Description: 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,同经典谱估计互为补充。在认真学习了现 代谱估计方法后,我选择了现代谱估计中的AR模型法的仿真作为题目。下面给出AR模型的相关理论和仿真实现。-Power Spectral Estimation of very extensive, in all disciplines and fields of application of a great deal of attention. The "modern signal processing" on the curriculum of classical and modern spectral estimation spectrum is estimated that the two types of spectrum estimation method; Classical spectrum estimation is based on Fourier transform, although high computing efficiency advantages, but also low-resolution spectrum Sidelobe serious leakage of long sequences have good estimates. In order to overcome the classic shortcomings of the spectrum estimation, there have been a pair of modern spectral estimation methods. Modern spectral estimation is the random process model parameters based on the maximum likelihood estimation, maximum entropy method, AR model, forecast filter. Spe Platform: |
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Author: |
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Description: 接法又称周期图法,它是把随机序列x(n)的N个观测数据视为一能量有限的序列,直接计算x(n)的离散傅立叶变换,得X(k),然后再取其幅值的平方,并除以N,作为序列x(n)真实功率谱的估计。
-Connection also known as cycle map, it is random sequence x (n) N observational data as a sequence of limited energy, direct calculation x (n) the discrete Fourier transform, in X (k), then the lesser of the square of the amplitude and divided by N, as the sequence x (n) real power spectrum estimation. Platform: |
Size: 9216 |
Author:梁宏波 |
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Description: 1.通过实验加深对快速傅立叶变换(FFT)基本原理的理解。
2.了解FFT点数与频谱分辨率的关系,以及两种加长序列FFT与原序列FFT的关系。
离散傅里叶变换(DFT)和卷积是信号处理中两个最基本也是最常用的运算,它们涉及到信号与系统的分析与综合这一广泛的信号处理领域。实际上卷积与DFT之间有着互通的联系:卷积可化为DFT来实现,其它的许多算法,如相关、滤波和谱估计等都可化为DFT来实现,DFT也可化为卷积来实现。-1. Deepen the experimental fast Fourier transform (FFT) the basic tenets of understanding. 2. Understand the FFT spectrum and points of the resolution, and two extended sequence with the original FFT FFT relations. Discrete Fourier Transform (DFT) and the convolution of two signal processing is the most commonly used basic arithmetic, they relate to the signal and system analysis and synthesis of the wide range of signal processing field. DFT actually convolution and interoperability between contact : DFT into convolution can be achieved in many other algorithms, If relevant, filtering and spectral estimation could be achieved as DFT, DFT into convolution can be achieved. Platform: |
Size: 3072 |
Author:深蓝 |
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Description: 实验内容:
1.求下列3个模板的频率响应,并显示其三维图形;选择一幅图
像,利用这3个模板分别对该图像进行卷积运算,将卷积运算
获得的图像与原始图像进行比较,说明各模板的类型以及模板
(b)、(c)的区别与联系。
2. 选择一幅图像,对其进行离散Fourier变换,仅利用其相位谱重构原图像,然后仅利用其振幅谱重构原图像,比较实验结果;
选择两幅不同类型的图像,分别进行Fourier变换,交换二者的相位谱后求Fourier反变换,比较实验结果,说明图像Fourier相位谱的重要性。-Experimental contents: 1. Template for the following three frequency response and to show its three-dimensional graphics select an image using the three templates, respectively, of the image convolution operation, the convolution operation to obtain the images were compared with the original image to illustrate the template the type of template (b), (c) the difference with the contact. 2. Select an image, its discrete Fourier transform, only to use its phase spectrum remodeling the original image, and then only the use of its amplitude spectrum reconstruction of the original image to compare experimental results choice of two different types of images, respectively Fourier Transform, the exchange between the two after the phase spectrum for Fourier Transform, compare experimental results to illustrate the image of the importance of Fourier phase spectrum. Platform: |
Size: 1024 |
Author:syq |
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Description: 利用傅里叶描述子进行物体形状分析:
对于一个物体的边缘即形状来说,可将其看作是平面在空间坐标系下的点集构成的闭合曲线,这样就可用周期函数来描述其外形,可以进行离散傅里叶变换,将图像由空域表示转换到频域表示,变换后的函数可由傅里叶变换系数来描述。对于数字图像的频谱来说,低频分量的分布反映了图像主体的基本形状,高频分量的分布反映图像的细节-Fourier descriptors for object shape analysis: For the edge of an object or shape, it can be regarded as the plane in the space coordinates of the point set consisting of closed curves, so that periodic function can be used to describe its shape , can be discrete Fourier transform, the image from the airspace, said the conversion to the frequency domain that function can be transformed to describe the Fourier transform coefficients. For digital images of the spectrum, the distribution of low-frequency components reflect the basic shape of the main images, high-frequency component of the distribution reflects the image details Platform: |
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Author:吴亚鹏 |
