Planck 2013 results. II. Low Frequency Instrument data processing
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An approach to analysis of time series of edge localized modes (ELMs) is proposed. It is based on the use of the autoregressive moving average model, which decomposes time series into deterministic and noise components. Despite the inclusion of nonlinearit ...
In this paper, we present an analytical noise modeling methodology for lateral nonuniform MOSFET. We demonstrate that the noise properties of lateral nonuniform MOSFETs are considerably different from the prediction obtained with the conventional Klaassen- ...
In the "missing data" (MD) approach to noise robust automatic speech recognition (ASR), speech models are trained on clean data, and during recognition sections of spectral data dominated by noise are detected and treated as "missing". However, this all-or ...
We report on the low-frequency electronic noise properties of individual multi-walled carbon nanotubes (CNTs). We present experimental evidence of the key role played by the structural quality of the tube and its gaseous environment on the excess noise lev ...
An upper bound is established on the usefulness of noisy feedback for the interference channel (IC). The bound is based on the Hekstra-Willems dependence-balance arguments for two-way channels. For Gaussian ICs, the results suggest that feedback loses its ...
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Particle filtering is now established as one of the most popular method for visual tracking. Within this framework, two assumptions are generally made. The first is that the data are temporally independent given the sequence of object states. In this paper ...
For classification problems, it is important that the classifier is trained with data which is likely to appear in the future. Discriminative models, because of their nature to focus on the boundary between classes rather than data itself, usually do not h ...
A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of two stages. The first stage computes a fuzzy derivative for eight different directions. The second stage uses these fuzzy derivatives to ...
In the "missing data" (MD) approach to noise robust automatic speech recognition (ASR), speech models are trained on clean data, and during recognition sections of spectral data dominated by noise are detected and treated as "missing". However, this all-or ...
This work deals with factorial models for multiple time series. Its core content puts it at the interface between statistics and finance. After a brief description of the historical link between the two sciences, it reviews the literature on factorial mode ...
