We are interested in obtaining a sparse representation of music signals by means of a discrete wavelet transform (DWT). That means we want the energy in the representation to be concentrated in few DWT coefficients. It is well-known that the decay of the DWT coefficients is strongly related to the number of vanishing moments of the mother wavelet, and to the smoothness of the signal. In this paper we present the result of applying two classical families of wavelets to a series of musical signals. The purpose is to determine a general relation between the number of vanishing moments of the wavelet and the sparseness of the DWT coefficients
Abstract—Sparse representations have proved a powerful toolin the analysis and processing of audio s...
International audienceThis paper investigates the use of musical priors for sparse expansion of audi...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
Within the last few decades a number of new signal processing tools has appeared. These have mainly ...
We introduce a new method for generating time-frequency distributions, which is particularly useful ...
We want to use a variety of sparseness measured applied to ‘the minimal L1 norm representation' of a...
In this paper we investigate how the energy is dis-tributed in the coefficients vector of various re...
We introduce a new method for generating time-frequency distributions, which is particularly useful ...
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
International audienceSparse representations have proved a powerful tool in the analysis and process...
© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Wavelet theory is a relatively new tool for signal analysis. Although the rst wavelet was derived by...
peer-reviewedIn this thesis, Blind Source Separation is studied in the context of both instantaneous...
A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to...
This paper explores the degree of sparsity of a signal ap-proximation that can be reached while ensu...
Abstract—Sparse representations have proved a powerful toolin the analysis and processing of audio s...
International audienceThis paper investigates the use of musical priors for sparse expansion of audi...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
Within the last few decades a number of new signal processing tools has appeared. These have mainly ...
We introduce a new method for generating time-frequency distributions, which is particularly useful ...
We want to use a variety of sparseness measured applied to ‘the minimal L1 norm representation' of a...
In this paper we investigate how the energy is dis-tributed in the coefficients vector of various re...
We introduce a new method for generating time-frequency distributions, which is particularly useful ...
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
International audienceSparse representations have proved a powerful tool in the analysis and process...
© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Wavelet theory is a relatively new tool for signal analysis. Although the rst wavelet was derived by...
peer-reviewedIn this thesis, Blind Source Separation is studied in the context of both instantaneous...
A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to...
This paper explores the degree of sparsity of a signal ap-proximation that can be reached while ensu...
Abstract—Sparse representations have proved a powerful toolin the analysis and processing of audio s...
International audienceThis paper investigates the use of musical priors for sparse expansion of audi...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...