谱估计原理与应用》,凯依著,一本谱估计方面比较经典的书。-"modern spectral estimation theory and applications", according to Kay, a spectral estimation compared classic book.
MSC
- Multiclass Spectral Clustering Algorithm,和Dominant-set算法同属于较常用的聚类算法,用于图像分割等-Multiclass Spectral Clustering Algorith m, and Dominant-set algorithm is more commonly used with the clustering algorithm for image segmentation
SpectralClustering
- Spectral Clustering Embedding Extension聚类算法,主要用于图像处理-Spectral Clustering Embedding Extension clustering algorithm, mainly for image processing
matlabzixiangguan
- 用matlab产生自相关系数固定的序列,然后再观察其功率谱密度.-using Matlab correlation coefficient derived from the fixed sequence, and then observed its power spectral density.
guzhangzhenduanprogram
- 自己编写的比较全面的故障诊断matlab函数程序,包括统计法、时域法、时间序列法、频谱及功率普密度函数、小波分析法程序中有详细的说明。-their preparation of a more comprehensive fault diagnosis Matlab function procedures, including statistics, time domain, time series, and power spectral