Relevant bibliographies by topics / Averaging

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Averaging'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Averaging"

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Nurser, A. J. George, and Mei-Man Lee. "Isopycnal Averaging at Constant Height. Part I: The Formulation and a Case Study." Journal of Physical Oceanography 34, no. 12 (2004): 2721–39. http://dx.doi.org/10.1175/jpo2649.1.

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Abstract Simple Eulerian averaging of velocities, density, and tracers at constant position is the most natural way of averaging. However, Eulerian averaging gives incorrect watermass distributions and properties as well as spurious diabatic circulations such as the Deacon cell. Instead of averaging at constant height, averaging along isopycnals removes such fictitious mixing and diabatic circulations. Such isopycnal averaging is normally performed at constant latitude, that is, averaging along isopynals as they heave up and down. As a result, height information is lost and the sea surface bec
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Sanders, Jan. "Averaging." Scholarpedia 1, no. 11 (2006): 1760. http://dx.doi.org/10.4249/scholarpedia.1760.

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Zhao, Shangwei, Xinyu Zhang, and Yichen Gao. "Model averaging with averaging covariance matrix." Economics Letters 145 (August 2016): 214–17. http://dx.doi.org/10.1016/j.econlet.2016.06.011.

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Sanders, Paul. "Averaging Sequences." Mathematical Gazette 78, no. 483 (1994): 326. http://dx.doi.org/10.2307/3620209.

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Smith, Scott G. "Recursive Averaging." Mathematics Teacher 108, no. 7 (2015): 553–57. http://dx.doi.org/10.5951/mathteacher.108.7.0553.

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The limit of a recursive sequence in which every term is the average of the preceding two is discovered; conclusions are generalized to similar sequences; and a theorem is referenced in which a general limit formula has been proved.
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Campbell, L. L. "Averaging entropy." IEEE Transactions on Information Theory 41, no. 1 (1995): 338–39. http://dx.doi.org/10.1109/18.370086.

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BREITHARDT, GÜNTER, MARTIN BORGGREFE, and ANTONI MARTINEZ-RUBIO. "Signal Averaging." Annals of the New York Academy of Sciences 601, no. 1 Electrocardio (1990): 180–96. http://dx.doi.org/10.1111/j.1749-6632.1990.tb37300.x.

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Markley, F. Landis, Yang Cheng, John L. Crassidis, and Yaakov Oshman. "Averaging Quaternions." Journal of Guidance, Control, and Dynamics 30, no. 4 (2007): 1193–97. http://dx.doi.org/10.2514/1.28949.

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Dubil, Robert. "Investment Averaging." Journal of Wealth Management 7, no. 4 (2005): 35–42. http://dx.doi.org/10.3905/jwm.2005.470608.

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Harris, W. F. "Averaging Powers." Optometry and Vision Science 77, no. 5 (2000): 235. http://dx.doi.org/10.1097/00006324-200005000-00009.

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Dissertations / Theses on the topic "Averaging"

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Dona', Eleonora <1987&gt. "Dollar Cost Averaging VS Suited Dollar Cost Averaging." Master's Degree Thesis, Università Ca' Foscari Venezia, 2015. http://hdl.handle.net/10579/6960.

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The Dollar Cost Averaging is a strategy based on periodic investment of a fixed amount of money, even small one, into a stock or a portfolio each interval over a given period of time. In this way it may be possible to reduce the volatility effects on the market, since each payments could be done both with positive and with negative conditions. What if the investment is not regular in time, but changes according to the market trend? This thesis project aims to compare the standard Dollar Cost Averaging with a suited plan. The amount of money for each instalment will be kept the same as for the
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Ullah, Barkat. "Signal Averaging for Digitizer ADQ214." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-143779.

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Signal averaging is a signal processing technique applied in the time domain, intended to increase the strength of a signal relative to noise that is obscuring it. From a very long sequence of data, a number of smaller data sequences called records are collected. The form of averaging performed in this thesis was not among samples within a record, but among samples from different records. For example, let's say a sample x(n, k) which is a sample n from record k, where 1 &lt;= n &lt;= N and N is the record size, and 1 &lt;= k &lt;= K, where K is the total number of records it would perform the
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Chaput, Philippe. "Approximating Markov processes by averaging." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66654.

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We recast the theory of labelled Markov processes in a new setting, in a way "dual" to the usual point of view. Instead of considering state transitions as a collection of subprobability distributions on the state space, we view them as transformers of real-valued functions. By generalizing the operation of conditional expectation, we build a category consisting of labelled Markov processes viewed as a collection of operators; the arrows of this category behave as projections on a smaller state space. We define a notion of equivalence for such processes, called bisimulation,
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Verra, Christina. "Macroeconomic forecasting using model averaging." Thesis, Queen Mary, University of London, 2009. http://qmro.qmul.ac.uk/xmlui/handle/123456789/383.