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Description: Matlab做的关于三角波,正弦波,方波的FFT算法,可以分析方波信号、三角波信号的频谱以及采样点数、采样频率对频谱分辨率的影响。-Matlab to do on the triangle wave, sine wave, square wave of the FFT algorithm, can be analyzed square-wave signal, triangular wave signal of the spectrum as well as the sampling points, the sampling frequency affect the resolution of the spectrum. Platform: |
Size: 1024 |
Author:venppen |
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Description: 本文讨论了信号经过傅立叶变换所得频谱的物理意义,其中着重于负频率成分。因为许多信号与系统的教材中都提出负频率成分没有物理意义,本文以多方面的实例证明了负频率成分不但具有明确的物理意义,而且有重要的工程应用价值。文章还用MATLAB程序演示了如何用几何方法求傅立叶反变换,把集总频谱合成为时域信号,从中也可鲜明地看出负频率成分的意义。(学习用)-This paper discusses the signal after Fourier transform from the physical meaning of the spectrum, which focuses on the negative frequency components. Signals and Systems because many materials have no negative frequency components of the physical meaning of this article to a wide range of examples to prove a negative frequency components not only specific physical meaning, but also have important engineering application value. Article also demonstrates how MATLAB program using the geometric method for the anti-Fourier transform, spectrum把集total synthesis time domain signal, which can also be vividly seen in the significance of the negative frequency components. (To learn) Platform: |
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Author:安浩 |
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Description: 1.用Matlab产生正弦波,矩形波,以及白噪声信号,并显示各自时域波形图
2.进行FFT变换,显示各自频谱图,其中采样率,频率、数据长度自选
3.做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱
4.用IFFT傅立叶反变换恢复信号,并显示恢复的正弦信号时域波形图
-1. Using Matlab generated sine wave, rectangular wave, as well as the white noise signal, and display their respective time-domain waveform of Figure 2. FFT to transform, showing their frequency spectrum, including sampling rate, frequency, data length of 3-on-demand. Made of the three signals in root-mean-square maps, power maps, as well as the number of root-mean-square map 4. Fourier Transform IFFT with the restoration of signals, and displays the sinusoidal signal the resumption of time-domain waveform Platform: |
Size: 4096 |
Author:白杨 |
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Description: Using the function to sample the voice signal and achieve fast Fourier transform in MATLAB, and then get the signal characteristics of the spectrum.Filtering the signal from the filter,and then playback the signal of voice Platform: |
Size: 72704 |
Author:林霞 |
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Description: MFCC (Mel Frequent Cepstral Coefficient) in M-File.
epresentation of the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency.
MFCCs derived as follows:
1. Take the Fourier transform of (a windowed excerpt of) a signal.
2. Map the powers of the spectrum obtained above onto the mel scale, using triangular overlapping windows.
3. Take the logs of the powers at each of the mel frequencies.
4. Take the discrete cosine transform of the list of mel log powers, as if it were a signal.
5. The MFCCs are the amplitudes of the resulting spectrum.
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Author:Mitha |
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Description: 本实验要求开发一个2-D FFT程序包,使其可以应用于后续的几个实验。这个程序需要完成的功能是用因子(-1)^(x+y)乘以输入图像以实现滤波的中心变换,并还要求用一个实矩阵乘以一个复数矩阵通过调用两个图像的乘法程序来实现对应元素的相乘,同时计算反傅立叶变换,得到的结果乘以(-1)^(x+y)并取其实部最后计算频谱。实验中用到傅立叶变换的基本公式,通过实验我们可以更加深刻的理解频域滤波的基础。-The experiment calls for the development of a 2-D FFT package so that it can be applied to a number of follow-up experiment. This process needs to be done is to factor the function (-1) ^ (x+ y) multiplied by the input image to achieve the center of filter change, and also requires a real matrix multiplied by a complex matrix by calling the two images of the multiplication process to achieve multiplication of the corresponding elements, calculating the anti-Fourier transform at the same time, the result multiplied by (-1) ^ (x+ y) and check the final calculation of the Department of the spectrum in fact. Fourier transform experiment used the basic formula, we can experiment more profound understanding of the basis of frequency domain filtering. Platform: |
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Author:jhm |
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Description: 二维傅里叶变换,对图像进行二维傅里叶变换处理-Two-Dimensional Fast Fourier Transform
The purpose of this project is to develop a 2-D FFT program "package" that will be used
in several other projects that follow. Your implementation must have the capabilities to:
(a) Multiply the input image by (-1)x+y to center the transform for filtering.
(b) Multiply the resulting (complex) array by a real function (in the sense that the
the real coefficients multiply both the real and imaginary parts of the transforms).
Recall that multiplication of two images is done on pairs of corresponding elements.
