Uniform stability of a particle approximation of the optimal filter derivative

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.

Convergence of the auxiliary particle implementation of the PHD filter

Optimal Bayesian multi-target filtering is in general computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency was proposed by Whiteley et. al. Numerical examples were presented for two scenarios, including a challenging nonlinear observation model, to support the claim. This paper studies the theoretical properties of this auxiliary particle implementation. $\mathbb{L}_p$ error bounds are established from which almost sure convergence follows.

Frontier experiences from industry-academia consortia

Technology roadmapping has been applied successfully in many industrial organizations. Designed to facilitate and communicate technology strategy and planning, roadmaps (or, as in Europe, route maps) can take a variety of specific forms, depending on the type (opportunities, capabilities, products, technologies, etc.) and particular company context. While roadmaps are generally manifest in a number of "program elements or levels" superimposed upon a timeline, experienced mappers often claim that it is "roadmapping" rather than "the roadmap" that generates the value. This special report focuses primarily on product and technology roadmaps. Following an introduction to the evolution, purpose and applications of corporate/industry roadmapping, four industry-developed articles examine roadmapping in Lucent Technologies, Rockwell Automation, the pharmaceutical/biotechnology industry, and UK-based Domino Printing Sciences.

Shifting atomic patterns: on the origin of the different atomic-scale patterns of graphite as observed using scanning tunnelling microscopy.

We present an in-depth study of the myriad atomically resolved patterns observed on graphite using the scanning tunnelling microscope (STM) over the past three decades. Through the use of highly resolved atomic resolution images, we demonstrate how the interactions between the different graphene layers comprising graphite affect the local surface atomic charge density and its resulting symmetry orientation, with particular emphasis on interactions that are thermodynamically unstable. Moreover, the interlayer graphene coupling is controlled experimentally by varying the tip-surface interaction, leading to associated changes in the atomic patterns. The images are corroborated by first-principles calculations, further validating our claim that surface graphene displacement, coming both from lateral and vertical displacement of the top graphene layer, forms the basis of the rich variety of atomic patterns observed in STM experiments on graphite.

An information oriented framework for relating IS/IT resources and business value

Several studies have highlighted the importance of information and information quality in organisations and thus information is regarded as key determinant for the success and organisational performance. At the same time, there are numerous studies, frameworks and case studies examining the impact of information technology and systems to business value. Recently, several studies have proposed maturity models for information management capabilities in the literature, which claim that a higher maturity results in a higher organizational performance. Although these studies provide valuable information about the underlying relations, most are limited in specifying the relationship in more detail. Furthermore, most prominent approaches do not or at least not explicitly consider information as important influencing factor for organisational performance. In this paper, we aim to review selected contributions and introduce a model that shows how IS/IT resources and capabilties could be interlinked with IS/IT utilization, organizational performance and business value. Complementing other models and frameworks, we explicitly consider information from a management maturity, quality and risk perspective. Moreover, the paper discusses how each part of the model can be assessed in order to validate the model in future studies.

Physical consequences of a nonparametric uncertainty model in structural dynamics

One of the main claims of the nonparametric model of random uncertainty introduced by Soize (2000) [3] is its ability to account for model uncertainty. The present paper investigates this claim by examining the statistics of natural frequencies, total energy and underlying dispersion equation yielded by the nonparametric approach for two simple systems: a thin plate in bending and a one-dimensional finite periodic massspring chain. Results for the plate show that the average modal density and the underlying dispersion equation of the structure are gradually and systematically altered with increasing uncertainty. The findings for the massspring chain corroborate the findings for the plate and show that the remote coupling of nonadjacent degrees of freedom induced by the approach suppresses the phenomenon of mode localization. This remote coupling also leads to an instantaneous response of all points in the chain when one mass is excited. In the light of these results, it is argued that the nonparametric approach can deal with a certain type of model uncertainty, in this case the presence of unknown terms of higher or lower order in the governing differential equation, but that certain expectations about the system such as the average modal density may conflict with these results. © 2012 Elsevier Ltd.

Evaluating the impact of V2G services on the degradation of batteries in PHEV and EV

Many researchers and industry observers claim that electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) could provide vehicle-to-grid (V2G) bulk energy and ancillary services to an electricity network. This work quantified the impact on various battery characteristics whilst providing such services. The sensitivity of the impact of V2G services on battery degradation was assessed for EV and PHEV for different battery capacities, charging regimes, and battery depth of discharge. Battery degradation was found to be most dependent on energy throughput for both the EV and PHEV powertrains, but was most sensitive to charging regime (for EVs) and battery capacity (for PHEVs). When providing ancillary services, battery degradation in both powertrains was most sensitive to individual vehicle battery depth of discharge. Degradation arising from both bulk energy and ancillary services could be minimised by reducing the battery capacity of the vehicle, restricting the number of hours connected and reducing the depth of discharge of each vehicle for ancillary services. Regardless, best case minimum impacts of providing V2G services are severe such as to require multiple battery pack replacements over the vehicle lifetime. © 2013 Elsevier Ltd.

High performance fibre-reinforced cementitious composite (CARDIFRC) - Performance and application to retrofitting

This paper describes first some of the recent performance checks on the high performance fibre-reinforced cementitious composite CARDIFRC and then its application to the retrofitting of damaged concrete beams. It is shown that an even distribution of fibres throughout the bulk of the material is crucial to its excellent fatigue performance and to the reduction in the autogenous shrinkage strains. The distribution of fibres in beams, cylinders and strips is examined using computerised tomography imaging and traditional image analysis. Thin strips of CARDIFRC are used to retrofit damaged concrete beams which are subjected to thermal cycling. It is shown that neither the load carrying capacity of the retrofitted beams nor the bond between retrofit strips and concrete deteriorates with thermal cycling. The load carrying capacity of retrofitted beams is predicted with a model based on fracture mechanics, and the predictions are shown to be in good agreement with test data. © 2006 Elsevier Ltd. All rights reserved.