搜索资源列表
jiyinzhouqi
- 利用自相关函数估计基音周期,函数jiyinzhouqi,输入参数是分析语音文件名和帧移,帧移在5~10ms-function jiyinzhouqi is used for estimate the period of fundamental tone.
psp1
- 使用逐幸存算法,对有码间串扰的信道参数和进行估计发送信息进行估计-Algorithm used by survivors, for there is intersymbol interference channel to send information to estimate parameters and to estimate the
EM
- 利用Matlab编程验证用EM算法估计的高斯混合模型的相关参数的性能。-Validate the use of Matlab programming estimated using EM algorithm for Gaussian mixture model parameters related to the performance.
GGD_Image-processing
- 这个是广义高斯分布随机数产生程序,它可以用做广义高斯分布形状参数的估计,以及用在图像处理,独立成分分析,信号处理,数字水印等方面。-This is the random numbers about the generalized Gaussian distribution.It can be used in image processing, ICA, signal processing,digital watermark and so on.
GREY
- 连续的系统灰色控制改善了控制性能,并提高了鲁棒性能,采用模型参数v粗略的估计出来,在加以补偿-Continuous gray control system to improve the control performance and improved robustness, using a rough estimate model parameters v out, to be compensated in
VB_RELS
- 用Vb实现的递推最小二乘法估计参数,有可视界面-Vb to achieve with the estimated parameters of recursive least squares method, a visual interface
voice-recognition_matlab-code
- 读入语音文件,并对其做时域、频域的分析,提取相关特征参数。进行线性预测分析,得到LPC谱等线性预测参数,并做了基于预测误差的基音周期估计。-read .wav files,analysing them in time domain,frequency domain and extract some feature parameters related,then do linear prediction analysis ,and get LPC linear prediction paramet
Blind-identification
- 利用现代谱估计中的AR 模型求取仿真噪声信号和真实噪声信号的模型参数,然后利用这些参数求得信号的功率谱图,通过功率谱图定性地描述主噪声源和次噪声源。在利用信号功率谱图定性描述噪声源后,进一步地利用曲线相似度和曲线关联度定量的识别主噪声源和次噪声源-Use of modern spectral estimation of AR model to strike a realistic simulation of the noise signal and noise model parameters,
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- 半参数线性回归模型的最小一乘核估计Semi-parametric linear regression model for the smallest estimated by nuclear-Semi-parametric linear regression model for the smallest estimated by nuclear
capon
- 实验目的: 研究上课所讲谱分析方法,利用实验验证书中的结论,掌握各种谱分析方法,学会实验设计和实验结果分析。 实验内容: 所应用到的谱分析方法,包括: 1) 非参数化方法:周期图(直接法)、BT法(间接法),Welch平均周期图法 2) 参数化方法: RELAX、Capon 3) 空间谱估计:常见的DOA方法(Capon) -Experimental Objective: To study methods of spectral analysis class talk
clean
- 研究上课所讲谱分析方法,利用实验验证书中的结论,掌握各种谱分析方法,学会实验设计和实验结果分析。 所应用到的谱分析方法,包括: 1) 非参数化方法:周期图(直接法)、BT法(间接法),Welch平均周期图法 2) 参数化方法: RELAX、Capon 3) 空间谱估计:常见的DOA方法(Capon) -Experimental Objective: To study methods of spectral analysis class talking about the us
relax
- 研究上课所讲谱分析方法,利用实验验证书中的结论,掌握各种谱分析方法,学会实验设计和实验结果分析。 实验内容: 所应用到的谱分析方法,包括: 1) 非参数化方法:周期图(直接法)、BT法(间接法),Welch平均周期图法 2) 参数化方法: RELAX、Capon 3) 空间谱估计:常见的DOA方法(Capon) -Experimental Objective: To study methods of spectral analysis class talking abou
task22
- 递推极大似然估计法辨识系统参数,输入是M序列,周期为N=24-1。利用递推极大似然算法对系统参数进行辨识-Recursive maximum likelihood estimation method identification system parameters, input M-sequence, period N = 24-1. Using recursive maximum likelihood algorithm for identification of system paramet
non_Gauss_signal_analyse
- 非高斯信号的分析,包括非参数法的双谱估计,基于参数建模的双谱估计,以及基于双谱的有色高斯噪声信号检测。-Non-Gaussian signal analysis, including non-parametric approach of bispectrum estimation, based on modeling bispectrum estimation parameters, and the bispectrum-based signal detection of colored Gau
stationary_signal_analysis
- 平稳信号分析。包括经典功率谱估计、基于参数建模的功率谱估计以及基于非参数建模的功率谱估计。-Stationary signal analysis. Including the classic power spectrum estimation, based on parametric modeling of the power spectrum estimation and modeling based on non-parametric power spectrum estimation.
234234
- 基于非参数核密度估计的Copula函数选择原理.-Based on nonparametric kernel density estimation in the Copula function selection principle
arls
- 对于信号 ,其中w(n)为均值为0,方差为1的AWGN。n=1,2,…,128。 AR模型功率谱估计。假设AR(4),用LS方法估计AR参数,功率谱用freqz(1,LS_ar,1024,1)来验证。-For the signal, which w (n) is zero mean and variance 1 AWGN. n = 1,2, ..., 128. AR model power spectrum estimation. Assuming AR (4), with the
Wiener
- 设计一维纳滤波器 (1). 产生三组观测数据:首先根据S(n)=aS(n-1)+w(n)产生信号S(n),将其加噪声(信噪比分别为20db,10db,6db),得到观测数据X1(n),X2(n),X3(n)。. (2). 估计Xi(n),i=1,2,3的AR模型参数。假设信号长度为L,AR模型阶数为N,分析实验结果,并讨论改变L,N对实验结果的影响。-Design a Wiener filter (1) produces three sets of observations: Fi
p2weifit
- 两参数威布尔最小二乘法估计程序。算法效率高,估计准确-Two-parameter Weibull least squares estimation procedures.High efficiency of the algorithm accurately estimated
p3weifit
- 三参数威布尔最小二乘法估计。算法效率高,估计准确-Least squares estimation of three-parameter Weibull.High efficiency of the algorithm accurately estimated