• Corpus ID: 59431810

Validated exponential analysis for harmonic sounds

  title={Validated exponential analysis for harmonic sounds},
  author={Matteo Briani and Annie A. M. Cuyt and Wen-shin Lee},
In audio spectral analysis, the Fourier method is popular because of its stability and its low computational complexity. It suffers however from a time-frequency resolution trade off and is not particularly suited for aperiodic signals such as exponentially decaying ones. To overcome their resolution limitation, additional techniques such as quadratic peak interpolation or peak picking, and instantaneous frequency computation from phase unwrapping are used. Parameteric methods on the other hand… 

Figures from this paper

Superresolution underwater acoustics
The application of some recent results in exponential analysis and sparse interpolation to underwater acoustics is explored, in a joint effort from marine engineers and computational mathematicians, to recover from possible aliasing introduced by the subsampling.
Regular Sparse Array Direction of Arrival Estimation in One Dimension
A novel technique that makes use of two sparse non-Nyquist regularly spaced antenna arrays, where one of the arrays is just a shifted version of the other, which offers several advantages over the use of traditional dense Nyquist-spaced arrays, while maintaining a comparable algorithmic complexity for the analysis.
Sparse Multidimensional Exponential Analysis with an Application to Radar Imaging
A $d$-dimensional exponential analysis algorithm that offers a range of advantages compared to other methods that does not suffer the curse of dimensionality and only needs $O(O) to be implemented.


Perceptual audio modeling with exponentially damped sinusoids
Fourier-based methods for the spectral analysis of musical sounds
  • S. Marchand
  • Physics
    21st European Signal Processing Conference (EUSIPCO 2013)
  • 2013
Three methods (phase vocoder, spectral reassignment, derivative algorithm) equally efficient: they are in fact different formulations of the best analysis method based on the Fourier spectrum.
A perceptual subspace approach for modeling of speech and audio signals with damped sinusoids
This work shows how to combine well-known subspace based estimation techniques with a recently developed perceptual distortion measure, in order to obtain an algorithm for extracting perceptually relevant model components.
Robust exponential modeling of audio signals
It is shown that by using a proper segmentation of the input data into variable length segments the signal-to-noise ratio can be drastically improved as compared to a fixed-length analysis.
Performance of ESPRIT for Estimating Mixtures of Complex Exponentials Modulated by Polynomials
It is proved that the efficiency of undamped single poles estimators is close to the optimality, and an application to ARMA filter synthesis, in the context of system conversion from continuous time to discrete time.
How to get high resolution results from sparse and coarsely sampled data
A sound analysis/synthesis system based on a deterministic plus stochastic decomposition
This paper addresses the second category of synthesis technique: spectrum modeling and describes a technique called specftal modeling synthesis {SMSl, that models time-varying spectra as a collection of sinusoids controlled through time by piecewise linear amplitude and frequency envelopes.
Identification of GW bursts in high noise using Pad\'e filtering
We consider the case of highly noisy data coming from two different antennas, each data set containing a damped signal with the same frequency and decay factor but different amplitude, phase,
Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise
  • Y. Hua, T. Sarkar
  • Engineering
    IEEE Trans. Acoust. Speech Signal Process.
  • 1990
It is found through perturbation analysis and simulation that, for signals with unknown damping factors, the pencil method is less sensitive to noise than the polynomial method.
On the distribution of poles of Padé approximants to the Z-transform of complex Gaussian white noise