(c) Compute the inverse Fourier transform.
(d) Multiply the result by (-1)x+y and take the real part.
(e) Compute the spectrum. Platform: |
Size: 1024 |
Author:solo |
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Description: 本次实验主要是对一个正弦信号加入高斯白噪声,然后通过傅里叶变换对正弦信号进行谱估计。最后要用matlab进行仿真,得到正弦函数的时域和频域波形,关键找出信噪比和正弦信号频谱的均方误差之间的关系。-The experiment is a sinusoidal signal which is to white Gaussian noise, then by Fourier transform of the sinusoidal signal spectrum estimation. Finally, using the matlab simulation, sine function in time domain and frequency domain waveforms. Platform: |
Size: 39936 |
Author:zjc |
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Description: 采用matlab进行傅里叶变换,将图像变换成频谱形式的图像。-Using MATLAB Fourier transform, the image is converted into a spectrum in the form of image. Platform: |
Size: 1024 |
Author:车军 |
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Description: 基于matlab 的叠加高斯白噪声的正弦信号频谱分析,给定正弦函数x=sin(2πf0n/N+π/3)+sin(2πf1n/N+π/4),设定f0.f1的值,加了噪声之后做快速傅里叶变换,在matlab中分析其频谱,验证是否与f0,f1的值符合。再变换N值,看随着N值的变化对应点是否符合及有何变化。-Matlab based on the superposition of Gaussian white noise sinusoidal signal spectrum analysis, given the sine function x = sin (2蟺f0n/N+蟺/3)+sin (2蟺f1n/N+蟺/4) set value of f0.f1, do a quick noise Fourier transform to analyze the spectrum in matlab, verify that with f0, in line with the value of F1. Transform the value of N, see change as the value of N corresponding points of compliance and what changes. Platform: |
Size: 1024 |
Author:xiha |
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Description: 信号处理中的振幅谱和相位谱以及谱密度估计等-1) Calculation of:
- One-sided amplitude spectrum
- One-sided phase spectrum
- Vector of frequencies.
2) The function can plot:
- One-sided amplitude spectrum
- One-sided phase spectrum.
Two examples are given in order to clarify the usage of the function. The input and output arguments are given in the beginning of the code.
The code is based on the theory described in:
[1] N. Majumdar, S. Banerjee. MATLAB Graphics and Data Visualization, Birmingham, Packt Publishing, 2012.
[2] D. Manolakis, V. Ingle. Applied Digital Signal Processing. Cambridge, Cambridge University Press, 2011.
[3] G. Heinzel, A. Rudiger, R. Schilling. Spectrum and spectral density estimation by the Discrete Fourier transform (DFT), including a comprehensive list of window functions and some new flat-top windows. Germany, Hannover, Max-Planck-Institut für Gravitationsphysik, 2002. Platform: |
Size: 2048 |
Author:小圆 |
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Description: (1)熟悉并掌握傅立叶变换
(2)了解傅立叶变换在图像处理中的应用
(3)通过实验了解二维频谱的分布特点
(4)用MATLAB实现傅立叶变换仿真
-(1) be familiar with and master the Fourier transform (2) understand the Fourier transform in image processing applications (3) experiments to understand the characteristics of the two-dimensional distribution of the spectrum (4) simulation using MATLAB Fourier transform Platform: |
Size: 158720 |
Author:小慷 |
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Description: 利用MATLAB中的GUI(图形用户界面),实现图像的灰度化,直方图,图像的错切变换,直方图均衡化,量化图像及图像的傅里叶频谱,是效果更加明显。-In MATLAB GUI (graphical user interface), to achieve graying, histogram, image conversion cut the wrong image, histogram equalization, quantized image and the image of the Fourier spectrum of the effect is more obvious. Platform: |
Size: 1210368 |
Author:konghao |
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Description: 对非平稳信号进行分段、截取,再做短时傅里叶变换,分析其频谱特性,并找到各个时间节点的频率特性,以便分析不同事件段内的声音特征。(The non-stationary signals are segmented and intercepted, and then the short-time Fourier transform is used to analyze their frequency spectrum characteristics, and the frequency characteristics of each time node are found in order to analyze the sound characteristics in different event segments.) Platform: |
Size: 23552 |
Author:帅红
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Description: 基于MATLAB 的语音信号频谱分析与去噪研究
1、通过Matlab读入语音信号,进行频域分析
2、绘制语音信号频谱;
3、设计滤波器并进行滤波;
4、加噪,对比语音信号波形和频谱(Research on speech signal spectrum analysis and denoising based on MATLAB
1, read the voice signal through Matlab and analyze it in frequency domain.
2, draw the frequency spectrum of speech signal;
3. The filter is designed and filtered.
4. Add noise and compare the waveform and spectrum of speech signal) Platform: |
Size: 26485760 |
Author:malvina |
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