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Yao Q, Brockwell P, “Gaussian maximum likelihood estimation for ARMA models II: spatial processes”, Bernoulli, Vol.12, No.3, 2006, pp. 403-429.10.3150/bj/1151525128Search in Google Scholar
Krishna, Ramuhalli, “Improved pointing accuracy using high-precision theodolite measurements”, SPIE, Vol.2818, 1998, No.1, pp.199-209.Search in Google Scholar
Wang Jianli, Chen Tao, Qi Chen qne Fang Zhonghua, “Method to improve the capability of electro-optical theodolite to track fast-moving target”, SPIE, Vol. 4564, No.1, 2003, pp. 238-244.Search in Google Scholar
LIU Chanlao, “The research on dynamic tracking and measurement and its computer simulation in shooting range”, Vol.13, No.3, 2001, pp. 455-479.Search in Google Scholar
H.J.Tiziani, “High precision optical measurement methods”, SPIE, Vo1.2248, No.1, 1996, pp.2-18.Search in Google Scholar
C. J. Stone, “Consistent nonparametric regression”, The Annals of Statistics, Vo1.17, No.5, 1977, pp.595-645.10.1214/aos/1176343886Search in Google Scholar
KlEIN L A, “Sensor and data fusion concepts and applications”, SPIE, Optical Engineering Press, Vo1.1848, No.1, 1993, pp.364-389.Search in Google Scholar
W.S.Cleveland, “Robust locally weighted regression and smoothing scatter plots”, Journal of American Statistical Association, Vo1.74, No.2, 1979, pp.829-836.10.1080/01621459.1979.10481038Search in Google Scholar
Hallin M, Lu Z, Tran L.T, “Local linear spatial regression”, Annals of Statistics, Vol.32, No.6, 2004, pp.356-378.10.1214/009053604000000850Search in Google Scholar
Lee L F, “Consistency and efficiency of least squares estimation for mixed regressive”, Spatial Autoregressive Models, Econometric Theory, Vol.18, No.1, 2002, pp.252–277.10.1017/S0266466602182028Search in Google Scholar
E. Masry, J. Fan, “Local polynomial estimation of regression functions for mixing processes”, Scandinavian Journal of Statistics, Vol.24, No.3, 1997, pp.165-179.10.1111/1467-9469.00056Search in Google Scholar
J.Fan,, I.Gijbels, “Local polynomial modelling and its applications”, Chapman& Hall. London, 1996, pp.196-210.Search in Google Scholar
H.Shen, L.Brown, “Nonparametric modelling for time-varying customer service times at a bank call center”, Appl Stoch Models Bus Ind, Vol.22, No.6, 2006, pp.297-311.10.1002/asmb.618Search in Google Scholar
Cliff A, Ord J K, “Spatial processes: models& applications”, London: Pion, pp.1-131, January 1981.Search in Google Scholar
L.Wang, L. Brown, T.Cai, M.Levine, “Effect of mean on variance function estimation in nonparametric regression. Technical report”, Dept. Statistics, Univ. Pennsylvania, Available at:www-stat. wharton. upenn. edu/tcai/paper/html/Variance-Estimation.Html, 2006.Search in Google Scholar
P.Hall, R.Carroll, “Variance function estimation in regression: the effect of estimating the mean”, J. Roy. Statist. Soc. Ser. B, Vol.51, 2006, No.2, pp.3-14.Search in Google Scholar
P.Hall, J.Kay, D.Titterington, “Asymptotically optimal difference-based estimation of variance in nonparametric regression”, Biometrika, Vol.77, No.3, 2006, pp.521-528.10.1093/biomet/77.3.521Search in Google Scholar
S.C.Mukhopadhyay, F.P. Dawson, M. Iwahara and S. Yamada, “A Novel Compact Magnetic Current Limiter for Three Phase Applications”, IEEE Transactions on Magnetics, Vol. 36, No. 5, pp. 3568-3570, September 2000.Search in Google Scholar
Delaigle A,Fan J,Carroll R J,”A design-adaptive local polynomial estimator for the errors-in-variables problem”, Amer.Statist.Assoc,Vol.104 , No.1, 2009, pp. 348–359.10.1198/jasa.2009.0114284638020351800Search in Google Scholar
Comte F, Taupin M L, “Nonparametric estimation of the regression function in an errors-in-variables model”, Statist.Sinica, Vol.17, No.3, 2007, pp.1065–1090.Search in Google Scholar
Meister Alexander, “Deconvolution problems in nonparametric statistics”, Lecture Notes in
Statistics, Springer, Berlin, Heidelberg, 2009, pp.5-138.10.1007/978-3-540-87557-4Search in Google Scholar
S.C.Mukhopadhyay, K. Chomsuwan, C. Gooneratne and S. Yamada, “A Novel Needle-Type SV-GMR Sensor for Biomedical Applications”, IEEE Sensors Journal, Vol. 7, No. 3, pp. 401-408, March 2007.10.1109/JSEN.2007.891929Search in Google Scholar
J. Fan, T. Gasser, I. Gijbels, M. Brockmann and J. Engel, “Local polynomial fitting: optimal kernel and asymptotic minimax efficiency”, Annals of the Institute of Statistical Mathematics, Vol.49, No.2, 1996, pp.79-99.10.1023/A:1003162622169Search in Google Scholar
Masry E., “Deconvolving multivariate kernel density estimates from contaminated associated observations”, IEEE Trans. Inform. Theory, Vol.49. No.11, 2003, pp.2941–2952.10.1109/TIT.2003.818415Search in Google Scholar
Wu W B, Mielniczuk J, “Kernel density estimation for linear processes”, Ann. Statist.,Vol.30, No.5, 2002, pp.1441–1459.10.1214/aos/1035844982Search in Google Scholar
Fan J, Truong Y K, “Nonparametric regression with errors in variables”, Ann. Statist.,Vol.21, No.4, 1993, pp.1900–1925.10.1214/aos/1176349402Search in Google Scholar
K. Muthumeenakshi and S. Radha, “Optimal techniques for sensing error minimization with improved energy detection in cognitive radios”, International Journal on Smart Sensing and Intelligent Systems, Vol 7, No. 4, December 2014, pp. 2014-2034.10.21307/ijssis-2017-745Search in Google Scholar
S. Yamada, K. Chomsuwan, S.C.Mukhopadhyay, M. Iwahara, M. Kakikawa and I. Nagano, “Detection of Magnetic Fluid Volume Density with a GMR Sensor”, Journal of Magnetics Society of Japan, Vol. 31, No. 2, pp. 44-47, 2007.10.3379/jmsjmag.31.44Search in Google Scholar
Mielniczuk J, Wu W B, “On random-design model with dependent errors”, Statist. Sinica.,Vol. 14, No.4, 2004, pp.1105–1126.Search in Google Scholar
Kulik R., “Nonparametric deconvolution problem for dependent sequences”, Electron. J.Statist., Vol. 2, No.3, 2008, pp.722–740.10.1214/07-EJS154Search in Google Scholar
Biswajit Panja, Zachary Scott and Priyanka Meharia, “Security of wireless sensor networks for health monitoring helmets with anomaly detection using power analysis and probabilistic model”, International Journal on Smart Sensing and Intelligent Systems, Vol 8, No. 1, March 2015, pp. 561-580.Search in Google Scholar
