Decomposition of Speech Signal into a Periodic and an Aperiodic Part

Liang, Mangui; Hu, Qi; Huang, Shouzeng

doi:10.1109/icicic.2006.259

Cited by 2 publications

(6 citation statements)

References 9 publications

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“…Unlike existing approaches, the developed methodology allows a signal's aperiodic and periodic components to be evaluated simultaneously, without defining it as the difference between the total signal and its periodic component. The computational complexity of the method depends on the orders n and N in the approximating dependence (13). It does not exceed the total complexity in applying the Fourier and the Maclaurin series.…”

Section: Discussionmentioning

confidence: 99%

“…Processes 2024, 12, x FOR PEER REVIEW 3 of 15 depend on the external influence's characteristics (e.g., shimmer, jitter, and type of excitation). Aczel and Vajk [2] proposed a way to separate signal components based on the frequency estimation method [13]. This approach was applicable for a wide frequency range.…”

Section: The Research Stagesmentioning

confidence: 99%

“…Notably, in the case of an aperiodic signal, the coefficients (14) of the decomposition to a comprehensive series (13) are reduced to the coefficients of the Maclaurin power series. In the absence of an aperiodic component, the same coefficients coincide with the Fourier trigonometric series' coefficients, particularly a 0 = I 0 /T, a p = 2I sp /T, and b p = 2I cp /T.…”

Section: The Polyharmonic Case Studymentioning

confidence: 99%

“…The numerical values of integrals (20), determined by the recurrence relations (24), are tabulated by the sequence of values ( 25) and ( 26) and reduced to Tables 1 and 2. It should be noted that the signal's periodic and aperiodic components are determined simultaneously based on the decomposition into power and polyharmonic series described by Equation (13).…”

Section: Numerical Calculation Of Integralsmentioning

confidence: 99%

“…Processes 2024, 12, 1188 3 of 14 Aczel and Vajk [2] proposed a way to separate signal components based on the frequency estimation method [13]. This approach was applicable for a wide frequency range.…”

Section: Introductionmentioning

confidence: 99%

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Signal Decomposition for Monitoring Systems of Processes

Pavlenko,

Trojanowska,

Ivanov

et al. 2024

Processes

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This article is devoted to the problem of signal decomposition into periodic and aperiodic components. According to the proposed approach, there is no need to evaluate the aperiodic component as a difference between the total signal of its periodic components. This research aims to create a general analytical approach that combines the Fourier and Maclaurin series methodologies into a single comprehensive series. As a result, analytical expressions for determining deposition coefficients were established for an aperiodic signal with a monoharmonic overlay. Recurrence relations were established to determine the coefficients of this series. These relations allow direct integrations of the obtained values of integrals to be avoided. The evaluated numerical values of the coefficients are also presented graphically and tabulated. It was proven that the values of these coefficients are universal numbers since they do not depend on the period/frequency of oscillations. The reliability of the proposed approach was confirmed by the fact that the evaluated coefficients are equal to the Fourier series coefficients in the case of a periodic signal. Also, for an aperiodic signal, these coefficients were reduced to the coefficients of the Maclaurin series. The usability of the proposed generalized analytical approach for signal decomposition is for control and monitoring systems of processes.

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Section: Discussionmentioning

confidence: 99%

Section: The Research Stagesmentioning

confidence: 99%