5 resultados para Noise pollution -- Catalonia -- Sarrià de Ter

em Massachusetts Institute of Technology


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Signalling off-chip requires significant current. As a result, a chip's power-supply current changes drastically during certain output-bus transitions. These current fluctuations cause a voltage drop between the chip and circuit board due to the parasitic inductance of the power-supply package leads. Digital designers often go to great lengths to reduce this "transmitted" noise. Cray, for instance, carefully balances output signals using a technique called differential signalling to guarantee a chip has constant output current. Transmitted-noise reduction costs Cray a factor of two in output pins and wires. Coding achieves similar results at smaller costs.

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Support Vector Machines Regression (SVMR) is a regression technique which has been recently introduced by V. Vapnik and his collaborators (Vapnik, 1995; Vapnik, Golowich and Smola, 1996). In SVMR the goodness of fit is measured not by the usual quadratic loss function (the mean square error), but by a different loss function called Vapnik"s $epsilon$- insensitive loss function, which is similar to the "robust" loss functions introduced by Huber (Huber, 1981). The quadratic loss function is well justified under the assumption of Gaussian additive noise. However, the noise model underlying the choice of Vapnik's loss function is less clear. In this paper the use of Vapnik's loss function is shown to be equivalent to a model of additive and Gaussian noise, where the variance and mean of the Gaussian are random variables. The probability distributions for the variance and mean will be stated explicitly. While this work is presented in the framework of SVMR, it can be extended to justify non-quadratic loss functions in any Maximum Likelihood or Maximum A Posteriori approach. It applies not only to Vapnik's loss function, but to a much broader class of loss functions.

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Urban air pollution and climate are closely connected due to shared generating processes (e.g., combustion) for emissions of the driving gases and aerosols. They are also connected because the atmospheric lifecycles of common air pollutants such as CO, NOx and VOCs, and of the climatically important methane gas (CH4) and sulfate aerosols, both involve the fast photochemistry of the hydroxyl free radical (OH). Thus policies designed to address air pollution may impact climate and vice versa. We present calculations using a model coupling economics, atmospheric chemistry, climate and ecosystems to illustrate some effects of air pollution policy alone on global warming. We consider caps on emissions of NOx, CO, volatile organic carbon, and SOx both individually and combined in two ways. These caps can lower ozone causing less warming, lower sulfate aerosols yielding more warming, lower OH and thus increase CH4 giving more warming, and finally, allow more carbon uptake by ecosystems leading to less warming. Overall, these effects significantly offset each other suggesting that air pollution policy has a relatively small net effect on the global mean surface temperature and sea level rise. However, our study does not account for the effects of air pollution policies on overall demand for fossil fuels and on the choice of fuels (coal, oil, gas), nor have we considered the effects of caps on black carbon or organic carbon aerosols on climate. These effects, if included, could lead to more substantial impacts of capping pollutant emissions on global temperature and sea level than concluded here. Caps on aerosols in general could also yield impacts on other important aspects of climate beyond those addressed here, such as the regional patterns of cloudiness and precipitation.

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This paper considers a connection between the deterministic and noisy behavior of nonlinear networks. Specifically, a particular bridge circuit is examined which has two possibly nonlinear energy storage elements. By proper choice of the constitutive relations for the network elements, the deterministic terminal behavior reduces to that of a single linear resistor. This reduction of the deterministic terminal behavior, in which a natural frequency of a linear circuit does not appear in the driving-point impedance, has been shown in classical circuit theory books (e.g. [1, 2]). The paper shows that, in addition to the reduction of the deterministic behavior, the thermal noise at the terminals of the network, arising from the usual Nyquist-Johnson noise model associated with each resistor in the network, is also exactly that of a single linear resistor. While this result for the linear time-invariant (LTI) case is a direct consequence of a well-known result for RLC circuits, the nonlinear result is novel. We show that the terminal noise current is precisely that predicted by the Nyquist-Johnson model for R if the driving voltage is zero or constant, but not if the driving voltage is time-dependent or the inductor and capacitor are time-varying

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This paper proposes three tests to determine whether a given nonlinear device noise model is in agreement with accepted thermodynamic principles. These tests are applied to several models. One conclusion is that every Gaussian noise model for any nonlinear device predicts thermodynamically impossible circuit behavior: these models should be abandoned. But the nonlinear shot-noise model predicts thermodynamically acceptable behavior under a constraint derived here. Further, this constraint specifies the current noise amplitude at each operating point from knowledge of the device v - i curve alone. For the Gaussian and shot-noise models, this paper shows how the thermodynamic requirements can be reduced to concise mathematical tests involving no approximatio