Bibliographic Review on Distributed Kalman Filtering

In recent years, a compelling need has arisen to understand the effects of distributed information structures on estimation and filtering. In this paper, a bibliographical review on distributed Kalman filtering (DKF) is provided.\ud The paper contains a classification of different approaches and methods involved to DKF. The applications of DKF are also discussed and explained separately. A comparison of different approaches is briefly carried out. Focuses on the contemporary research are also addressed with emphasis on the practical applications of the techniques. An exhaustive list of publications, linked directly or indirectly to DKF in the open literature, is compiled to provide an overall picture of different developing aspects of this area

On the genericity properties in networked estimation: Topology design and sensor placement

In this paper, we consider networked estimation of linear, discrete-time dynamical systems monitored by a network of agents. In order to minimize the power requirement at the (possibly, battery-operated) agents, we require that the agents can exchange information with their neighbors only \emph{once per dynamical system time-step}; in contrast to consensus-based estimation where the agents exchange information until they reach a consensus. It can be verified that with this restriction on information exchange, measurement fusion alone results in an unbounded estimation error at every such agent that does not have an observable set of measurements in its neighborhood. To over come this challenge, state-estimate fusion has been proposed to recover the system observability. However, we show that adding state-estimate fusion may not recover observability when the system matrix is structured-rank ($S$-rank) deficient. In this context, we characterize the state-estimate fusion and measurement fusion under both full $S$-rank and $S$-rank deficient system matrices.Comment: submitted for IEEE journal publicatio

REGULATORY APPROVAL OF NEW MEDICAL DEVICES: A CROSS SECTIONAL STUDY

Objective To investigate the regulatory approval of new medical devices. Design Cross sectional study of new medical devices reported in the biomedical literature. Data sources PubMed was searched between 1 January 2000 and 31 December 2004 to identify clinical studies of new medical devices. The search was carried out during this period to allow time for regulatory approval. Eligibility criteria for study selection Articles were included if they reported a clinical study of a new medical device and there was no evidence of a previous clinical study in the literature. We defined a medical device according to the US Food and Drug Administration as an “instrument, apparatus, implement, machine, contrivance, implant, in vitro reagent, or other similar or related article.” Main outcome measures Type of device, target specialty, and involvement of academia or of industry for each clinical study. The FDA medical databases were then searched for clearance or approval relevant to the device. Results 5574 titles and abstracts were screened, 493 full text articles assessed for eligibility, and 218 clinical studies of new medical devices included. In all, 99/218 (45%) of the devices described in clinical studies ultimately received regulatory clearance or approval. These included 510(k) clearance for devices determined to be “substantially equivalent” to another legally marketed device (78/99; 79%), premarket approval for high risk devices (17/99; 17%), and others (4/99; 4%). Of these, 43 devices (43/99; 43%) were actually cleared or approved before a clinical study was published. Conclusions We identified a multitude of new medical devices in clinical studies, almost half of which received regulatory clearance or approval. The 510(k) pathway was most commonly used, and clearance often preceded the first published clinical study

Noise thresholds for optical cluster-state quantum computation

In this paper we do a detailed numerical investigation of the fault-tolerant threshold for optical cluster-state quantum computation. Our noise model allows both photon loss and depolarizing noise, as a general proxy for all types of local noise other than photon loss noise. We obtain a threshold region of allowed pairs of values for the two types of noise. Roughly speaking, our results show that scalable optical quantum computing is possible for photon loss probabilities less than 0.003, and for depolarization probabilities less than 0.0001. Our fault-tolerant protocol involves a number of innovations, including a method for syndrome extraction known as telecorrection, whereby repeated syndrome measurements are guaranteed to agree. This paper is an extended version of [Dawson et al., Phys. Rev. Lett. 96, 020501].Comment: 28 pages. Corrections made to Table I

Cram\'er-Rao Bounds for Polynomial Signal Estimation using Sensors with AR(1) Drift

We seek to characterize the estimation performance of a sensor network where the individual sensors exhibit the phenomenon of drift, i.e., a gradual change of the bias. Though estimation in the presence of random errors has been extensively studied in the literature, the loss of estimation performance due to systematic errors like drift have rarely been looked into. In this paper, we derive closed-form Fisher Information matrix and subsequently Cram\'er-Rao bounds (upto reasonable approximation) for the estimation accuracy of drift-corrupted signals. We assume a polynomial time-series as the representative signal and an autoregressive process model for the drift. When the Markov parameter for drift \rho<1, we show that the first-order effect of drift is asymptotically equivalent to scaling the measurement noise by an appropriate factor. For \rho=1, i.e., when the drift is non-stationary, we show that the constant part of a signal can only be estimated inconsistently (non-zero asymptotic variance). Practical usage of the results are demonstrated through the analysis of 1) networks with multiple sensors and 2) bandwidth limited networks communicating only quantized observations.Comment: 14 pages, 6 figures, This paper will appear in the Oct/Nov 2012 issue of IEEE Transactions on Signal Processin

Next Steps for Hydrogen - physics, technology and the future

Hydrogen has been proposed as a future energy carrier for more than 40 years. In recent decades, impetus has been given by the need to reduce global greenhouse gas emissions from vehicles. In addition, hydrogen has the potential to facilitate the large-scale deployment of variable renewables in the electricity system. Despite such drivers, the long-anticipated hydrogen economy is proving to be slow to emerge. This report stresses the role that physics and physics-based technology could play in accelerating the large-scale deployment of hydrogen in the energy system. Emphasis is given to the potential of cryogenic liquid hydrogen and the opportunities afforded by developments in nanoscience for hydrogen storage and use. The use of low-temperature liquid hydrogen opens up a technological opportunity separate from, but complementary with, energy applications. The new opportunity is the ability to cool novel materials into the superconducting state without the need to use significant quantities of expensive liquid helium. Two of the authors have previously coined the term “hydrogen cryomagnetics” for when liquid hydrogen is utilised in high-field and high-efficiency magnets. The opportunity for liquid hydrogen to displace liquid helium may be a relatively small business opportunity compared to global transport energy demands, but it potentially affords an opportunity to kick-start the wider commercial use of hydrogen. The report considers various important factors shaping the future for hydrogen, such as competing production methods and the importance of safety, but throughout it is clear that science and engineering are of central importance to hydrogen innovation and physics has an important role to play