Academic literature on the topic 'Frequency averaging'
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Journal articles on the topic "Frequency averaging"
Khitrin, A. K., Jiadi Xu, and Ayyalusamy Ramamoorthy. "Coherent averaging in the frequency domain." Journal of Chemical Physics 136, no. 21 (June 7, 2012): 214504. http://dx.doi.org/10.1063/1.4723682.
Full textIde, Hideto, and Masafumi Uchida. "Analysis of Recognition Processes by Measurement of Brain Waves and Temperature Distributions." Journal of Robotics and Mechatronics 4, no. 1 (February 20, 1992): 63–69. http://dx.doi.org/10.20965/jrm.1992.p0063.
Full textPinnau, René, and Alexander Schulze. "Radiation, Frequency Averaging and Proper Orthogonal Decomposition." PAMM 6, no. 1 (December 2006): 791–94. http://dx.doi.org/10.1002/pamm.200610376.
Full textIKAWA, NOBUKO. "AUTOMATED AVERAGING OF AUDITORY EVOKED RESPONSE WAVEFORMS USING WAVELET ANALYSIS." International Journal of Wavelets, Multiresolution and Information Processing 11, no. 04 (July 2013): 1360009. http://dx.doi.org/10.1142/s0219691313600096.
Full textHansen, A. C., and T. E. Hausfeld. "Frequency-Response Matching to Optimize Wind-Turbine Test Data Correlation." Journal of Solar Energy Engineering 108, no. 3 (August 1, 1986): 246–51. http://dx.doi.org/10.1115/1.3268100.
Full textLuque, Alejandro, and Jordi Villanueva. "Quasi-Periodic Frequency Analysis Using Averaging-Extrapolation Methods." SIAM Journal on Applied Dynamical Systems 13, no. 1 (January 2014): 1–46. http://dx.doi.org/10.1137/130920113.
Full textWeitenberg, Erik, Claudio De Persis, and Nima Monshizadeh. "Exponential convergence under distributed averaging integral frequency control." Automatica 98 (December 2018): 103–13. http://dx.doi.org/10.1016/j.automatica.2018.09.010.
Full textSen, Surojit, Paul L. Evans, and C. Mark Johnson. "Multi‐frequency averaging (MFA) model of a generic electric vehicle powertrain suitable under variable frequency of averaging developed for remote operability." IET Electrical Systems in Transportation 10, no. 3 (September 2020): 268–74. http://dx.doi.org/10.1049/iet-est.2019.0043.
Full textGiannoulis, Johannes, Alexander Mielke, and Christof Sparber. "High-frequency averaging in semi-classical Hartree-type equations." Asymptotic Analysis 70, no. 1-2 (2010): 87–100. http://dx.doi.org/10.3233/asy-2010-1007.
Full textDolganov, M. V. "High-frequency sampling error of averaging digital phase meters." Measurement Techniques 30, no. 4 (April 1987): 379–82. http://dx.doi.org/10.1007/bf00864771.
Full textDissertations / Theses on the topic "Frequency averaging"
Zhang, Xuan. "High Precision Dynamic Power System Frequency Estimation Algorithm Based on Phasor Approach." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/31001.
Full textMaster of Science
Gartmark, Joakim. "On Optimal Sample-Frequency and Model-Averaging Selection When Predicting Realized Volatility." Thesis, Stockholms universitet, Nationalekonomiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-147483.
Full textGreen, Jr Donald Lee. "ANALYSIS OF THE EFFECTS OF ATROPINE AND SALINE ON THE HRV OF RATS USING ENSEMBLE AVERAGING AND FREQUENCY ANALYSIS." MSSTATE, 2008. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07102008-123307/.
Full textCarrier, Denis Joseph Gaston. "Automatic measurement of particles from holograms taken in the combustion chamber of a rocket motor." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/22924.