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Recently, there has been a broadening concern on forecasting techniques that are applied on large data sets, since economists in business and management want to deal with the great magnitude of information. In this analysis, the issue of forecasting a large data set by using different model averaging approaches is addressed. In particular, Bayesian and frequentist model averaging methods are considered, including Bayesian model averaging (BMA), information theoretic model averaging (ITMA) and predictive likelihood model averaging (PLMA). The predictive performance of each scheme is compared wi
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Rajagopalan, Shreevatsa. "Distributed averaging in dynamic networks." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62315.

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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (p. 39-40).<br>The question of computing average of numbers present at nodes in a network in a distributed manner using gossip or message-passing algorithms has been of great recent interest across disciplines -- algorithms, control and
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Li, Lan (Simone). "Disparity averaging mechanisms in stereopsis." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2007. http://wwwlib.umi.com/cr/syr/main.

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Afsari, Bijan. "Means and averaging on riemannian manifolds." College Park, Md. : University of Maryland, 2009. http://hdl.handle.net/1903/9978.

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Thesis (Ph.D.) -- University of Maryland, College Park, 2009.<br>Thesis research directed by: Dept. of Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Pan, Fei. "Multifrequency Averaging in Power Electronic Systems." UKnowledge, 2014. http://uknowledge.uky.edu/ece_etds/62.

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Power electronic systems have been widely used in the electrical power processing for applications with power levels ranging from less than one watt in battery-operated portable devices to more than megawatts in the converters, inverters and rectifiers of the utility power systems. These systems typically involve the passive elements such as inductors, capacitors, and resistors, the switching electronic components such as IGBTs, MOSFETS, and diodes, and other electronic circuits. Multifrequency averaging is one of the widely used modeling and simulation techniques today for the analysis and de
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Amini, Moghadam Shahram. "Model Uncertainty & Model Averaging Techniques." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/28398.

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The primary aim of this research is to shed more light on the issue of model uncertainty in applied econometrics in general and cross-country growth as well as happiness and well-being regressions in particular. Model uncertainty consists of three main types: theory uncertainty, focusing on which principal determinants of economic growth or happiness should be included in a model; heterogeneity uncertainty, relating to whether or not the parameters that describe growth or happiness are identical across countries; and functional form uncertainty, relating to which growth and well-being regresso
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Noble, Robert Bruce. "Multivariate Applications of Bayesian Model Averaging." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/30180.

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The standard methodology when building statistical models has been to use one of several algorithms to systematically search the model space for a good model. If the number of variables is small then all possible models or best subset procedures may be used, but for data sets with a large number of variables, a stepwise procedure is usually implemented. The stepwise procedure of model selection was designed for its computational efficiency and is not guaranteed to find the best model with respect to any optimality criteria. While the model selected may not be the best possible of those in the
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Books on the topic "Averaging"

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Edleson, Michael E. Value Averaging. John Wiley & Sons, Ltd., 2006.

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Fletcher, David. Model Averaging. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-58541-2.

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United States. Internal Revenue Service. Income averaging. 8th ed. Dept. of the Treasury, Internal Revenue Service, 1985.

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Lowry, Malcolm, ed. Averaging Insight. 2nd ed. Letters, 2005.

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Zhu, Wei-Qiu, Mao-Lin Deng, and Guo-Qiang Cai. Stochastic Averaging. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3829-1.

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Kagan, R. L. Averaging of Meteorological Fields. Edited by Lev S. Gandin and Thomas M. Smith. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8820-1.

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Hapaev, M. M. Averaging in Stability Theory. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2644-1.

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Kagan, Ruvim Leĭzerovich. Averaging of meteorological fields. Kluwer Academic Publishers, 1997.

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S, Gandin L., and Smith Thomas M, eds. Averaging of meteorological fields. Kluwer Academic, 1997.

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Woźniak, Czesław. Averaging techniques in thermomechanics of composite solids: Tolerance averaging versus homogenization. Wydawn. politechniki Częstochowskiej, 2000.

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Book chapters on the topic "Averaging"

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Andrianov, I., J. Awrejcewicz, and L. I. Manevitch. "Averaging." In Foundations of Engineering Mechanics. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-45246-1_8.

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Skorokhod, Anatoli V., Frank C. Hoppensteadt, and Habib Salehi. "Averaging." In Applied Mathematical Sciences. Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-22446-6_4.

