The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of g...
Geophysical measurements can often be described in terms of multichannel, autoregressive data models...
This thesis is concerned with a comparative study of discrete time filters using the theories of Wie...
We study the geoelectrical problem of picking out the useful signal from voltage time series, monito...
The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem ...
The present paper treats the application of the Kalman-Bucy filter (KBF), organized as a deconvoluti...
Sequences of observations or measurements are often modeled as realizations of stochastic processes ...
The linear generalized Kalman Bucy filter problem is studied. An observed process is a sum of a us...
An important problem in the practical use of optimal spectral methods in gravity field modelling is ...
Sequential Bayesian techniques enable tracking of evolving geophysical parameters via sequential obs...
The Kalman filter is applied to the inverse filtefing or deconvolution problem. In this dissertation...
The linear Kalman Bucy filter problem for a system, at that a signal and a noise are vector indepen...
Abstract. One of the most basic tools in optimal spectral gravity field modelling is the method of W...
Optimal filtering applied to stationary and non-stationary signals provides the most efficient means...
The full text of this article is not available on SOAR. WSU users can access the article via IEEE Xp...
International audienceFor modelling geophysical systems, large-scale processes are described through...
Geophysical measurements can often be described in terms of multichannel, autoregressive data models...
This thesis is concerned with a comparative study of discrete time filters using the theories of Wie...
We study the geoelectrical problem of picking out the useful signal from voltage time series, monito...
The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem ...
The present paper treats the application of the Kalman-Bucy filter (KBF), organized as a deconvoluti...
Sequences of observations or measurements are often modeled as realizations of stochastic processes ...
The linear generalized Kalman Bucy filter problem is studied. An observed process is a sum of a us...
An important problem in the practical use of optimal spectral methods in gravity field modelling is ...
Sequential Bayesian techniques enable tracking of evolving geophysical parameters via sequential obs...
The Kalman filter is applied to the inverse filtefing or deconvolution problem. In this dissertation...
The linear Kalman Bucy filter problem for a system, at that a signal and a noise are vector indepen...
Abstract. One of the most basic tools in optimal spectral gravity field modelling is the method of W...
Optimal filtering applied to stationary and non-stationary signals provides the most efficient means...
The full text of this article is not available on SOAR. WSU users can access the article via IEEE Xp...
International audienceFor modelling geophysical systems, large-scale processes are described through...
Geophysical measurements can often be described in terms of multichannel, autoregressive data models...
This thesis is concerned with a comparative study of discrete time filters using the theories of Wie...
We study the geoelectrical problem of picking out the useful signal from voltage time series, monito...