Processing photofluorographic images by means of decomposition into empirical modes

Tychkov, Alexander Yu.; Churakov, Pyotr P.

doi:10.1007/s11018-011-9628-9

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Front panel of the VI enables graphic illustration of relationship between the amplitude and time, menu of patient condi Thus, the VI for EPS registration was developed in the LabView environment. Performance of the VI is based on algorithms of recording and processing developed by the authors, which can be used for the training of medical staff and in clinical practice [6].…”

Section: Resultsmentioning

confidence: 99%

Development and Study of a Virtual Encephalograph

Tychkov

2015

Biomed Eng

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Section: Resultsmentioning

confidence: 99%

Development and Study of a Virtual Encephalograph

Tychkov

2015

Biomed Eng

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“…On the basis of the analysis of known algorithms and own researches [9,10,11] speech signals filtering algorithm for noise-robust VCS, based on the CEEMD [12] method is offered. Unlike the EMD and the EEMD methods the use of the CEEMD for decomposition allows excluding almost completely mixing of IMF (arising when processing signals containing short-term and disparate in scale areas).…”

Section: Introductionmentioning

confidence: 99%

Noise-robust speech signals processing for the voice control system based on the Complementary Ensemble Empirical Mode Decomposition

Казанферович

Churakov

2015

2015 International Siberian Conference on Control and Communications (SIBCON)

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Noise-robust speech signals processing is one of the main problems of practical realization of voice control systems (VCS). The offered algorithm of noise-robust processing represents speech signals filtering (voice commands) with the use of the Complementary Ensemble Empirical Mode Decomposition (CEEMD) and the Independent Component Analysis (ICA) methods. A noisy speech signal is adaptively decomposed into frequency components -intrinsic mode functions (IMF) by means of the CEEMD method. The application of the CEEMD method for signals decomposition allows excluding mixing of IMF arising when processing signals containing short-term and disparate in scale areas. From the received set of IMF the mode is defined containing the main noise by means of an assessment of weight energy and noise IMF coefficients. Further the initial noisy speech signal and IMF with the main noise are exposed to processing by means of the ICA method. As a result the filtered speech signal is allocated. The application of the offered filtering algorithm contributes to the increase of VCS noise resistance and accuracy of voice commands recognition. The results of the offered algorithm researches show the effective noise suppression, including small values of signal-to-noise ratio (SNR).

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Processing photofluorographic images by means of decomposition into empirical modes

Cited by 2 publications

References 2 publications

Development and Study of a Virtual Encephalograph

Development and Study of a Virtual Encephalograph

Noise-robust speech signals processing for the voice control system based on the Complementary Ensemble Empirical Mode Decomposition

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