W. Gersch

发表

Spectral analysis of EEG's by autoregressive decomposition of time series

W. Gersch, 1970 .

Estimation of power spectra with finite-order autoregressive models

W. Gersch, D. Sharpe, 1973 .

Smoothness Priors in Time Series.

G. Kitagawa, W. Gersch, 1987 .

Automatic classification of electroencephalograms: Kullback-Leibler nearest neighbor rules.

W Gersch, F Martinelli, J Yonemoto, 1979, Science.

A smoothness priors time-varying AR coefficient modeling of nonstationary covariance time series

G. Kitagawa, W. Gersch, 1985, IEEE Transactions on Automatic Control.

On the achievable accuracy of structural system parameter estimates

W. Gersch, 1974 .

Causality or driving in electrophysiological signal analysis

W. Gersch, 1972 .

A Kullback Leibler-nearest neighbor rule classification of EEGs: the EEG population screening problem, an anesthesia level EEG classification application.

W. Gersch, M. Low, F. Martinelli, 1980, Computers and biomedical research, an international journal.

Epileptic Focus Location: Spectral Analysis Method

W. Gersch, G. V. Goddard, 1970, Science.

A Smoothness Priors–State Space Modeling of Time Series with Trend and Seasonality

G. Kitagawa, W. Gersch, 1984 .

Linear Gaussian State Space Modeling

G. Kitagawa, W. Gersch, 1996 .

Estimation of stationary structural system parameters from non-stationary random vibration data: A locally stationary model method

W. Gersch, T. Brotherton, 1982 .

A time varying AR coefficient model for modelling and simulating earthquake ground motion

G. Kitagawa, W. Gersch, 1985 .

Structural System Parameter Estimation by Two-Stage Least Squares Method

W. Gersch, G. Taoka, Robert. Liu, 1976 .

Smoothness priors transfer function estimation

G. Kitagawa, W. Gersch, 1989, Autom..

An approach to the prediction of time series with trends and seasonalities

Genshiro Kitagawa, Will Gersch, G. Kitagawa, 1982, 1982 21st IEEE Conference on Decision and Control.

Least squares estimates of structural system parameters using covariance function data

W. Gersch, W. Gersch, D. Foutch, 1974 .

Maximum likelihood estimation of structural parameters from random vibration data

Hirotugu Akaike, W. Gersch, H. Akaike, 1973 .

A data analytic approach to the smoothing problem and some of its variations

Will Gersch, Tom Brotherton, W. Gersch, 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

Estimation of structural system parameters from stationary and non-stationary ambient vibrations: An exploratory-confirmatory analysis

W. Gersch, W. Gersch, F. Martinelli, 1979 .

04 A SMOOTHNESS PRIORS APPROACH TO THE MODELING OF TIME SERIES WITH TREND AND SEASONALITY *

G. Kitagawa, W. Gersch, 2022 .

Computation of the mean-square response of a stationary time-discrete system

W. Gersch, W. Gersch, 1971 .

Selectivity Concentration and Integration Efficiency

W. Gersch, K. Miller, 1961 .

One Channel At-A-Time Multichannel Autoregressive Modeling of Stationary and Nonstationary Time Series

Will Gersch, David Stone, W. Gersch, 1994 .

Synthesis of multivariate random vibration systems: A two-stage least squares AR-MA model approach☆

W. Gersch, W. Gersch, J. Yonemoto, 1977 .

Time Series Methods for the Synthesis of Random Vibration Systems

W. Gersch, W. Gersch, R. S-Z. Liu, 1976 .

Discrete Time Series Synthesis of Randomly Excited Structural System Response

Will Gersch, W. Gersch, Susan Luo, 1972 .

Estimation of the autoregressive parameters of a mixed autoregressive moving-average time series

Will Gersch, W. Gersch, 1970 .

Smoothness priors modeling of seafloor bathymetric data

W. Gersch, 1990 .

Forecasting Using Long-Order Autoregressive Processes: An Example Using Housing Starts

W. Gersch, N. Miller, Michael Sklarz, 1987 .

NEAREST NEIGHBOR RULE CLASSIFICATION OF STATIONARY AND NONSTATIONARY TIME SERIES

Will Gersch, W. Gersch, 1981 .

Parametric time domain analysis of the multiple input/scalar output problem: The source identification problem

Simon Braun, W. Gersch, T. Brotherton, 1980 .

Smoothness priors multichannel autoregressive time series modeling

W. Gersch, W. Gersch, 1989, International Conference on Acoustics, Speech, and Signal Processing,.

A smoothness priors long AR model method for spectral estimation

W. Gersch, G. Kitagawa, G. Kitagawa, 1985, IEEE Transactions on Automatic Control.

Smoothness priors analysis of quasi-periodic time series

W. Gersch, G. Kitagawa, G. Kitagawa, 1995, Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers.

A Circular Lattice-Smoothness Priors Multichannel Time Varying Autoregressive Model

W. Gersch, D. Stone, 1991 .

Multivariate autoregressive time semes modeling: one scalar autoregressive model at-A-time

W. Gersch, D. Stone, 1995 .

Spectral analysis of seizures in humans.

W Gersch, W. Gersch, B. Tharp, 1975, Computers and biomedical research, an international journal.

Some applications of smoothness priors in time series

W. Gersch, 1987, 26th IEEE Conference on Decision and Control.

Some New Tools for EEG Modeling and Analysis

Will Gersch, W. Gersch, 1996 .

The smoothing problem — a state space recursive computational approach: Applications to econometric time series with trends and seasonalities

Will Gersch, Tom Brotherton, W. Gersch, 1982 .

Parametric time series models for multivariate EEG analysis.

W Gersch, J Yonemoto, W. Gersch, 1977, Computers and biomedical research, an international journal.

General State Space Modeling

Genshiro Kitagawa, Will Gersch, G. Kitagawa, 2018, Statistical Methods in Control & Signal Processing.

Modeling multivariate covariance nonstationary time series and their dependency structure: An application to human epileptic event EEG analysis

Will Gersch, W. Gersch, 1985, 1985 24th IEEE Conference on Decision and Control.

Modeling Nonstationary Time Series and Inferring Instantaneous Dependency, Feedback and Causality: An Application to Human Epileptic Seizure Event Data

W. Gersch, W. Gersch, 1985 .

Mean-Square Responses in Structural Systems

Will Gersch, W. Gersch, 1970 .