Browsing by Keywords "Sparse signals"
Now showing items 1-6 of 6
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Average error in recovery of sparse signals and discrete fourier transform
(IEEE, 2012-04)In compressive sensing framework it has been shown that a sparse signal can be successfully recovered from a few random measurements. The Discrete Fourier Transform (DFT) is one of the transforms that provide the best ... -
Compressive sensing based target detection in delay-doppler radars
(IEEE, 2013)Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rate random samples. With this property, CS approach has many applications. Radar systems, which deal with sparse signal due ... -
Filtered Variation method for denoising and sparse signal processing
(IEEE, 2012)We propose a new framework, called Filtered Variation (FV), for denoising and sparse signal processing applications. These problems are inherently ill-posed. Hence, we provide regularization to overcome this challenge by ... -
A new OMP technique for sparse recovery
(IEEE, 2012)Compressive Sensing (CS) theory details how a sparsely represented signal in a known basis can be reconstructed using less number of measurements. However in reality there is a mismatch between the assumed and the actual ... -
Phase retrieval of sparse signals from Fourier Transform magnitude using non-negative matrix factorization
(IEEE, 2013)Signal and image reconstruction from Fourier Transform magnitude is a difficult inverse problem. Fourier transform magnitude can be measured in many practical applications, but the phase may not be measured. Since the ... -
Sıkıştırılmış algılama kullanarak Uzaklık-Doppler radar hedef tespiti
(IEEE, 2014-04)Sıkıştırılmış algılama(SA) fikri, az sayıda ölçümlerden seyrek bir sinyalin geri çatımını mümkün kılar. SA yaklaşımı bir çok farklı alanda uygulamalara sahiptir. Bu alanlardan birisi de radar sistemleridir. Bu makalede, ...
