We estimate a realistic process for noise trading to help theorists calibrate their models. For this purpose we characterize the trades executed by individual investors, who are natural candidates for the role of noise traders because their trades are (on average) cross-correlated, loss making, and weakly correlated with stocks’ future fundamentals. We use transactions data from a retail broker...

Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process that result in pixel values that do not reflect the true intensities of the real scene (Gagnon & Smaili, 1996). There are several ways that noise can be introduced into an image, depending on how the image is created. For example if the image is scanned from a photograph made ...

In image processing and pattern recognition, the accuracy of most algorithms is dependent on a good parameterization, generally a computation scale or an estimation of the amount of noise, which may be global or variable within the input image. Recently, a simple and linear time algorithm for arc detection in images was proposed [1]. Its accuracy is dependent on the correct evaluation of the am...