90 resultados para Additive Gaussian noise
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Interference by siren background-noise with speech transmitted from radio equipment (3) of an emergency-service vehicle, is reduced by apparatus (1) that subtracts (43) an estimate nk of the correlated siren-noise component from the contaminated signal yk supplied by the cab-microphone (2). The estimate nk is computed by FIR (finite impulse response) filtering of a siren-reference signal xk supplied by a unit (4) from one or more microphones located on or near the siren, or from the electric waveform driving the siren. The filter-coefficients wk are adjusted according to an LMS (least mean square) adaptive algorithm that is applied to the correlated-noise component ek of the fed-back noise-reduced signal, so as to bring about iterative cancellation with close frequency-tracking, of the siren noise.
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This paper investigates the price effects of environmental certification on commercial real estate assets. It is argued that there are likely to be three main drivers of price differences between certified and non-certified buildings. First, certified buildings offer a bundle of benefits to occupiers relating to business productivity, image and occupancy costs. Second, due to these occupier benefits, certified buildings can result in higher rents and lower holding costs for investors. Third, certified buildings may require a lower risk premium. Drawing upon the CoStar database of US commercial real estate assets, hedonic regression analysis is used to measure the effect of certification on both rent and price. We first estimate the rental regression for a sample of 110 LEED and 433 Energy Star as well as several thousand benchmark buildings to compare the sample to. The results suggest that, compared to buildings in the same metropolitan region, certified buildings have a rental premium and that the more highly rated that buildings are in terms of their environmental impact, the greater the rental premium. Furthermore, based on a sample of transaction prices for 292 Energy Star and 30 LEED-certified buildings, we find price premia of 10% and 31% respectively compared to non-certified buildings in the same metropolitan area
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Using the formalism of the Ruelle response theory, we study how the invariant measure of an Axiom A dynamical system changes as a result of adding noise, and describe how the stochastic perturbation can be used to explore the properties of the underlying deterministic dynamics. We first find the expression for the change in the expectation value of a general observable when a white noise forcing is introduced in the system, both in the additive and in the multiplicative case. We also show that the difference between the expectation value of the power spectrum of an observable in the stochastically perturbed case and of the same observable in the unperturbed case is equal to the variance of the noise times the square of the modulus of the linear susceptibility describing the frequency-dependent response of the system to perturbations with the same spatial patterns as the considered stochastic forcing. This provides a conceptual bridge between the change in the fluctuation properties of the system due to the presence of noise and the response of the unperturbed system to deterministic forcings. Using Kramers-Kronig theory, it is then possible to derive the real and imaginary part of the susceptibility and thus deduce the Green function of the system for any desired observable. We then extend our results to rather general patterns of random forcing, from the case of several white noise forcings, to noise terms with memory, up to the case of a space-time random field. Explicit formulas are provided for each relevant case analysed. As a general result, we find, using an argument of positive-definiteness, that the power spectrum of the stochastically perturbed system is larger at all frequencies than the power spectrum of the unperturbed system. We provide an example of application of our results by considering the spatially extended chaotic Lorenz 96 model. These results clarify the property of stochastic stability of SRB measures in Axiom A flows, provide tools for analysing stochastic parameterisations and related closure ansatz to be implemented in modelling studies, and introduce new ways to study the response of a system to external perturbations. Taking into account the chaotic hypothesis, we expect that our results have practical relevance for a more general class of system than those belonging to Axiom A.
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The understanding of the statistical properties and of the dynamics of multistable systems is gaining more and more importance in a vast variety of scientific fields. This is especially relevant for the investigation of the tipping points of complex systems. Sometimes, in order to understand the time series of given observables exhibiting bimodal distributions, simple one-dimensional Langevin models are fitted to reproduce the observed statistical properties, and used to investing-ate the projected dynamics of the observable. This is of great relevance for studying potential catastrophic changes in the properties of the underlying system or resonant behaviours like those related to stochastic resonance-like mechanisms. In this paper, we propose a framework for encasing this kind of studies, using simple box models of the oceanic circulation and choosing as observable the strength of the thermohaline circulation. We study the statistical properties of the transitions between the two modes of operation of the thermohaline circulation under symmetric boundary forcings and test their agreement with simplified one-dimensional phenomenological theories. We extend our analysis to include stochastic resonance-like amplification processes. We conclude that fitted one-dimensional Langevin models, when closely scrutinised, may result to be more ad-hoc than they seem, lacking robustness and/or well-posedness. They should be treated with care, more as an empiric descriptive tool than as methodology with predictive power.
