Nonlinear system identification using Wiener basis functions and multiple-variance perfect sequences

Carini, Alberto; Orcioni, Simone; Terenzi, Alessandro; Cecchi, Stefania

doi:10.1016/j.sigpro.2019.02.017

Cited by 18 publications

(14 citation statements)

References 42 publications

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“…This was due to the request of knowledge of the sound characteristics of those instruments from lutherie, industrial manufactory companies, researchers, curators, collectors, museums, historians, musicians, theatre companies and all parties involved with preservation and restoration of those important, valuable objects. One more reason for studying the sound characteristics of musical instruments from the physical perspective is the emulation of their sound characteristics [6] by means of measurements of impulse responses [7] and convolution with dry music, including nonlinear properties [8,9].…”

Section: Introductionmentioning

confidence: 99%

The Carabattola—Vibroacoustical Analysis and Intensity of Acoustic Radiation (IAR)

2020

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Among the studies of musical instruments, one important, sometime underestimated discipline, is represented by ethnomusicology. The acoustic analyses on ethnic musical instruments (M.I.) are much more infrequent if compared to those on classical M.I. This article deals with the vibro-acoustic analysis on one of the most unknown ethnic, Italian M.I., i.e., the carabattola (also called battola), which used to be played in Italy until the late 1960s during the Holy Thursday before Easter. The study includes modal analysis and Intensity of Acoustic Radiation measured on an original carabattola, which was played in the Romagna area until the early twentieth century. After a brief overview about the theory of acoustic and vibrational analysis on musical instruments, the Intensity of acoustic radiation and its correlation with modal analysis are recalled, based on previous studies. In the experimental part of the article, the measurements conducted on the carabattola are described. Afterwards, the results obtained both from modal analysis and IAR measurements are analyzed and compared with other measurements previously conducted on musical (particularly percussion) instruments and commented.

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Section: Introductionmentioning

confidence: 99%

The Carabattola—Vibroacoustical Analysis and Intensity of Acoustic Radiation (IAR)

2020

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Section: Wiener Nonlinear Filtersmentioning

confidence: 97%

“…It was also shown in [38,51] that the WN filters admit PPSs that guarantee the same orthogonality of the WN basis functions on a finite period. The PPSs that were developed in [38,51] are periodic sequences whose samples have approximately a Gaussian distribution. With a PPS input, a WN filter can be identified with the cross-correlation method, computing the cross-correlation between the basis functions and the system output.…”

Section: Wiener Nonlinear Filtersmentioning

confidence: 97%

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Robust Room Impulse Response Measurement Using Perfect Periodic Sequences for Wiener Nonlinear Filters

2020

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The paper discusses a measurement approach for the room impulse response (RIR), which is insensitive to the nonlinearities that affect the measurement instruments. The approach employs as measurement signals the perfect periodic sequences for Wiener nonlinear (WN) filters. Perfect periodic sequences (PPSs) are periodic sequences that guarantee the perfect orthogonality of a filter basis functions over a period. The PPSs for WN filters are appealing for RIR measurement, since their sample distribution is almost Gaussian and provides a low excitation to the highest amplitudes. RIR measurement using PPSs for WN filters is studied and its advantages and limitations are discussed. The derivation of PPSs for WN filters suitable for RIR measurement is detailed. Limitations in the identification given by the underestimation of RIR memory, order of nonlinearity, and effect of measurement noise are analysed and estimated. Finally, experimental results, which involve both simulations using signals affected by real nonlinear devices and real RIR measurements in the presence of nonlinearities, compare the proposed approach with the ones that are based on PPSs for Legendre nonlinear filter, maximal length sequences, and exponential sweeps.

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Offline identification and output prediction for a class of SISO Wiener process

et al. 2022

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In this paper, a simplified Wiener structure (SWS) for single‐input‐single‐output (SISO) Wiener processes and an identification method based on Gaussian mixture model (GMM) and expectation maximization (EM) algorithm are proposed. The vast majority of industrial processes can be regarded as approximately monotonic non‐linear processes. Approximately, a monotonic characteristic is introduced into the non‐linear module and a rich dynamic characteristic is added into the linear module of the Wiener model. Thus, SWS is exploited and has strong generalization ability. Because GMM can describe the arbitrary distribution of sample data in theory, it is used to accurately describe the output data, including the system error term of SWS. Hence, a statistical model (Equation (17)) is obtained. Then, the EM algorithm is introduced to identify the parameters of the statistical model that contains the parameters of SWS. In the end, two numerical examples demonstrate the effectiveness of both the SWS and the GMM‐EM‐based iterative offline identification algorithm.

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Nonlinear system identification using Wiener basis functions and multiple-variance perfect sequences

Cited by 18 publications

References 42 publications

The Carabattola—Vibroacoustical Analysis and Intensity of Acoustic Radiation (IAR)

The Carabattola—Vibroacoustical Analysis and Intensity of Acoustic Radiation (IAR)

Robust Room Impulse Response Measurement Using Perfect Periodic Sequences for Wiener Nonlinear Filters

Offline identification and output prediction for a class of SISO Wiener process

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