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130
Estimating the instantaneous frequency of sinusoidal components using phasebased methods
 J. of the Audio Eng. Soc
, 2007
"... The robust estimation of the frequency of some sinusoidal components is a major prerequisite for many applications, such as in sinusoidal sound modeling, where the estimation has often to be done with a low complexity, on shortterm spectra. Among the estimators proposed in the literature, we foc ..."
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The robust estimation of the frequency of some sinusoidal components is a major prerequisite for many applications, such as in sinusoidal sound modeling, where the estimation has often to be done with a low complexity, on shortterm spectra. Among the estimators proposed in the literature, we focus in this paper on a class known as the phasebased estimators. In this paper, we prove that five of these estimators are equivalent, at least in theory. Indepth practical experiments demonstrate that these estimators perform roughly similarly in practice, although small differences remain, differences which are most probably due to numerical properties of the mathematical operators used in their implementation. 1
On the Use of TimeFrequency Reassignment in Additive Sound Modeling
, 2001
"... We introduce the use of the method of reassignment in sound modeling to produce a sharper, more robust additive representation. The Reassigned BandwidthEnhanced Additive Model follows ridges in a timefrequency analysis to construct partials having both sinusoidal and noise characteristics. This mo ..."
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We introduce the use of the method of reassignment in sound modeling to produce a sharper, more robust additive representation. The Reassigned BandwidthEnhanced Additive Model follows ridges in a timefrequency analysis to construct partials having both sinusoidal and noise characteristics. This model yields greater resolution in time and frequency than is possible using conventional additive techniques, and better preserves the temporal envelope of transient signals, even in modified reconstruction, without introducing new component types or cumbersome phase interpolation algorithms.
On Sinusoidal Parameter Estimation
 In Proc. Digital Audio Effects Workshop (DAFx), Queen Marys
, 2003
"... This paper contains a review of the issues surrounding sinusoidal parameter estimation which is a vital part of many audio manipulation algorithms. A number of algorithms which use the phase of the Fourier transform for estimation (e.g. [1]) are explored and shown to be identical. Their performance ..."
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Cited by 11 (2 self)
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This paper contains a review of the issues surrounding sinusoidal parameter estimation which is a vital part of many audio manipulation algorithms. A number of algorithms which use the phase of the Fourier transform for estimation (e.g. [1]) are explored and shown to be identical. Their performance against a classical interpolation estimator [2] and comparison with the Cramer Rao Bound (CRB) is presented. Component detection is also considered and various methods of improving these algorithms are discussed.
Adaptive TimeVarying Cancellation of Wideband Interferences in SpreadSpectrum Communications Based on TimeFrequency Distributions
 IEEE Trans. Signal Processing
, 1999
"... The aim of this paper is to propose an adaptive method for suppressing wideband interferences in spread spectrum (SS) communications. The proposed method is based on the timefrequency representation of the received signal from which the parameters of an adaptive timevarying interference excision ..."
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The aim of this paper is to propose an adaptive method for suppressing wideband interferences in spread spectrum (SS) communications. The proposed method is based on the timefrequency representation of the received signal from which the parameters of an adaptive timevarying interference excision filter are estimated. The approach is based on the generalized WignerHough transform as an effective way to estimate the instantaneous frequency of parametric signals embedded in noise. The performance of the proposed approach is evaluated in the presence of linear and sinusoidal FM interferences plus white Gaussian noise in terms of SNR improvement factor and bit error rate (BER).
Analysis Of Reassigned Spectrograms For Musical Transcription
 IN IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS, MOHONK
, 2001
"... The reassignment method for the shorttime Fourier transform is proposed as a technique for improving the time and frequency estimates of musical audio data. Based on this representation, four classes of expected objects (sinusoid, unresolved sinusoid, transient and noise) are proposed and explained ..."