Full textThis thesis describes the procedure used for the automatic measurement of particles from hologram taken in the combustion chamber of a rocket motor while firing. It describes the investigation done on two averaging techniques used to reduce speckle noise, capturing the image focused on a spinning mylar disk and software averaging of several image frames. The spinning disk technique proved superior for this application. The Kolmogorov-Smirnov two-sample test is applied to different particle samples in order to find an estimate of the number of particles required to obtain a stable distribution function. The number of particles is calculated and given. The last part of this study shows real particle distributions in the form of frequency histograms.
http://archive.org/details/automaticmeasure00carr
Major, Canadian Armed Forces
Sarini, Sarini. "Statistical methods for modelling falls and symptoms progression in patients with early stages of Parkinson's disease." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/116208/1/_Sarini_Thesis.pdf.
Full textRosander, Peter. "Averaging level control in the presence of frequent inlet flow upsets." Licentiate thesis, Linköpings universitet, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-77049.
Full textJebai, Al Kassem. "Commande sans capteur des moteurs synchrones à aimants permanents par injection de signaux." Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2013. http://pastel.archives-ouvertes.fr/pastel-00818400.
Full textGross, Tadeu Junior. "Structure learning of Bayesian networks via data perturbation." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-19022019-134517/.
Full textO aprendizado da estrutura de uma Rede Bayesiana (BN) é um problema NP-difícil, e o uso de estratégias sub-ótimas é essencial em domínios que envolvem muitas variáveis. Uma delas consiste em gerar várias estruturas aproximadas e depois reduzir o conjunto a uma estrutura representativa. É possível usar a frequência de ocorrência (no conjunto de estruturas) como critério para aceitar um arco dominante entre dois nós e assim obter essa estrutura única. Nesta pesquisa de doutorado, foi feita uma analogia com um passeio aleatório unidimensional adaptado para deduzir analiticamente um limiar de decisão apropriado para essa frequência de ocorrência. A expressão de forma fechada obtida foi validada usando bases de dados de referência e aplicando o Coeficiente de Correlação de Matthews como métrica de desempenho. Nos experimentos utilizando dados médicos recentes, a BN resultante da frequência de corte analítica capturou as associações esperadas entre os nós e também obteve melhor desempenho de predição do que as BNs aprendidas com limiares vizinhos ao calculado. Na literatura, a característica contabilizada ao longo das estruturas perturbadas tem sido as arestas e não as arestas direcionadas (arcos) como nesta tese. Essa estratégia modificada ainda foi aplicada a um conjunto de dados de idosos para identificar potenciais relações entre variáveis de interesse médico, mas usando um limiar aumentado em vez do previsto pela fórmula proposta - essa cautela deve-se às possíveis implicações sociais do achado. A motivação por trás dessa aplicação é que, apesar da proporção de idosos na população ter aumentado substancialmente nas últimas décadas, os fatores de risco que devem ser controlados com antecedência para garantir um processo natural de declínio mental devido ao envelhecimento permanecem desconhecidos. No modelo estrutural aprendido, investigou-se graficamente o mecanismo de dependência probabilística entre duas variáveis de interesse médico: o fator de risco suspeito conhecido como Síndrome Metabólica e o indicador de declínio mental denominado Comprometimento Cognitivo. Nessa investigação, empregou-se o conceito conhecido no contexto de BNs como D-separação. Esse estudo revelou que a dependência entre Síndrome Metabólica e Variáveis Cognitivas de fato existe e depende tanto do Índice de Massa Corporal quanto da idade.
D'AMICO, ROBERTO. "Efficient frequency averaging techniques for noise and vibration simulations." Doctoral thesis, 2014. http://hdl.handle.net/2158/872926.
Full textHounyo, Koomla Ulrich. "Bootstrapping high frequency data." Thèse, 2013. http://hdl.handle.net/1866/10217.
