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The proposed algorithms exploit multi-scale signal information through a multi-scale weighting approach.
With a local decomposition of a multi-scale signal, wavelet analysis is particularly suited to detect and follow the time evolution of the frequency distribution of a given time series (Ivanov et al., 2001; Kovacs et al., 2001; Lui, 2002; Mendes et al., 2005; Mandea and Balasis, 2006; Zaourar et al., 2006; Gaci et al., 2010).
Scale-space (Witkin, 1983) is a framework for multi-scale signal representation.
A multi-scale supervised neural architecture, called Multi-Scale SOON, is proposed for natural texture classification.
Firstly, NSCT is employed to decompose the image into multi-scales.
It is a multi-stakeholder, multi-variable, multi-scale problem.
These characteristics include multi-scale, multi-directional, and multi-precision.
Aimed at the detection problem of multi-frequency signal under colored noise background, a novel weak signal detection method based on stochastic resonance (SR) tuning by multi-scale noise is proposed.
It is clear that a multi-frequency signal modulates the phase history of SAR returned signals.
Such a mixing model is illustrated in Figure 1. Figure 1 Multi-microphone signal model.
Most of the current multi-scale IQA metrics use linear filters in the multi-resolution decomposition.
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