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A new incremental four-dimensional variational (4D-Var) data assimilation algorithm is introduced. The algorithm does not require the computationally expensive integrations with the nonlinear model in the outer loops. Nonlinearity is accounted for by modifying the linearization trajectory of the observation operator based on integrations with the tangent linear (TL) model. This allows us to update the linearization trajectory of the observation operator in the inner loops at negligible computational cost. As a result the distinction between inner and outer loops is no longer necessary. The key idea on which the proposed 4D-Var method is based is that by using Gaussian quadrature it is possible to get an exact correspondence between the nonlinear time evolution of perturbations and the time evolution in the TL model. It is shown that J-point Gaussian quadrature can be used to derive the exact adjoint-based observation impact equations and furthermore that it is straightforward to account for the effect of multiple outer loops in these equations if the proposed 4D-Var method is used. The method is illustrated using a three-level quasi-geostrophic model and the Lorenz (1996) model.
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ABSTRACT Non-Gaussian/non-linear data assimilation is becoming an increasingly important area of research in the Geosciences as the resolution and non-linearity of models are increased and more and more non-linear observation operators are being used. In this study, we look at the effect of relaxing the assumption of a Gaussian prior on the impact of observations within the data assimilation system. Three different measures of observation impact are studied: the sensitivity of the posterior mean to the observations, mutual information and relative entropy. The sensitivity of the posterior mean is derived analytically when the prior is modelled by a simplified Gaussian mixture and the observation errors are Gaussian. It is found that the sensitivity is a strong function of the value of the observation and proportional to the posterior variance. Similarly, relative entropy is found to be a strong function of the value of the observation. However, the errors in estimating these two measures using a Gaussian approximation to the prior can differ significantly. This hampers conclusions about the effect of the non-Gaussian prior on observation impact. Mutual information does not depend on the value of the observation and is seen to be close to its Gaussian approximation. These findings are illustrated with the particle filter applied to the Lorenz ’63 system. This article is concluded with a discussion of the appropriateness of these measures of observation impact for different situations.
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This paper describes a novel adaptive noise cancellation system with fast tunable radial basis function (RBF). The weight coefficients of the RBF network are adapted by the multi-innovation recursive least square (MRLS) algorithm. If the RBF network performs poorly despite of the weight adaptation, an insignificant node with little contribution to the overall performance is replaced with a new node without changing the model size. Otherwise, the RBF network structure remains unchanged and only the weight vector is adapted. The simulation results show that the proposed approach can well cancel the noise in both stationary and nonstationary ANC systems.
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Agency of Noise is a network of artists, musicians and academics from across the UK whose work is concerned with noise. The website offers a site for the development of online profiles for its members, the publication of works by members and the promotion and documentation of events hosted by the network. It also provides related links and references. The platform has developed from participation at national network events and conferences including Noise Vs Culture, University of Kent (2012); Liveness, University of Bournemouth (2012); Noise, Affect Politics, University of Salford (2010); and a research residency at The Banff Centre, Banff, Canada (2009).
Resumo:
'The Prophetic Sound: a day and night of noise cabaret' is the first event hosted by Agency of Noise. This all day event brought together artists and academics whose subject of focus is noise (in creative practice). Artists from across the UK were invited to consider a future post-digital era in which everything with a microchip has malfunctioned, as a thought exercise and starting point for response through sound. In response to Jacques Attali’s claim that music is prophecy, The Prophetic Sound asks us to consider if noise can communicate in an unbridled, unfiltered, way that is somehow not culturally coded -before it becomes sound that is recognised, refined, manipulated and exploited for musical or other cultured purpose. Featuring students from Reading, Brighton, LCC and Goldsmiths alongside more established artists and academics from across the UK, this event brings into focus locations where pattern, timbre, pitch, organisation and sequencing of sounds become distinguishable from noise and asks us to consider, through diversion within such locations, new origins for future communication systems. The Prophetic Sound included talks, films, presentations and performances from: Ryo Ikeshiro / Inigo Wilkins / Neal Spowage / Dane Sutherland / Poulomi Desai / Benedict Drew / AAS / Polly Fibre / Steven Dickie As part of The Prophetic Sound, POLLYFIBRE (Ellison, C.) performed LIVE RECORDING with Amplified Scissors. This industrial activity by POLLYFIBRE short-circuits the complicated chain that is music production. The distinctive roles of consumer, producer, composer, and performer collapse in a series of live ‘cuts’ where vinyl discs are produced with amplified scissors. Production happens through action and action becomes production. A limited edition of 9 flexi discs were produced and available for special collectors at the event.
