Question

谁能帮我翻译一段话，中译英！急

去噪，一般的傅里叶算法，一般可以是IIR滤波和FIR滤波。两者各有优缺点。而小波的消噪，一般也是由多层分解和阈值策略组成。我们需要的是信号的特点，噪声的特点，然后确定用不用小波，或用什么小波。这点上，小波的优势并不是很明显。但是在实际工程应用中，所分析的信号可能包含许多尖峰或突变部分，且噪声不是平稳的白噪声，对这种信号进行分析处理，首先要做预处理，将噪声去除，提取有用信号。对于这种信号的去噪，传统的Fourior分析显得无能为力。 小波变换是一种信号的时频分析方法，他具有多分辨率分析的特点，很适合探测正常信号中夹带的瞬态反常现象并展示其成分，有效区分信号中的突变部分和噪声。因此利用小波变换进行信号消除的同时提取含噪信号明显好于传统的Fourior变换的分析方法。通过M atlab编制程序进行给定信号的噪声抑制和非平稳信号的噪声消除。

Answer 1

Denoising, the general Fourier algorithm, the general IIR filter and FIR can be filtered. Both have advantages and disadvantages. The wavelet denoising, the general is made up of layers composed of decomposition and threshold strategies. What we need is the signal characteristics, noise characteristics, and then determine the wavelet with the need, or what wavelet. This point, the advantages of wavelets is not very obvious. However, in practical application, the analysis of the signal may contain many parts of the peak or mutation, and the noise is not stationary white noise, the analysis of this signal processing, first of all pretreatment, the noise removal, extract the useful signal. For this signal denoising, the traditional Fourior analysis look powerless. Wavelet transform is a time-frequency analysis methods, he has the characteristics of multi-resolution analysis, it is suitable for detection of transient entrainment of the normal signal anomaly and show their constituents effectively distinguish between the mutant part of the signal and noise. Therefore, the signal using wavelet transform to eliminate the simultaneous extraction of signals with noise is better than the traditional Fourior transform analysis. Preparation program through M atlab given signal noise suppression and elimination of non-stationary noise signals.

Answer 2

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Denoising, the general Fourier algorithm, the general IIR filter and FIR can be filtered. Both have advantages and disadvantages. The wavelet denoising, the general is made up of layers composed of decomposition and threshold strategies. What we need is the signal characteristics, noise characteristics, and then determine the wavelet with the need, or what wavelet. This point, the advantages of wavelets is not very obvious. However, in practical application, the analysis of the signal may contain many parts of the peak or mutation, and the noise is not stationary white noise, the analysis of this signal processing, first of all pretreatment, the noise removal, extract the useful signal. For this signal denoising, the traditional Fourior analysis look powerless. Wavelet transform is a time-frequency analysis methods, he has the characteristics of multi-resolution analysis, it is suitable for detection of transient entrainment of the normal signal anomaly and show their constituents effectively distinguish between the mutant part of the signal and noise. Therefore, the signal using wavelet transform to eliminate the simultaneous extraction of signals with noise is better than the traditional Fourior transform analysis. Preparation program through M atlab given signal noise suppression and elimination of non-stationary noise signals.

Answer 3

Denoising, normal Fourier algorithm, which can be one of the IIR and FIR filter filter. Each has advantages and disadvantages. The wavelet Denoise, generally consists of multiple layers of decomposition and the threshold policy. What we need is the noise signal characteristics, features, and then determine the use of wavelet, or what the wavelet. This point, the advantages of wavelet and not be obvious. However in a real application, the analysis of signal may contain a number of spikes or mutation, and the noise is not a smooth white noise, this signal analysis and processing, the first thing we do preprocessing, noise removal, and extract the useful signal. For this type of signal denoising, traditional Fourior analysis found. DWT is a time-frequency analysis, he has a multi-resolution analysis of characteristics, very suitable for detecting good signal in the midst of transient anomaly and show differentiate their constituents, a valid signal mutation and noise. Therefore application of wavelet transform to signal the Elimination of noisy signals simultaneously extracting significantly better than traditional methods of analysis for the Fourior transform. Atlab developed by M program for a given signal noise suppression and non-stationary signals in noise reduction.

Answer 4

自己找本信号处理的双语教材看吧，鬼会帮你翻