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Description
  • This paper focuses on blind compensation of memoryless nonlinear distortions in sparse signals. A nonlinear distortion tends to decrease the sparsity. We propose to compensate for the unknown distortion using a general monotonic function, such that the compensated signal is as sparse as possible. Novel estimator for the compensation function is presented, which is able to compensate for both symmetric and asymmetric distortions. The selection of a sparsity measure is discussed with respect to compensation performance. The functionality of the method is evaluated in experiments with artificially distorted real-world speech signals.
  • This paper focuses on blind compensation of memoryless nonlinear distortions in sparse signals. A nonlinear distortion tends to decrease the sparsity. We propose to compensate for the unknown distortion using a general monotonic function, such that the compensated signal is as sparse as possible. Novel estimator for the compensation function is presented, which is able to compensate for both symmetric and asymmetric distortions. The selection of a sparsity measure is discussed with respect to compensation performance. The functionality of the method is evaluated in experiments with artificially distorted real-world speech signals. (en)
Title
  • Blind Compensation of Memoryless Nonlinear Distortions in Sparse Signals
  • Blind Compensation of Memoryless Nonlinear Distortions in Sparse Signals (en)
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  • Blind Compensation of Memoryless Nonlinear Distortions in Sparse Signals
  • Blind Compensation of Memoryless Nonlinear Distortions in Sparse Signals (en)
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  • RIV/46747885:24220/13:#0002596!RIV14-TA0-24220___
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  • P(TA01011142)
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  • 63632
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  • RIV/46747885:24220/13:#0002596
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  • Memoryless nonlinear distortion; blind compensation; sparse signal (en)
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  • [8CDAD3D1CB38]
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  • Maroko
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  • Proc. of EUSIPCO 2013
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  • Málek, Jiří
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issn
  • 2219-5491
number of pages
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  • Neuveden
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  • 24220
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