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首页> 外文期刊>International Journal of Wavelets, Multiresolution and Information Processing >Instantaneous frequency estimation and representation of the audio signal through Complex Wavelet Additive Synthesis
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Instantaneous frequency estimation and representation of the audio signal through Complex Wavelet Additive Synthesis

机译：复数小波加法合成的瞬时频率估计和音频信号表示

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摘要

In this work, an improvement of the Complex Wavelet Additive Synthesis (CWAS) algorithm is presented. This algorithm is based on a discrete version of the Complex Continuous Wavelet Transform (CCWT) which analyzes the input signal in a frame-to-frame approach and under variable frequency resolution per octave. After summarizing several Time-Frequency Distributions (TFD), concretely the standard Short Time Fourier Transform (STFT), the Pseudo Wigner-Ville Distribution (PWVD), reassignment and complex wavelets, a comparative study of the accuracy in the instantaneous frequency (IF) estimation is shown. The comparative study includes three different signal processing tools (based on the summarized TFD): the Time-Frequency Toolbox (TFTB) of Francois Auger, the High Resolution Spectrographic Routines (HRSR) of Sean Fulop and the proposed CWAS algorithm. A set of eight synthetic signals have been analyzed using six different methods: the regular STFT spectrogram, the PWVD, their corresponding reassigned versions, the Nelson crossed spectrum method and finally the Complex Continuous Wavelet Transform (CCWT). Finally, two- and three-dimensional Time-Frequency representations of the IF provided by the CWAS algorithm are presented.
机译：在这项工作中，提出了对复小波加法综合（CWAS）算法的改进。该算法基于复杂连续小波变换（CCWT）的离散版本，该形式以帧至帧的方式并以每倍频程可变的频率分辨率分析输入信号。在总结了几种时频分布（TFD），具体而言是标准的短时傅立叶变换（STFT），伪Wigner-Ville分布（PWVD），重新分配和复数小波之后，比较了瞬时频率（IF）的精度显示估算。对比研究包括三种不同的信号处理工具（基于已总结的TFD）：弗朗索瓦·奥格（Francois Auger）的时频工具箱（TFT-B），肖恩·富洛普（Sean Fulop）的高分辨率光谱例程（HRSR）和拟议的CWAS算法。已使用六种不同方法分析了一组八个合成信号：常规STFT频谱图，PWVD，其对应的重新分配版本，Nelson交叉谱方法以及最后的复数连续小波变换（CCWT）。最后，给出了由CWAS算法提供的IF的二维和三维时频表示。

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