Relevant bibliographies by topics / Random-multisine

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Random-multisine'

Author: Grafiati
Published: 1 April 2023

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Journal articles on the topic "Random-multisine"

1

Enqvist, Martin. "Separability of scalar random multisine signals." Automatica 47, no. 9 (September 2011): 1860–67. http://dx.doi.org/10.1016/j.automatica.2011.05.015.

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Figwer, Jarosław. "Continuous-time dynamic system identification with multisine random excitation revisited." Archives of Control Sciences 20, no. 2 (January 1, 2010): 133–49. http://dx.doi.org/10.2478/v10170-010-0009-4.

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Continuous-time dynamic system identification with multisine random excitation revisitedThe paper presents a new, revisited and unified approach to a linear continuous-time dynamic single-input single-output system identification using input and output signal samples acquired with a deterministic constant or random sampling interval. The approach is based on a specially designed identification experiment with excitation of the form of a continuous-time multisine random excitation and digital processing of the corresponding signal samples obtained without analogue antialiasing filtration in the case of disturbances satisfying or not satisfying the Shannon's sampling theorem. Properties of the proposed approach are discussed taking into account nonlinearity of the excitation generation and data acquisition systems with a focus on model identification in the case of input and output signal levels comparable with data acquisition system accuracy. Methods reducing influence of the disturbances (including aliasing) as well as nonlinearities of the excitation generation and data acquisition systems on identification results are proposed, too.
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Breugelmans, Tom, Els Tourwé, Jean-Baptiste Jorcin, Ana Alvarez-Pampliega, Bart Geboes, Herman Terryn, and Annick Hubin. "Odd random phase multisine EIS for organic coating analysis." Progress in Organic Coatings 69, no. 2 (October 2010): 215–18. http://dx.doi.org/10.1016/j.porgcoat.2010.04.008.

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Van Ingelgem, Yves, Els Tourwé, Orlin Blajiev, Rik Pintelon, and Annick Hubin. "Advantages of Odd Random Phase Multisine Electrochemical Impedance Measurements." Electroanalysis 21, no. 6 (March 2009): 730–39. http://dx.doi.org/10.1002/elan.200804471.

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Crama, Philippe, and Johan Schoukens. "FIRST ESTIMATES OF WIENER-HAMMERSTEIN SYSTEMS USING A RANDOM MULTISINE EXCITATION." IFAC Proceedings Volumes 35, no. 1 (2002): 43–48. http://dx.doi.org/10.3182/20020721-6-es-1901.00418.

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Główka, Teresa, and Jarosław Figwer. "A Higher-Order Spectra Based Method of On-Line Secondary Path Model Identification for Active Noise Control Systems." Solid State Phenomena 248 (March 2016): 3–10. http://dx.doi.org/10.4028/www.scientific.net/ssp.248.3.

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The aim of this paper is to present a method of nonparametric and parametric secondary path model identification for adaptive active noise control systems with low-power non-Gaussian excitations of the form of a higher-order discrete-time multisine random process and data processing based on cross-higher-order spectra. Properties of the discussed method are illustrated by simulation experiments devoted to secondary path identification for feedforward and feedback active noise control systems. Its robustness to nonlinear distortions implied by data acquisition system and adaptation procedure is proved.
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Zhang, E., R. Pintelon, and P. Guillaume. "Modal Identification Using OMA Techniques: Nonlinearity Effect." Shock and Vibration 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/178696.

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This paper is focused on an assessment of the state of the art of operational modal analysis (OMA) methodologies in estimating modal parameters from output responses of nonlinear structures. By means of the Volterra series, the nonlinear structure excited by random excitation is modeled as best linear approximation plus a term representing nonlinear distortions. As the nonlinear distortions are of stochastic nature and thus indistinguishable from the measurement noise, a protocol based on the use of the random phase multisine is proposed to reveal the accuracy and robustness of the linear OMA technique in the presence of the system nonlinearity. Several frequency- and time-domain based OMA techniques are examined for the modal identification of simulated and real nonlinear mechanical systems. Theoretical analyses are also provided to understand how the system nonlinearity degrades the performance of the OMA algorithms.
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Crama, P., and J. Schoukens. "Computing an Initial Estimate of a Wiener–Hammerstein System With a Random Phase Multisine Excitation." IEEE Transactions on Instrumentation and Measurement 54, no. 1 (February 2005): 117–22. http://dx.doi.org/10.1109/tim.2004.838130.

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Hauffman, Tom, Tom Breugelmans, Yves van Ingelgem, Els Tourwé, Herman Terryn, and Annick Hubin. "Measuring the adsorption of ethanol on aluminium oxides using odd random phase multisine electrochemical impedance spectroscopy." Electrochemistry Communications 22 (August 2012): 124–27. http://dx.doi.org/10.1016/j.elecom.2012.06.008.

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Alvarez-Pampliega, A., T. Hauffman, M. Petrova, T. Breugelmans, T. Muselle, K. Van den Bergh, J. De Strycker, H. Terryn, and A. Hubin. "Corrosion study on Al-rich metal-coated steel by odd random phase multisine electrochemical impedance spectroscopy." Electrochimica Acta 124 (April 2014): 165–75. http://dx.doi.org/10.1016/j.electacta.2013.09.159.

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Dissertations / Theses on the topic "Random-multisine"

1

Chang, Tsung-Chun, and 張琮鈞. "Identification of Nonlinear Power Amplifiers Using Random-phase Multisine Signals." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/90010944640185262080.

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Abstract:
碩士
國立臺灣海洋大學
電機工程學系
95
The power amplifier in a communication system has much to do with the quality of the output replayed by the system. It is due to the fact that nonlinear phenomena may exist in the electronic circuit, mechanical structure, and material design of a power amplifier. To be able to evaluate the goodness of a power amplifier, an accurate and efficient technique for estimating the nonlinear distortion is required. Conventional approaches to measure nonlinear distortion parameters of a power amplifier are time-consuming and cumbersome tasks. In this paper, we use a Volterra model to describe the relation between the input signal and the nonlinear distortion introduced by the power amplifier, and then formulate a parameter-measurement problem into a parameter-estimation problem. In this proposed method, we send a random-phase multisine signal to the power amplifier and record both the input and response signals. These signals are then used by an algorithm to estimate the transfer functions of the Volterra model. Once the transfer functions are estimated, the distortion parameters can be obtained. In this thesis we put forward one efficient method to identify a nonlinear power amplifier system using random-phase multisine signals. This method utilizes the high-order spectral characteristic of random-phase multisine signals.
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Conference papers on the topic "Random-multisine"

1

Ching-Hsiang Tseng. "Estimation of nonlinear communication channels using random multisine signals." In 2008 Third International Conference on Communications and Networking in China. IEEE, 2008. http://dx.doi.org/10.1109/chinacom.2008.4685110.

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Crama, Philippe, and Johan Schoukens. "Wiener-Hammerstein System Estimator Initialisation Using a Random Multisine Excitation." In 58th ARFTG Conference Digest. IEEE, 2001. http://dx.doi.org/10.1109/arftg.2001.327502.

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Figwer, Jaroslaw. "Identification of Multichannel Nonlinear Systems Excited by Realisations of Mutivariate Orthogonal Multisine Random Time-Series." In 2019 24th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2019. http://dx.doi.org/10.1109/mmar.2019.8864620.

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Figwer, Jaroslaw. "An addendum to continuous-time dynamic system identification with multisine random excitations — From frequency response to transfer function." In 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2017. http://dx.doi.org/10.1109/mmar.2017.8046848.

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Journal articles
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