Robust Design of Radar Doppler Filters Aubry, Augusto; De Maio, Antonio; Yongwei Huang ...
IEEE transactions on signal processing,
11/2016, Volume:
64, Issue:
22
Journal Article
Peer reviewed
This paper considers the design of robust filters for radar pulse-Doppler processing when the interference is a wide sense stationary random process. The figure of merit which is optimized is the ...signal-to-interference-plus-noise ratio (SINR) at the filter output under a multitude of constraints accounting for Doppler filter sidelobes as well as uncertainties both in the received useful signal component and interference covariance matrix. The design is analytically formulated as a constrained optimization problem whose solvability is thoroughly studied. Precisely, a polynomial-time solution technique to get the optimal filter is proposed exploiting the representation of non-negative trigonometric polynomials via linear matrix inequalities, the spectral factorization theorem, and the duality theory. Last but not least, a detailed analysis of the optimum filter performance is provided showing the tradeoffs involved in the design and the gain achievable over some already known counterparts.
Predicting failure in composite materials under service loading conditions has been challenging due to the non-uniform mechanical properties arising from the composite fabrication process. Including ...these uncertainties in the analysis becomes critical. The probabilistic approach plays a vital role in making the design less conservative and anticipates the risk associated with the design incorporating the uncertainties. In this work, metamodels such as support vector machines, radial basis function, and logistic regression in conjunction with Latin hypercube, Sobol, and Halton sequence sampling methods were used to calculate the failure probability in the carbon fibre/epoxy-based composite material. Here, the composite plates were fabricated using the vacuum-assisted resin transfer molding (VARTM) process. The variation in the fibre-volume fraction was evaluated at different sites of the composite plate. Then, the effective orthotropic properties of the composite for various fibre-volume fractions have been numerically computed by the homogenisation method using periodic boundary conditions. A double cantilever composite beam problem was considered to predict the failure probability by including the uncertainties in single-source — fibre-volume fraction and double-source — fibre-volume fraction and fracture toughness. At the end, a study to ascertain the metamodels stability was presented to demonstrate the accuracy and effectiveness of the proposed approach.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose
The use of social media and information exchange increased during Covid-19 pandemic because people are isolated and working from home. The use of social media enhances information exchange in ...a global society, therefore customers are uncertain and not in a better position to take decisions before the situation goes worst everywhere in the world. The current study helps to understand how social media facilitate social and global engagement and information exchange which ultimately leads to the development of the customer psychology of stockpiling. This study aims to develop a research framework which helps to understand the customer psychology of stockpiling during a global pandemic.
Design/methodology/approach
This study opted for a social constructionist approach because it can help to understand both individual and social subjective realities with respect to stockpiling behaviour due to the fear and risk of Covid-19 pandemic. For this purpose, the researcher collected data from 40 customers of UK retail stores who actively use social media. The data were collected during telephonic interviews and thematic analysis was used for data analysis.
Findings
Results highlighted that institutional communication and social public interpretation of uncertainties and risk enhanced misinformation and sensationalism through social media platforms; therefore, stockpiling behaviour increased during Covid-19 pandemic. The fear of items being out of stock, illness, misinformation, family fear and going out were some of the possible causes that led to the development of panic stockpiling behaviour. The global uncertainty proof, as well as a public social consensus for staying at home and protecting the future also increased customers’ intention to buy in bulk for their future. Although social media played an important role in transferring relevant and timely information, it also increased uncertainty and social proof which may have led to stockpiling of retail products.
Research limitations/implications
The results of this study are beneficial for understanding how Covid-19 creates and enhances uncertainties and risks at both global and national level which developed into customer panic stockpiling behaviour, even when there is no promotional scheme or decrease in prices. This study helps marketers understand the psychology of customer stockpiling during a global pandemic. This study also helps to understand the role of social media, which promotes social interpretations of uncertainties and risk which ultimately enhance panic stockpiling among customers.
Originality/value
Limited research is available which provides an understanding of how social media can play a role in socially generated uncertainties and risks, which enhance misinformation and sensationalism, as well as the development of stockpiling behaviour. This study provided a stockpiling behaviour model based on the theory of uncertainty and social proof. The results of this study are unique as there is limited literature available which connects social media, uncertainties and risk, Covid-19 pandemic and stockpiling behaviour among educated people.
We study the use of methods based on the real symplectic groups Sp(2n,R) in the analysis of the Arthurs-Kelly model of proposed simultaneous measurements of position and momentum in quantum ...mechanics. Consistent with the fact that such measurements are in fact not possible, with arbitrary precision, we show that the observable consequences of the Arthurs-Kelly interaction term are contained in the symplectic transformation law connecting the system plus apparatus variance matrices at an initial and a final time. The individual variance matrices are made up of averages and spreads or uncertainties for single hermitian observables one at a time, which are quantum mechanically well defined. The consequences of the multimode symplectic covariant Uncertainty Principle in the Arthurs-Kelly context are examined.
