Objective: To measure and analyse noise levels in the learn-

a step change of aircraft noise in residential areas

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• NOISE limits the minimum signal level that a circuit can process with acceptable quality. Can you identify the signal buried in the noise? How does the minimal signal must be with respect to the noise level?

We present a simple overlapping generations model of an asset market in which irrational noise traders with erroneous stochastic beliefs both affect prices and earn higher expected returns. The unpredictability of noise traders ’ beliefs creates a risk in the price of the asset that deters rational

The topic of this article is the estimation of the colored noise level in audio signals with mixed noise and sinusoidal components. The noise envelope model is based on the assumptions that the envelope varies only slowly with frequency and that the noise amplitudes obey a Rayleigh distribution

A constrained optimization type of numerical algorithm for removing noise from images is presented. The total variation of the image is minimized subject to constraints involving the statistics of the noise. The constraints are imposed using Lagrange multipliers. The solution is obtained using

Abstract The noise level at GEOSCOPE seismograph stations operating in 1995 has been studied in order to quantify the quality of stations for periods ranging from 0.2 to 8000 sec. The power spectral density curves presented in this article are a useful tool for selecting stations as a function

that the overcomplete system is incoherent, it is shown that the optimally sparse approximation to the noisy data differs from the optimally sparse decomposition of the ideal noiseless signal by at most a constant multiple of the noise level. As this optimal-sparsity method requires heavy (combinatorial) computational

that has been contaminated with additive noise, the goal is to identify which elementary signals participated and to approximate their coefficients. Although many algorithms have been proposed, there is little theory which guarantees that these algorithms can accurately and efficiently solve the problem