Search results for "Estimation theory"
showing 4 items of 84 documents
Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data
2013
Abstract. Increasingly, ground-based and airborne geophysical datasets are used to inform groundwater models. Recent research focuses on establishing coupling relationships between geophysical and groundwater parameters. To fully exploit such information, this paper presents and compares a joint hydrogeophysical inversion (JHI) approach and sequential hydrogeophysical inversion (SHI) approach to inform a field-scale groundwater model with Time Domain Electromagnetic (TDEM) and Electrical Resistivity Tomography (ERT) data. The implemented SHI coupled inverted geophysical models with groundwater parameters, where the strength of the coupling was based on geophysical parameter resolution. To t…
Joint second-order parameter estimation for spatio-temporal log-Gaussian Cox processes
2018
We propose a new fitting method to estimate the set of second-order parameters for the class of homogeneous spatio-temporal log-Gaussian Cox point processes. With simulations, we show that the proposed minimum contrast procedure, based on the spatio-temporal pair correlation function, provides reliable estimates and we compare the results with the current available methods. Moreover, the proposed method can be used in the case of both separable and non-separable parametric specifications of the correlation function of the underlying Gaussian Random Field. We describe earthquake sequences comparing several Cox model specifications.
Towards Robust Adaptive Least-Squares Parameter Estimation with Internal Feedback
1998
Abstract The new concepts of the ‘covariance matrix normalization’ and the ‘cascade’ structure of the adaptive least-squares estimator are shown to generalize and extend the use of internal information feedback in various robustness/alertness-oriented modifications to the standard ALS estimation algorithm. In the cascade estimation structure it is possible to ‘naturally’ stabilize, rather than maximize, the information matrix so that the covariance windup and blowup are effectively eliminated and the celebrated square root update of the covariance matrix is no longer needed Consequently, a new, ‘single-loop/cascade’ ALS MIMO estimation algorithm, enabling to effectively track both slow and …
Model selection using limiting distributions of second-order blind source separation algorithms
2015
Signals, recorded over time, are often observed as mixtures of multiple source signals. To extract relevant information from such measurements one needs to determine the mixing coefficients. In case of weakly stationary time series with uncorrelated source signals, this separation can be achieved by jointly diagonalizing sample autocovariances at different lags, and several algorithms address this task. Often the mixing estimates contain close-to-zero entries and one wants to decide whether the corresponding source signals have a relevant impact on the observations or not. To address this question of model selection we consider the recently published second-order blind identification proced…