Results 61 to 70 of about 318 (139)

Research on Series Arc Fault Detection Based on Higher-Order Cumulants

IEEE Access, 2019
At present, the detection methods on series arc faults are mainly based on the current of the main circuit, which probably results in misjudgment because of the singularity of the normal working current in a nonlinear load.
Guanghai Bao, Run Jiang, Dejun Liu
doaj   +1 more source

Variance Ratio Tests for Panels With Cross‐Section Dependence

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT This paper develops panel variance ratio statistics to examine serial dependence in time series with cross‐sectional dependence. We derive asymptotic properties for panels where the cross‐section dimension N$$ N $$ is fixed or grows with T. Using a factor structure to explain cross‐sectional dependence, we propose a common correlation effects ...
Seongman Moon, Carlos Velasco
wiley   +1 more source

Cumulant-Based Coherent Signal Subspace Method for Bearing and Range Estimation

EURASIP Journal on Advances in Signal Processing, 2007
A new method for simultaneous range and bearing estimation for buried objects in the presence of an unknown Gaussian noise is proposed. This method uses the MUSIC algorithm with noise subspace estimated by using the slice fourth-order cumulant matrix of ...
Salah Bourennane, Zineb Saidi
doaj   +2 more sources

Time Averaged CCE

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT A popular approach to interactive effects panel data models is the common correlated effects (CCE) estimator of Pesaran (Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012, 2006). The current paper proposes a modified version of this estimator that is useful in a number of cases
Yousef Kaddoura, Yiannis Karavias, Joakim Westerlund   +2 more
wiley   +1 more source

Buffer and salt dependent reassembly pathways of Myxococcus xanthus encapsulin

Protein Science, Volume 35, Issue 9, September 2026.
Abstract Protein cages that adopt multiple assembly states provide tractable systems for probing the mechanisms that govern icosahedral shell formation. The Myxococcus xanthus encapsulin shell protein assembles into either a T = 1 shell (60 subunits) or a T = 3 shell (180 subunits), making it an ideal model to investigate how solution conditions bias ...
Varnika Yadav, Tobias Beck
wiley   +1 more source

A Cumulative Study on Differential Transform Method

International Journal of Mathematical, Engineering and Management Sciences, 2019
Many real-world phenomena when modelled as a differential equation don't generally have exact solutions, so their numerical or analytic solutions are sought after. Differential transform method (DTM) is one of the analytical methods that gives the solution in the form of a power series. In this paper, a cumulative study is done on DTM and its evolution
Geeta Arora, Pratiksha
openaire   +2 more sources

Multiuser Channel Estimation from Higher-Order Statistical Matrix Pencil

EURASIP Journal on Advances in Signal Processing, 2002
This paper presents a new statistical approach to the blind estimation of linear multiple-input multiple-output (MIMO) channels with finite impulse response.
Liang Jing, Ding Zhi
doaj   +1 more source

Wavelet‐Based Hurst Exponent Estimation

WIREs Computational Statistics, Volume 18, Issue 3, September 2026.
The review explores how wavelet‐based methods for estimating the Hurst parameters have developed from their theoretical roots to real‐world applications in fields like biology, engineering, and telecommunications. The review aims to highlight key techniques, compare their strengths and limitations, and point out challenges that still need to be ...
Dixon Vimalajeewa, Fabrizio Ruggeri, Brani Vidakovic   +2 more
wiley   +1 more source

Isolation of flow and nonflow correlations by two- and four-particle cumulant measurements of azimuthal harmonics in sNN=200 GeV Au+Au collisions