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Chicone, Carmen. "Averaging." In Texts in Applied Mathematics. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-51652-8_10.

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Jähne, Bernd. "Averaging." In Digital Image Processing. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04781-1_11.

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Rand, Richard H., and Dieter Armbruster. "Averaging." In Perturbation Methods, Bifurcation Theory and Computer Algebra. Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-1060-3_5.

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Fletcher, David. "Why Model Averaging?" In Model Averaging. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-58541-2_1.

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Fletcher, David. "Bayesian Model Averaging." In Model Averaging. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-58541-2_2.

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Fletcher, David. "Frequentist Model Averaging." In Model Averaging. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-58541-2_3.

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Fletcher, David. "Summary and Future Directions." In Model Averaging. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-58541-2_4.

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Zhu, Wei-Qiu, Mao-Lin Deng, and Guo-Qiang Cai. "Stochastic Averaging Methods of Single-Degree-Of-Freedom Systems." In Stochastic Averaging. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-3829-1_4.

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Conference papers on the topic "Averaging"

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Van Baren, John. "Random Averaging." In SAE 2015 Noise and Vibration Conference and Exhibition. SAE International, 2015. http://dx.doi.org/10.4271/2015-01-2213.

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Bodas, Shreeshankar, and Devavrat Shah. "Fast averaging." In 2011 IEEE International Symposium on Information Theory - ISIT. IEEE, 2011. http://dx.doi.org/10.1109/isit.2011.6033939.

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Barbosa, Samuel, Dan Cosley, Amit Sharma, and Roberto M. Cesar. "Averaging Gone Wrong." In WWW '16: 25th International World Wide Web Conference. International World Wide Web Conferences Steering Committee, 2016. http://dx.doi.org/10.1145/2872427.2883083.

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Potey, M. A., and N. V. Upasani. "Generalized ring averaging." In ICWET '10: International Conference and Workshop on Emerging Trends in Technology. ACM, 2010. http://dx.doi.org/10.1145/1741906.1741951.

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Dibaji, Seyed Mehran, Mostafa Safi, and Hideaki Ishii. "Resilient Distributed Averaging." In 2019 American Control Conference (ACC). IEEE, 2019. http://dx.doi.org/10.23919/acc.2019.8814959.

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Su, Han-I., and Abbas El Gamal. "Distributed lossy averaging." In 2009 IEEE International Symposium on Information Theory - ISIT. IEEE, 2009. http://dx.doi.org/10.1109/isit.2009.5205877.

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Sun, Shaoyuan, and Haitao Zhao. "Kernel Averaging Filter." In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.591.

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Chen, Yu, Ji Zhao, and Laurent Kneip. "Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach." In 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2021. http://dx.doi.org/10.1109/cvpr46437.2021.01022.

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Tsai, Chun-Ming, and Zong-Mu Yeh. "Fast Spatial Averaging Filter." In 2012 International Symposium on Computer, Consumer and Control (IS3C). IEEE, 2012. http://dx.doi.org/10.1109/is3c.2012.47.

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King, P. R. "Effective Values in Averaging." In Mathematics in Oil Production. European Association of Geoscientists & Engineers, 1987. http://dx.doi.org/10.3997/2214-4609-pdb.235.006.

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Reports on the topic "Averaging"

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Sepke, S. Inverse Bremsstrahlung Averaging. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1888624.

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Steinerberger, Stefan, and Aleh Tsyvinski. On Vickrey’s Income Averaging. National Bureau of Economic Research, 2020. http://dx.doi.org/10.3386/w27024.

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Soanes, Royce. Function Smoothing by Repeated Averaging. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada196575.

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Chen, Xiaohong, David Jacho-Chávez, and Oliver Linton. Averaging of moment condition estimators. Institute for Fiscal Studies, 2012. http://dx.doi.org/10.1920/wp.cem.2012.2612.

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Banternghansa, Chanont, and Michael W. McCracken. Real-Time Forecast Averaging with ALFRED. Federal Reserve Bank of St. Louis, 2010. http://dx.doi.org/10.20955/wp.2010.033.

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McCracken, Michael W., and Todd E. Clark. Averaging Forecasts from VARs with Uncertain Instabilities. Federal Reserve Bank of St. Louis, 2008. http://dx.doi.org/10.20955/wp.2008.030.

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McCallen, R. C. Time averaging of instantaneous quantities in HYDRA. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/453332.

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Ernst, R. E., and G. W. Pearce. Averaging of Anisotropy of Magnetic Susceptibility Data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128071.

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Yost, G. P. Averaging in the presence of sliding errors. Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/79719.

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Crockett, Carl E. An Introduction to the Method of Averaging. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada258990.

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