In this paper, L1 minimization refers to finding the minimum L1-norm solution to an
overdetermined linear system y= X· p. The underdetermined variant of the same problem …

Compressed sensing (CS) is a technique for signal sampling below the Nyquist rate, based
on the assumption that the signal is sparse in some transform domain. The acquired signal …

Compact representation of signals and images is a key for many applications. Compactness
is often achieved through linear transforms with good energy concentration property. We …

Wavelets play a key role in many applications like image representations and compression,
which is a main issue in the process of reducing the size in bytes of a digital image file to …

Denoising is an important issue in signal processing. Noise, caused by sensors or by
quantization effects during digitalization or compression, can significantly influence the …

Actual economic crisis initiated numerous debates on fiscal policy of the European Union
(EU) and unrealistic convergence demands placed upon the Member States, where the …

In this paper, the relative intersection of confidence intervals (ICI) rule is used to adaptively
determine window sizes around each observed point in purpose of denoising. The relative …

Many microscopy images, or 3D depth maps can be represented using piecewise constant
models. They usually contain noise due to sensor imperfectness. In this paper, an improved …

To meet the great demand of the ever-growing global market through process monitoring in
real time, a high processing speed is required without loss of performance in industrial …