Physics Letters B, 2015
A data-driven method was applied to Au+Au collisions at sNN=200 GeV made with the STAR detector at RHIC to isolate pseudorapidity distance Δη-dependent and Δη-independent correlations by using two- and four-particle azimuthal cumulant measurements.
N.M. Abdelwahab, L. Adamczyk, J.K. Adkins, G. Agakishiev, M.M. Aggarwal, Z. Ahammed, I. Alekseev, J. Alford, C.D. Anson, A. Aparin, D. Arkhipkin, E.C. Aschenauer, G.S. Averichev, A. Banerjee, D.R. Beavis, R. Bellwied, A. Bhasin, A.K. Bhati, P. Bhattarai, J. Bielcik, J. Bielcikova, L.C. Bland, I.G. Bordyuzhin, W. Borowski, J. Bouchet, A.V. Brandin, S.G. Brovko, S. Bültmann, I. Bunzarov, T.P. Burton, J. Butterworth, H. Caines, M. Calderón de la Barca Sánchez, J.M. Campbell, D. Cebra, R. Cendejas, M.C. Cervantes, P. Chaloupka, Z. Chang, S. Chattopadhyay, H.F. Chen, J.H. Chen, L. Chen, J. Cheng, M. Cherney, A. Chikanian, W. Christie, M.J.M. Codrington, G. Contin, J.G. Cramer, H.J. Crawford, X. Cui, S. Das, A. Davila Leyva, L.C. De Silva, R.R. Debbe, T.G. Dedovich, J. Deng, A.A. Derevschikov, R. Derradi de Souza, B. di Ruzza, L. Didenko, C. Dilks, F. Ding, P. Djawotho, X. Dong, J.L. Drachenberg, J.E. Draper, C.M. Du, L.E. Dunkelberger, J.C. Dunlop, L.G. Efimov, J. Engelage, K.S. Engle, G. Eppley, L. Eun, O. Evdokimov, O. Eyser, R. Fatemi, S. Fazio, J. Fedorisin, P. Filip, Y. Fisyak, C.E. Flores, C.A. Gagliardi, D.R. Gangadharan, D. Garand, F. Geurts, A. Gibson, M. Girard, S. Gliske, L. Greiner, D. Grosnick, D.S. Gunarathne, Y. Guo, A. Gupta, S. Gupta, W. Guryn, B. Haag, A. Hamed, L-X. Han, R. Haque, J.W. Harris, S. Heppelmann, A. Hirsch, G.W. Hoffmann, D.J. Hofman, S. Horvat, B. Huang, H.Z. Huang, X. Huang, P. Huck, T.J. Humanic, G. Igo, W.W. Jacobs, H. Jang, E.G. Judd, S. Kabana, D. Kalinkin, K. Kang, K. Kauder, H.W. Ke, D. Keane, A. Kechechyan, A. Kesich, Z.H. Khan, D.P. Kikola, I. Kisel, A. Kisiel, D.D. Koetke, T. Kollegger, J. Konzer, I. Koralt, L.K. Kosarzewski, L. Kotchenda, A.F. Kraishan, P. Kravtsov, K. Krueger, I. Kulakov, L. Kumar, R.A. Kycia, M.A.C. Lamont, J.M. Landgraf, K.D. Landry, J. Lauret, A. Lebedev, R. Lednicky, J.H. Lee, C. Li, W. Li, X. Li, X. Li, Y. Li, Z.M. Li, M.A. Lisa, F. Liu, T. Ljubicic, W.J. Llope, M. Lomnitz, R.S. Longacre, X. Luo, G.L. Ma, Y.G. Ma, D.P. Mahapatra, R. Majka, S. Margetis, C. Markert, H. Masui, H.S. Matis, D. McDonald, T.S. McShane, N.G. Minaev, S. Mioduszewski, B. Mohanty, M.M. Mondal, D.A. Morozov, M.K. Mustafa, B.K. Nandi, Md. Nasim, T.K. Nayak, J.M. Nelson, G. Nigmatkulov, L.V. Nogach, S.Y. Noh, J. Novak, S.B. Nurushev, G. Odyniec, A. Ogawa, K. Oh, A. Ohlson, V. Okorokov, E.W. Oldag, D.L. Olvitt, Jr., B.S. Page, Y.X. Pan, Y. Pandit, Y. Panebratsev, T. Pawlak, B. Pawlik, H. Pei, C. Perkins, P. Pile, M. Planinic, J. Pluta, N. Poljak, K. Poniatowska, J. Porter, A.M. Poskanzer, N.K. Pruthi, M. Przybycien, J. Putschke, H. Qiu, A. Quintero, S. Ramachandran, R. Raniwala, S. Raniwala, R.L. Ray, C.K. Riley, H.G. Ritter, J.B. Roberts, O.V. Rogachevskiy, J.L. Romero, J.F. Ross, A. Roy, L. Ruan, J. Rusnak, O. Rusnakova, N.R. Sahoo, P.K. Sahu, I. Sakrejda, S. Salur, A. Sandacz, J. Sandweiss, E. Sangaline, A. Sarkar, J. Schambach, R.P. Scharenberg, A.M. Schmah, W.B. Schmidke, N. Schmitz, J. Seger, P. Seyboth, N. Shah, E. Shahaliev, P.V. Shanmuganathan, M. Shao, B. Sharma, W.Q. Shen, S.S. Shi, Q.Y. Shou, E.P. Sichtermann, M. Simko, M.J. Skoby, D. Smirnov, N. Smirnov, D. Solanki, P. Sorensen, H.M. Spinka, B. Srivastava, T.D.S. Stanislaus, J.R. Stevens, R. Stock, M. Strikhanov, B. Stringfellow, M. Sumbera, X. Sun, X.M. Sun, Y. Sun, Z. Sun, B. Surrow, D.N. Svirida, T.J.M. Symons, M.A. Szelezniak, J. Takahashi, A.H. Tang, Z. Tang, T. Tarnowsky, J.H. Thomas, A.R. Timmins, D. Tlusty, M. Tokarev, S. Trentalange, R.E. Tribble, P. Tribedy, B.A. Trzeciak, O.D. Tsai, J. Turnau, T. Ullrich, D.G. Underwood, G. Van Buren, G. van Nieuwenhuizen, M. Vandenbroucke, J.A. Vanfossen, Jr., R. Varma, G.M.S. Vasconcelos, A.N. Vasiliev, R. Vertesi, F. Videbæk, Y.P. Viyogi, S. Vokal, A. Vossen, M. Wada, F. Wang, G. Wang, H. Wang, J.S. Wang, X.L. Wang, Y. Wang, Y. Wang, G. Webb, J.C. Webb, G.D. Westfall, H. Wieman, S.W. Wissink, Y.F. Wu, Z. Xiao, W. Xie, K. Xin, H. Xu, J. Xu, N. Xu, Q.H. Xu, Y. Xu, Z. Xu, W. Yan, C. Yang, Y. Yang, Y. Yang, Z. Ye, P. Yepes, L. Yi, K. Yip, I-K. Yoo, N. Yu, H. Zbroszczyk, W. Zha, J.B. Zhang, J.L. Zhang, S. Zhang, X.P. Zhang, Y. Zhang, Z.P. Zhang, F. Zhao, J. Zhao, C. Zhong, X. Zhu, Y.H. Zhu, Y. Zoulkarneeva, M. Zyzak   +348 more
doaj   +1 more source

Adaptive Estimation for Weakly Dependent Functional Times Series

Journal of Time Series Analysis, Volume 47, Issue 5, Page 1013-1027, September 2026.
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro, Valentin Patilea, Myriam Vimond   +2 more
wiley   +1 more source