•Arthurs-Kelly model of simultaneous measurements of position and momentum is analysed using symplectic group Sp(6,R).•The initial and final variance matrices for the system apparatus combine get connected by a symplectic transformation.•The consequences of the multimode symplectic covariant Uncertainty Principle in the this context are examined.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Accurate biomass measurements and analyses are critical components in quantifying carbon stocks and sequestration rates, assessing potential impacts due to climate change, locating bio-energy ...processing plants, and mapping and planning fuel treatments. To this end, biomass equations will remain a key component of future carbon measurements and estimation. As researchers in biomass and carbon estimation, we review the present scenario of aboveground biomass estimation, focusing particularly on estimation using tree-level models and identify some cautionary points that we believe will improve the accuracy of biomass and carbon estimates to meet societal needs. In addition, we discuss the critical challenges in developing or calibrating tree biomass models and opportunities for improved biomass. Some of the opportunities to improve biomass estimate include integration of taper and other attributes and combining different data sources. Biomass estimation is a complex process, when possible, we should make use of already available resources such as wood density and forest inventory databases. Combining different data-sets for model development and using independent data-sets for model verification will offer opportunities to improve biomass estimation. Focus should also be made on belowground biomass estimation to accurately estimate the full forest contribution to carbon sequestration. In addition, we suggest developing comprehensive biomass estimation methods that account for differences in site and stand density and improve forest biomass modeling and validation at a range of spatial scales.
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BFBNIB, DOBA, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, ...computation, and time can in fact improve accuracy. We review the major progress made so far: (a) the discovery of less‐is‐more effects; (b) the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; (c) an advancement from vague labels to computational models of heuristics; (d) the development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an “adaptive toolbox;” and (e) the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people’s adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource‐intensive and general‐purpose processing strategies.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Rubber isolators are widely used in engineering structures, which often exhibit some nonlinearity and uncertainty properties subjected to different environment exciting. In order to study the ...nonlinear characteristic and uncertainty of a rubber isolator system, the sin-sweep vibration tests with different base exciting level are carried out firstly. Then a single freedom degree mass-spring-damper model is introduced to simplify the rubber isolator system. In the theory model, the spring and the damper are represented by polynomial functions of the relative displacement. The coefficients in the functions are identified by the test data, while the uncertainties of the coefficients are quantified by the principal components analysis (PCA) and Monte Carlo (MC) simulations. The major resonant frequencies and the damping ratios of the isolation system are calculated according to the theory model, the amplitude-frequency nonlinear characteristics are simulated by Runge–Kutta numerical method. The simulation results agree well with the experimental results, which indicate that the nonlinear model and the uncertainty quantifying results are feasible to predict the vibration characteristic and uncertainty of the isolation systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We propose a multi-level method to increase the accuracy of machine learning algorithms for approximating observables in scientific computing, particularly those that arise in systems modelled by ...differential equations. The algorithm relies on judiciously combining a large number of computationally cheap training data on coarse resolutions with a few expensive training samples on fine grid resolutions. Theoretical arguments for lowering the generalisation error, based on reducing the variance of the underlying maps, are provided and numerical evidence, indicating significant gains over underlying single-level machine learning algorithms, are presented. Moreover, we also apply the multi-level algorithm in the context of forward uncertainty quantification and observe a considerable speedup over competing algorithms.
Model uncertainty and VaR aggregation Embrechts, Paul; Puccetti, Giovanni; Rüschendorf, Ludger
Journal of banking & finance,
August 2013, 2013-8-00, 20130801, Volume:
37, Issue:
8
Journal Article
Peer reviewed
•We derive an algorithm for the calculation of bounds on the best and worst VaR.•The numerical results are compared with available analytical bounds.•Worst dependence scenarios are derived using the ...notion of complete mixability.•Examples show one can handle portfolios with several hundreds of risk factors.•The results obtained highlight VaR-based model uncertainty.
Despite well-known shortcomings as a risk measure, Value-at-Risk (VaR) is still the industry and regulatory standard for the calculation of risk capital in banking and insurance. This paper is concerned with the numerical estimation of the VaR for a portfolio position as a function of different dependence scenarios on the factors of the portfolio. Besides summarizing the most relevant analytical bounds, including a discussion of their sharpness, we introduce a numerical algorithm which allows for the computation of reliable (sharp) bounds for the VaR of high-dimensional portfolios with dimensions d possibly in the several hundreds. We show that additional positive dependence information will typically not improve the upper bound substantially. In contrast higher order marginal information on the model, when available, may lead to strongly improved bounds. Several examples of practical relevance show how explicit VaR bounds can be obtained. These bounds can be interpreted as a measure of model uncertainty induced by possible dependence scenarios.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
This paper deals with the design of discrete sliding mode control incorporating difference equation with minima. It discuss two reaching laws having hybrid structure with respect to Gao's reaching ...law and Utkin's reaching law. This approach overcomes the limitations of both methods, which are primarily chattering in the former and overly large control action in the latter case. These laws are crafted for systems with and without perturbation. In the case of the undisturbed system, the switching variable converges to zero within a finite-time steps, while for the perturbed system, the variable remains close to the vicinity of the switching manifold. Simulation results show the efficacy of the discussed methodology.
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