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We describe a one-port de-embedding technique suitable for the quasi-optical characterization of terahertz integrated components at frequencies beyond the operational range of most vector network analyzers. This technique is also suitable when the manufacturing of precision terminations to sufficiently fine tolerances for the application of a TRL de-embedding technique is not possible. The technique is based on vector reflection measurements of a series of easily realizable test pieces. A theoretical analysis is presented for the precision of the technique when implemented using a quasi-optical null-balanced bridge reflectometer. The analysis takes into account quantization effects in the linear and angular encoders associated with the balancing procedure, as well as source power and detector noise equivalent power. The precision in measuring waveguide characteristic impedance and attenuation using this de-embedding technique is further analyzed after taking into account changes in the power coupled due to axial, rotational, and lateral alignment errors between the device under test and the instruments' test port. The analysis is based on the propagation of errors after assuming imperfect coupling of two fundamental Gaussian beams. The required precision in repositioning the samples at the instruments' test-port is discussed. Quasi-optical measurements using the de-embedding process for a WR-8 adjustable precision short at 125 GHz are presented. The de-embedding methodology may be extended to allow the determination of S-parameters of arbitrary two-port junctions. The measurement technique proposed should prove most useful above 325 GHz where there is a lack of measurement standards.
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A boundary integral equation is described for the prediction of acoustic propagation from a monofrequency coherent line source in a cutting with impedance boundary conditions onto surrounding flat impedance ground. The problem is stated as a boundary value problem for the Helmholtz equation and is subsequently reformulated as a system of boundary integral equations via Green's theorem. It is shown that the integral equation formulation has a unique solution at all wavenumbers. The numerical solution of the coupled boundary integral equations by a simple boundary element method is then described. The convergence of the numerical scheme is demonstrated experimentally. Predictions of A-weighted excess attenuation for a traffic noise spectrum are made illustrating the effects of varying the depth of the cutting and the absorbency of the surrounding ground surface.
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There is considerable interest in the use of porous asphalt (PA) surfacing on highways since physical and subjective assessments of noise have indicated a significant advantage over conventional non-porous surfaces such as hot rolled asphalt (HRA) used widely for motorway surfacing in the UK. However, it was not known whether the benefit of the PA surface was affected by the presence of roadside barriers. Noise predictions have been made using the Boundary Element Method (BEM) approach to determine the extent to which the noise reducing benefits of PA could be added to the screening effects of noise barriers in order to obtain the overall reduction in noise levels
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Results are presented of a study of a performance of various track-side railway noise barriers, determined by using a two- dimensional numerical boundary element model. The basic model uses monopole sources and has been adapted to allow the sources to exhibit dipole-type radiation characteristics. A comparison of boundary element predictions of the performance of simple barriers and vehicle shapes is made with results obtained by using the standard U.K. prediction method. The results obtained from the numerical model indicate that modifying the source to exhibit dipole characteristics becomes more significant as the height of the barrier increases, and suggest that for any particular shape, absorbent barriers provide much better screening efficiency than the rigid equivalent. The cross-section of the rolling stock significantly affects the performance of rigid barriers. If the position of the upper edge is fixed, the results suggest that simple absorptive barriers provide more effective screening than tilted barriers. The addition of multiple edges to a barrier provides additional insertion loss without any increase in barrier height.
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A numerical model using boundary element techniques is discussed which enables the insertion loss for various noise barriers of complex profile and surface cover to be calculated. The model is applied to single-foundation noise barriers to which additional side-panels are added to create fork-like profiles. Spectra of insertion loss and mean insertion loss results over a range of receiver positions for a broadband source are presented. It is concluded that ‘multiple-edged’ barriers show a significant increase in acoustic-efficiency over a simple vertical screen. Adding lightweight side-panels would be a relatively inexpensive measure, and one which could be applied to barriers already in existence. This type of barrier would also allow the height of the construction to be kept to a minimum.
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Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.