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learn.zip

于 2014-08-18 发布文件大小:153KB

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MFCC参数和LPCC参数需要频繁使用的语音的说话人识别分析还需要使用大量的这些特征参数,这就需要研究MFCC和LPCC算法和参数提取的原则。因为我们需要了解与人交谈的过程中,我们要进行建模率不构成线性关系，而更偏向于对数关系，这就使得人耳对低频信号比高频信号更敏感。Mel频率的提出是为了方便人耳对不同频率语音的感知特性的研究。频率与Mel频率的转换公式为(MFCC parameters and LPCC parameters are parameters of speaker recognition which requires frequent use of voice analysis also need to use a lot of these characteristic parameters, This requires research MFCC and LPCC algorithm and the principle of parameter extraction. Because we need to understand the process of talking to people, we want to conduct a speaker modeling the perception of the human ear does not constitute a linear relationship with frequency, and prefer to logarithmic relationship, which makes the human ear is sensitive to low frequency signal is better than high frequency signal. Mel frequency is put forward in order to facilitate the ear of the study of speech perception characteristics of different frequency. For frequency and Mel frequency conversion formula)

文件列表：

MMaben.mat,6279,2008-06-15
Numdata.mat,153792,2008-06-15
Periods.m,1055,2008-06-15
RcNum.m,306,2008-06-15
RcNum1.m,878,2008-06-15

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interp1
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homework5a
this is a homw work for students to get concept

2010-11-25 10:43:31下载

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zy1
摘要该文主要考虑利用图像噪声再生技术来提取图像细节其思想是利用被滤除的噪声信号进行回收再利用通过对噪声信号和初步去噪信号进行小波变换比较它们的小波系数当噪声信号的小波系数达到一定的阈值时将噪声信号的小波系数保留叠加至初步去噪信号的小波系数然后利用传统的软阈值去噪的方法来进行图像的去噪从而达到既能够去除噪声又能保留图像细节的目的实验证明该方法较传统的方法在去噪和细节保持上有改进(Abstract In this paper, consider using images to extract the noise regeneration of its ideological image detail is the use of the noise signal was filtered to recycle through the noise signal and the initial wavelet transform de-noising signal comparison of their wavelet coefficients of the wavelet signal when the noise coefficient reaches a certain threshold will be the noise signal superimposed to the wavelet coefficients to retain the initial de-noising signal wavelet coefficients and then using the traditional soft-threshold denoising approach to image denoising in order to achieve the removal of noise can not only be able to retain The purpose of image detail that the methods of the experiment a more traditional approach to denoising and detail in there to keep improving)

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snogcca01
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常用信号分析程序，包括FFT，画包络谱，频谱，自相关、互相关，倒频谱，功率谱(Common signal analysis program, including FFT, painting envelope spectrum, spectrum, auto-correlation, cross correlation, cepstrum, power spectrum)

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dd
说明：此函数实现对自适应波束图的极化，这样更加方便地在极化图中看到波束图的期望方向和干扰方向(This function implementation of adaptive beamforming polarization map, so that makes it easier to see in the picture at the polarization beam map the direction and interfere with the expectations of the direction of)

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