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Almost sure convergence of classification procedures using Hermite series density estimates

Pattern recognition letters, 1983-10, Vol.2 (1), p.13-17

1983

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Asymptotic efficiency of classifying procedures using the Hermite series estimate of multivariate probability densities (Corresp.)

IEEE transactions on information theory, 1981-05, Vol.27 (3), p.364-366

Greblicki, W.

1981

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Asymptotic properties of kernel estimates of a regression function

Journal of statistical planning and inference, 1980, Vol.4 (1), p.81-90

1980

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Asymptotically optimal pattern recognition procedures with density estimates (Corresp.)

IEEE transactions on information theory, 1978-03, Vol.24 (2), p.250-251

Greblicki, W.

1978

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Cascade non-linear system identification by a non-parametric method

International journal of systems science, 1994-01, Vol.25 (1), p.129-153

1994

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A classification procedure using the multiple Fourier series

Information sciences, 1982-01, Vol.26 (2), p.115-126

1982

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Continuous-time Hammerstein system identification

IEEE transactions on automatic control, 2000-06, Vol.45 (6), p.1232-1236

Greblicki, W.

2000

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Continuous-time Hammerstein system identification from sampled data

IEEE transactions on automatic control, 2006-07, Vol.51 (7), p.1195-1200

Greblicki, W.

2006

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Continuous-time Wiener system identification

IEEE transactions on automatic control, 1998-10, Vol.43 (10), p.1488-1493

Greblicki, W.

1998

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Density-free Bayes risk consistency of nonparametric pattern recognition procedures

Proceedings of the IEEE, 1981-01, Vol.69 (4), p.482-483

1981

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Distribution-Free Pointwise Consistency of Kernel Regression Estimate

The Annals of statistics, 1984-12, Vol.12 (4), p.1570-1575

1984

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Dynamic system identification with order statistics

IEEE transactions on information theory, 1994-09, Vol.40 (5), p.1474-1489

1994

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Hammerstein system identification by non-parametric regression estimation

International journal of control, 1987-01, Vol.45 (1), p.343-354

1987

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Hammerstein System Identification With the Nearest Neighbor Algorithm

IEEE transactions on information theory, 2017-08, Vol.63 (8), p.4746-4757

2017

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Identification of discrete Hammerstein systems using kernel regression estimates

IEEE transactions on automatic control, 1986-01, Vol.31 (1), p.74-77

1986

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Input Nonlinearity Recovering in a Class of Systems

IEEE transactions on automatic control, 2009-07, Vol.54 (7), p.1714-1717

Greblicki, W.

2009

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Learning to recognize patterns with a probabilistic teacher

Pattern recognition, 1980, Vol.12 (3), p.159-164

Greblicki, Włodzimierz

1980

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Necessary and sufficient conditions for Bayes risk consistency of a recursive kernel classification rule (Corresp.)

IEEE transactions on information theory, 1987-05, Vol.33 (3), p.408-412

1987

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Necessary and sufficient consistency conditions for a recursive kernel regression estimate

Journal of multivariate analysis, 1987-10, Vol.23 (1), p.67-76

1987

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Non-parametric identification of a memoryless system with a cascade structure

International journal of systems science, 1979-11, Vol.10 (11), p.1301-1310

1979

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Non-parametric identification of non-linearity in hammerstein systems

IFAC Proceedings Volumes, 2003-09, Vol.36 (16), p.825-830

2003

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Non-parametric orthogonal series identification of Hammerstein systems

International journal of systems science, 1989-12, Vol.20 (12), p.2355-2367

GREBLICKI, WLODZIMIERZ

1989

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Nonlinearity estimation in Hammerstein systems based on ordered observations

IEEE transactions on signal processing, 1996-05, Vol.44 (5), p.1224-1233

Greblicki, W.

1996

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Nonlinearity recovering in Wiener system driven with correlated signal

IEEE transactions on automatic control, 2004-10, Vol.49 (10), p.1805-1812

Greblicki, W.

2004

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Nonparametric approach to Wiener system identification

IEEE transactions on circuits and systems. 1, Fundamental theory and applications, 1997-06, Vol.44 (6), p.538-545

Greblicki, W.

1997

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Almost sure convergence of classification procedures using Hermite series density estimates

Asymptotic efficiency of classifying procedures using the Hermite series estimate of multivariate probability densities (Corresp.)

Asymptotic properties of kernel estimates of a regression function

Asymptotically optimal pattern recognition procedures with density estimates (Corresp.)

Cascade non-linear system identification by a non-parametric method

A classification procedure using the multiple Fourier series

Continuous-time Hammerstein system identification

Continuous-time Hammerstein system identification from sampled data

Continuous-time Wiener system identification

Density-free Bayes risk consistency of nonparametric pattern recognition procedures

Distribution-Free Pointwise Consistency of Kernel Regression Estimate

Dynamic system identification with order statistics

Hammerstein system identification by non-parametric regression estimation

Hammerstein System Identification With the Nearest Neighbor Algorithm

Identification of discrete Hammerstein systems using kernel regression estimates

Input Nonlinearity Recovering in a Class of Systems

Learning to recognize patterns with a probabilistic teacher

Necessary and sufficient conditions for Bayes risk consistency of a recursive kernel classification rule (Corresp.)

Necessary and sufficient consistency conditions for a recursive kernel regression estimate

Non-parametric identification of a memoryless system with a cascade structure

Non-parametric identification of non-linearity in hammerstein systems

Non-parametric orthogonal series identification of Hammerstein systems

Nonlinearity estimation in Hammerstein systems based on ordered observations

Nonlinearity recovering in Wiener system driven with correlated signal

Nonparametric approach to Wiener system identification

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