Full textWe develop in this thesis bootstrap methods for high frequency financial data. The first two chapters focalise on bootstrap methods for the "pre-averaging" approach, which is robust to the presence of market microstructure effects. The main idea underlying this approach is that we can reduce the impact of the noise by pre-averaging high frequency returns that are possibly contaminated with market microstructure noise before applying a realized volatility-like statistic. Based on this approach, we develop several bootstrap methods, which preserve the dependence structure and the heterogeneity in the mean of the original data. The third chapter shows how and to what extent the local Gaussian- ity assumption can be explored to generate a bootstrap approximation for covolatility measures. The first chapter is entitled "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns". The main contribution of this chapter is to propose bootstrap methods for realized volatility-like estimators defined on pre-averaged returns. In particular, we focus on the pre-averaged realized volatility estimator proposed by Podolskij and Vetter (2009). This statistic can be written (up to a bias correction term) as the (scaled) sum of squared pre-averaged returns, where the pre-averaging is done over all possible non-overlapping blocks of consecutive observations. Pre-averaging reduces the influence of the noise and allows for realized volatility estimation on the pre-averaged returns. The non-overlapping nature of the pre-averaged returns implies that these are asymptotically independent, but possibly heteroskedastic. This motivates the application of the wild bootstrap in this context. We provide a proof of the first order asymptotic validity of this method for percentile and percentile-t intervals. Our Monte Carlo simulations show that the wild bootstrap can improve the finite sample properties of the existing first order asymptotic theory provided we choose the external random variable appropriately. The second chapter is entitled "Bootstrapping pre-averaged realized volatility under market microstructure noise ". In this chapter we propose a bootstrap method for inference on integrated volatility based on the pre-averaging approach of Jacod et al. (2009), where the pre-averaging is done over all possible overlapping blocks of consecutive observations. The overlapping nature of the pre-averaged returns implies that these are m-dependent with m growing slowly with the sample size n. This motivates the application of a blockwise bootstrap method. We show that the “blocks of blocks” bootstrap method suggested by Politis and Romano (1992) (and further studied by Bühlmann and Künsch (1995)) is valid only when volatility is constant. The failure of the blocks of blocks bootstrap is due to the heterogeneity of the squared pre-averaged returns when volatility is stochastic. To preserve both the dependence and the heterogeneity of squared pre-averaged returns, we propose a novel procedure that combines the wild bootstrap with the blocks of blocks bootstrap. We provide a proof of the first order asymptotic validity of this method for percentile intervals. Our Monte Carlo simulations show that the wild blocks of blocks bootstrap improves the finite sample properties of the existing first order asymptotic theory. The third chapter is entitled "Bootstrapping realized volatility and realized beta under a local Gaussianity assumption". The financial econometric of high frequency data litera- ture often assumed a local constancy of volatility and the Gaussianity properties of high frequency returns in order to carry out inference. In this chapter, we show how and to what extent the local Gaussianity assumption can be explored to generate a bootstrap approximation. We show the first-order asymptotic validity of the new wild bootstrap method, which uses the conditional local normality properties of financial high frequency returns. In addition to that we use Edgeworth expansions and Monte Carlo simulations to compare the accuracy of the bootstrap with other existing approaches. It is shown that at second order, the new wild bootstrap matches the cumulants of realized betas-based t-statistics, whereas it provides a third-order asymptotic refinement for realized volatility. Monte Carlo simulations suggest that our new wild bootstrap methods improve upon the first-order asymptotic theory in finite samples and outperform the existing bootstrap methods for realized covolatility measures. We use empirical work to illustrate its uses in practice.
Books on the topic "Frequency averaging"
Khapaev, M. M. Averaging in stability theory: A study of resonance multi-frequency systems. Dordrecht: Kluwer Academic Publishers, 1993.
Find full textHapaev, M. M. Averaging in Stability Theory: A Study of Resonance Multi-Frequency Systems (Mathematics and its Applications). Springer, 1992.
Find full textCongendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.
Full textIsett, Philip. The Euler-Reynolds System. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691174822.003.0001.
Full textFacca, Joseph Bruno. "In vitro" characterization of the maximum and mean frequency wave forms of the CW Doppler spectrum from a corotid artery model using DFT analysis and ensemble averaging. 1986.
Find full textIsett, Philip. The Coarse Scale Flow and Commutator Estimates. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691174822.003.0016.
Full textBook chapters on the topic "Frequency averaging"
Weik, Martin H. "frequency averaging." In Computer Science and Communications Dictionary, 644. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_7606.
Full textHapaev, M. M. "Stability of Multi — Frequency Systems." In Averaging in Stability Theory, 114–39. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2644-1_4.
Full textHapaev, M. M. "Averaging of Ordinary Differential Equations in One — and Multi — Frequency Systems." In Averaging in Stability Theory, 1–18. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2644-1_1.
Full textAkulenko, Leonid D. "Averaging Method in Optimal Control Problems for Single-Frequency Essentially Nonlinear Systems." In Problems and Methods of Optimal Control, 97–134. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1194-2_3.
