52 resultados para noise


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The paper analyzes the performance of the unconstrained filtered-x LMS (FxLMS) algorithm for active noise control (ANC), where we remove the constraints on the controller that it must be causal and has finite impulse response. It is shown that the unconstrained FxLMS algorithm always converges to, if stable, the true optimum filter, even if the estimation of the secondary path is not perfect, and its final mean square error is independent of the secondary path. Moreover, we show that the sufficient and necessary stability condition for the feedforward unconstrained FxLMS is that the maximum phase error of the secondary path estimation must be within 90°, which is the only necessary condition for the feedback unconstrained FxLMS. The significance of the analysis on a practical system is also discussed. Finally we show how the obtained results can guide us to design a robust feedback ANC headset.

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Instability is a serious problem for acoustic Active Noise Cancellation (ANC) headsets as a result of large errors in estimating the transfer function of the plant. Typically this occurs when, for example, a wearer adjusts the headset. In this paper, the instability problem of adaptive ANC headset is addressed. To ensure stability of the whole system, we propose a hybrid solution consisting of an analog feedback loop parallel to the digital loop, and the role of the analog loop in stabilizing the headset is analyzed theoretically. Finally the methodology of implementing such a hybrid ANC headset is described in detail. The experiments carried out on the headset prototype show that the headset is robust under considerable fluctuations of the plant transfer characteristics, and has very good noise cancellation performance both for narrow-band and wide-band disturbances.

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When speech is in competition with interfering sources in rooms, monaural indicators of intelligibility fail to take account of the listener’s abilities to separate target speech from interfering sounds using the binaural system. In order to incorporate these segregation abilities and their susceptibility to reverberation, Lavandier and Culling [J. Acoust. Soc. Am. 127, 387–399 (2010)] proposed a model which combines effects of better-ear listening and binaural unmasking. A computationally efficient version of this model is evaluated here under more realistic conditions that include head shadow, multiple stationary noise sources, and real-room acoustics. Three experiments are presented in which speech reception thresholds were measured in the presence of one to three interferers using real-room listening over headphones, simulated by convolving anechoic stimuli with binaural room impulse-responses measured with dummy-head transducers in five rooms. Without fitting any parameter of the model, there was close correspondence between measured and predicted differences in threshold across all tested conditions. The model’s components of better-ear listening and binaural unmasking were validated both in isolation and in combination. The computational efficiency of this prediction method allows the generation of complex “intelligibility maps” from room designs. © 2012 Acoustical Society of America

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Harmonic analysis on configuration spaces is used in order to extend explicit expressions for the images of creation, annihilation, and second quantization operators in L2-spaces with respect to Poisson point processes to a set of functions larger than the space obtained by directly using chaos expansion. This permits, in particular, to derive an explicit expression for the generator of the second quantization of a sub-Markovian contraction semigroup on a set of functions which forms a core of the generator.

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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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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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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).

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'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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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.