Relevant bibliographies by topics / Tufts-Kumaresan

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

Academic literature on the topic 'Tufts-Kumaresan'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Tufts-Kumaresan"

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Watson, Willie R., Mark H. Carpenter, and Michael G. Jones. "Performance of Kumaresan and Tufts Algorithm in Liner Impedance Eduction with Flow." AIAA Journal 53, no. 4 (2015): 1091–102. http://dx.doi.org/10.2514/1.j053705.

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Porat, B., and B. Friedlander. "A modification of the Kumaresan-Tufts methods for estimating rational impulse responses." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 5 (1986): 1336–38. http://dx.doi.org/10.1109/tassp.1986.1164934.

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SO, H. C. "A Simple Improvement to Tufts-Kumaresan Method for Multiple Sinusoidal Frequency Estimation." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E88-A, no. 1 (2005): 381–83. http://dx.doi.org/10.1093/ietfec/e88-a.1.381.

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Porat, B., and B. Friedlander. "On the accuracy of the Kumaresan-Tufts method for estimating complex damped exponentials." IEEE Transactions on Acoustics, Speech, and Signal Processing 35, no. 2 (1987): 231–35. http://dx.doi.org/10.1109/tassp.1987.1165121.

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Nickel, U. "Algebraic formulation of Kumaresan-Tufts superresolution method, showing relation to ME and MUSIC methods." IEE Proceedings F Communications, Radar and Signal Processing 135, no. 1 (1988): 7. http://dx.doi.org/10.1049/ip-f-1.1988.0002.

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Bakhshi, Mohsen, Reza Noroozian, and G. B. Gharehpetian. "Anti-Islanding Scheme for Synchronous DG Units Based on Tufts–Kumaresan Signal Estimation Method." IEEE Transactions on Power Delivery 28, no. 4 (2013): 2185–93. http://dx.doi.org/10.1109/tpwrd.2013.2271837.

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Kahn, M. H. "Effect of the numerical rank of the coefficient matrix on the performance of the Kumaresan—Tufts Prony method." Chemometrics and Intelligent Laboratory Systems 16, no. 1 (1992): 17–23. http://dx.doi.org/10.1016/0169-7439(92)80074-e.

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Zieliński, Tomasz, and Krzysztof Duda. "Frequency and Damping Estimation Methods - An Overview." Metrology and Measurement Systems 18, no. 4 (2011): 505–28. http://dx.doi.org/10.2478/v10178-011-0051-y.

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Abstract:
Frequency and Damping Estimation Methods - An Overview This overview paper presents and compares different methods traditionally used for estimating damped sinusoid parameters. Firstly, direct nonlinear least squares fitting the signal model in the time and frequency domains are described. Next, possible applications of the Hilbert transform for signal demodulation are presented. Then, a wide range of autoregressive modelling methods, valid for damped sinusoids, are discussed, in which frequency and damping are estimated from calculated signal linear self-prediction coefficients. These methods aim at solving, directly or using least squares, a matrix linear equation in which signal or its autocorrelation function samples are used. The Prony, Steiglitz-McBride, Kumaresan-Tufts, Total Least Squares, Matrix Pencil, Yule-Walker and Pisarenko methods are taken into account. Finally, the interpolated discrete Fourier transform is presented with examples of Bertocco, Yoshida, and Agrež algorithms. The Matlab codes of all the discussed methods are given. The second part of the paper presents simulation results, compared with the Cramér-Rao lower bound and commented. All tested methods are compared with respect to their accuracy (systematic errors), noise robustness, required signal length, and computational complexity.
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Dissertations / Theses on the topic "Tufts-Kumaresan"

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Ruplėnaitė, Eglė. "Signalų įvertinimo specialiu mažiausių kvadratų metodu analizė." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080924_174518-69277.

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Abstract:
Darbe atlikta eksponentinių-sinusinių modelių įvertinimo specialiu mažiausių kvadratų metodu analizė. Apžvelgti pagrindiniai signalo parametrai. Aprašyti signalo modeliai bei jų formos. Išnagrinėtas visuminių mažiausių kvadratų metodas bei jam alternatyvūs metodai: kovariacinis, Tufts-Kumaresan ir Pisarenko. Pateikti šių metodų matematiniai aprašymai. Signalų modelių parametrų analizei sukurtos MATLAB programos bei pateikti jų programiniai kodai. Skaitiniais eksperimentais ištirta, kaip kiekvienas iš metodų veikia, esant skirtingam signalo-triukšmo santykiui. Gauti rezultatai iliustruoti grafiškai. Remiantis sumodeliuotais rezultatais, suformuluotos išvados apie nagrinėjamų metodų galimybes.<br>The aim of this study is to explore exponential-sinusoidal signal model estimation by a special least squares method. The main signal parameters are considered. Signal models and their forms are described. The total least squares method as well as its alternatives – the covariance, Tufts-Kumaresan and Pisarenko methods – are analysed. The mathematical description of these methods is given. MATLAB–based programs to analyse signal model parameters are developed and their codes are presented. We investigated the performance of each of these methods for different signal noise ratio values. The results obtained are illustrated graphically. Conclusions about the method properties are drawn on the basis of simulation experiments.
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Conference papers on the topic "Tufts-Kumaresan"

1

Shiyong Li, Xin Lv, Houjun Sun, and Weidong Hu. "Multiple scattering centers measurements using the Kumaresan Tufts method." In IET International Conference on Wireless Mobile and Multimedia Networks Proceedings (ICWMMN 2006). IEE, 2006. http://dx.doi.org/10.1049/cp:20061463.

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