Full textSanders, Jan A., and Ferdinand Verhulst. "Averaging over Spatial Variables: Systems with Slowly Varying Frequency and Passage through Resonance." In Applied Mathematical Sciences, 83–123. New York, NY: Springer New York, 1985. http://dx.doi.org/10.1007/978-1-4757-4575-7_5.
Full textGuschina, Oksana, Timofey Shevgunov, Evgeniy Efimov, and Vladimir Kirdyashkin. "The Exact Frequency Domain Solution for the Periodic Synchronous Averaging Performed in Discrete-Time." In Computational Statistics and Mathematical Modeling Methods in Intelligent Systems, 167–75. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31362-3_17.
Full textKlimina, Liubov, Ekaterina Shalimova, Marat Dosaev, Boris Lokshin, and Vitaly Samsonov. "Two-Frequency Averaging in the Problem of Motion of a Counter-Rotating Vertical Axis Wind Turbine." In Springer Proceedings in Mathematics & Statistics, 183–92. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96598-7_15.
Full textTony Fischer, R. A. "History of Wheat Breeding: A Personal View." In Wheat Improvement, 17–30. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90673-3_2.
Full textWeaver, James C., Timothy E. Vaughan, Robert K. Adair, and R. Dean Astumian. "Altered Cumulative Calcium Influx for Biological Cells: An Illustration of the Theory of Signal Averaging by Rectification of Weak Extremely Low Frequency Electric Fields." In Electricity and Magnetism in Biology and Medicine, 319–22. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4867-6_73.
Full textPronin, A., and D. Treschev. "Averaging in multi–frequency slow–fast systems." In Equadiff 99, 955–60. World Scientific Publishing Company, 2000. http://dx.doi.org/10.1142/9789812792617_0187.
Full textConference papers on the topic "Frequency averaging"
Zaplata, Filip, and Miroslav Kasal. "Spectrum averaging carrier frequency estimation." In 2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA. IEEE, 2015. http://dx.doi.org/10.1109/radioelek.2015.7129027.
Full textYimin Zhang and M. G. Amin. "Spatial averaging of time-frequency distributions." In 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258). IEEE, 1999. http://dx.doi.org/10.1109/icassp.1999.756227.
Full textAdachi, Kentaro, Haruo Suemitsu, and Takami Matsuo. "LMI-Based Frequency Estimator with Averaging." In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icicic.2007.370.
Full textYan, Hongxiang, and Hamid Moradkhani. "Bayesian Model Averaging for Flood Frequency Analysis." In World Environmental and Water Resources Congress 2014. Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413548.189.
Full textStovas, A., and Y. Roganov. "Low-frequency extension of the Backus averaging method." In 12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15-18 August 2011. Society of Exploration Geophysicists and Brazilian Geophysical Society, 2011. http://dx.doi.org/10.1190/sbgf2011-361.
Full textWear, Keith, and Anant Shah. "Hydrophone Spatial Averaging Correction for High-Frequency Arrays." In 2022 IEEE International Ultrasonics Symposium (IUS). IEEE, 2022. http://dx.doi.org/10.1109/ius54386.2022.9957622.
Full textKammer, Christoph, and Alireza Karimi. "Robust distributed averaging frequency control of inverter-based microgrids." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7799029.
Full textNadeu, Climent, Felix Galindo, and Jaume Padrell. "On frequency averaging for spectral analysis in speech recognition." In 5th International Conference on Spoken Language Processing (ICSLP 1998). ISCA: ISCA, 1998. http://dx.doi.org/10.21437/icslp.1998-541.
Full textRohaly, Ann Marie, and Hugh R. Wilson. "Disparity averaging across spatial scales." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.fkk3.
Full textYu, J., T. Legero, F. Riehle, C. Y. Ma, S. Herbers, D. Nicolodi, D. Kedar, E. Oelker, J. Ye, and U. Sterr. "A Simple Frequency Stabilization Technique for Averaging Birefringent Noise in Crystalline Mirror Coatings." In 2022 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium (EFTF/IFCS). IEEE, 2022. http://dx.doi.org/10.1109/eftf/ifcs54560.2022.9850735.
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