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Cited by 11 (4 self)
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The reassignment method for the shorttime Fourier transform is proposed as a technique for improving the time and frequency estimates of musical audio data. Based on this representation, four classes of expected objects (sinusoid, unresolved sinusoid, transient and noise) are proposed and explained. Pattern classification methods are then used to extract objects conforming to these classes from individual frames of the reassigned spectrogram, with each frame being examined independently. Results for several simple realworld examples are presented, showing the capability of this method even without the aid of tracking from frame to frame. The main benefits of the proposed reassignment stage are that it yields an improved timefrequency localisation estimate relative to standard methods, and that it produces a measure of the variance of these estimates to be used as an aid in later processing.
Multiple window timevarying spectrum estimation
 in Conf. Info. Sci. and Sys. (CISS
, 1996
"... We overview a new nonparametric method for estimating the timevarying spectrum of a nonstationary random process. Our method extends Thomson’s powerful multiple window spectrum estimation scheme to the timefrequency and timescale planes. Unlike previous extensions of Thomson’s method, we identi ..."
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We overview a new nonparametric method for estimating the timevarying spectrum of a nonstationary random process. Our method extends Thomson’s powerful multiple window spectrum estimation scheme to the timefrequency and timescale planes. Unlike previous extensions of Thomson’s method, we identify and utilize optimally concentrated Hermite window and Morse wavelet functions and develop a statistical test for extracting chirping line components. Examples on synthetic and realworld data illustrate the superior performance of the technique. 2
Adaptive noise level estimation
 in Workshop on Computer Music and Audio Technology(WOCMAT’06
, 2006
"... The topic of this article is the estimation of the colored noise level in audio signals with mixed noise and sinusoidal components. The noise envelope model is based on the assumptions that the envelope varies only slowly with frequency and that the noise amplitudes obey a Rayleigh distribution. The ..."
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The topic of this article is the estimation of the colored noise level in audio signals with mixed noise and sinusoidal components. The noise envelope model is based on the assumptions that the envelope varies only slowly with frequency and that the noise amplitudes obey a Rayleigh distribution. The method is an extension of a recently proposed approach of classification of sinusoidal and noise spectral peaks, which takes into account the noise envelope model to improve the detection of sinusoidal peaks. By means of iterative evaluation and adaptation of the noise envelope model, the classification of noise and sinusoidal peaks is iteratively refined until the detected noise peaks are coherently explained by the noise envelope model. Testing examples of nearly white noise and colored noise are demonstrated. 1.
Signal decomposition by means of classification of spectral peaks
 Proceedings of the International Computer Music Conference. 446– 9
, 2004
"... In extending previous work on detecting transient spectral peaks we here investigate into the distinction between sinusoidal and noise components by means of classification of spectral peaks. The classification is based on descriptors derived from properties related to timefrequency distributions. ..."
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In extending previous work on detecting transient spectral peaks we here investigate into the distinction between sinusoidal and noise components by means of classification of spectral peaks. The classification is based on descriptors derived from properties related to timefrequency distributions. In contrast to existing methods, the descriptors are designed to properly deal with nonstationary sinusoids, which considerably increases the range of applications. The experimental investigation shows superior classification results compared to the standard correlationbased approach. 1
Theory of Modulation Frequency Analysis and Modulation Filtering, with Applications to Hearing Devices
 University of Washington
, 2007
"... and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee: ..."
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and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee:
Estimating Partial Frequency and Frequency Slope Using Reassignment Operators
 in Proc. of the International Computer Music Conference (ICMC’02
, 2002
"... The estimation of the frequency slope of a partial from its peak in the DFT spectrum today is possible only if a Gaussian window is used. In the following we derive a new method to estimate the frequency slope of a partial from its DFT spectral peak based on the reassignment operators. Compared to t ..."
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The estimation of the frequency slope of a partial from its peak in the DFT spectrum today is possible only if a Gaussian window is used. In the following we derive a new method to estimate the frequency slope of a partial from its DFT spectral peak based on the reassignment operators. Compared to the Gaussian window based method our new method can be used with a much larger variety of windows and often achieves better accuracy for equal resolution. After a short introduction into the reassignment method we present a short analytical derivation of the method and we investigate into the analysis properties in relation with the window properties. Based on the analytical derivation of the method we explain the basic requirements for the windows to be used to achieve high accuracy estimates for frequency and frequency slope.