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The Kriged Kalman filter
In recent years there has been growing interest in spatial-temporal modelling, partly due to the potential of large scale data in pollution and global climate monitoring to answer importantExpand
Estimation and smoothing from incomplete data for a class of lattice processes
Multidimensional discrete-parameter processes with factorable covariance structure are of great importance for applications and approximations to certain continuous parameter processes. In practicalExpand
A study on sampling design for optimal prediction of space–time stochastic processes
Abstract. Optimal selection of sampling strategies is considered for the prediction of spatio-temporal processes in a state-space-model framework. General conditions are assumed in relation to theExpand
A state-space model approach to optimum spatial sampling design based on entropy
We consider the spatial sampling design problem for a random field X. This random field is in general assumed not to be directly observable, but sample information from a related variable Y isExpand
Analysis of the statistics of device-to-device and cycle-to-cycle variability in TiN/Ti/Al:HfO2/TiN RRAMs
Abstract In order to study the device-to-device and cycle-to-cycle variability of switching voltages in 4-kbit RRAM arrays, an alternative statistical approach has been adopted by using experimentalExpand
Time series statistical analysis: A powerful tool to evaluate the variability of resistive switching memories
Time series statistical analyses (TSSA) have been employed to evaluate the variability of resistive switching memories and to model the set and reset voltages for modeling purposes. The conventionalExpand
A study on sensitivity of spatial sampling designs to a priori discretization schemes
TLDR
We address the problem of sensitivity of optimal designs with respect to the configuration of the set of potential observation sites considered, as well as to the model specifications. Expand
Resistive Switching and Charge Transport in Laser-Fabricated Graphene Oxide Memristors: A Time Series and Quantum Point Contact Modeling Approach
This work investigates the sources of resistive switching (RS) in recently reported laser-fabricated graphene oxide memristors by means of two numerical analysis tools linked to the Time SeriesExpand
Functional stochastic modeling and prediction of spatiotemporal processes
TLDR
A class of nonstationary statistical models with finite-order autoregressive spatiotemporal dynamics is introduced. Expand
Memristor variability and stochastic physical properties modeling from a multivariate time series approach
TLDR
A new multivariate approach is proposed for the reset and set voltages that accurately describes the statistical data structure of a resistive switching series. Expand
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