In this paper, a complex-valued Zadoff–Chu measurement matrix is proposed and used in
an image-based quantized compressive sensing (CS) scheme. The results of theoretical …

Image denoising is a vital image processing phase aiming to improve the quality of images
and to make them more informative. In this paper, we propose a blind denoising approach …

In this paper, we present an approach to the reconstruction of signals exhibiting sparsity in a
transformation domain, having some heavily disturbed samples. This sparsity-driven signal …

Smart devices for image/video sensing are needed to work within the constraints of limited
bandwidth and low computing capabilities. In this context, Block based Compressive …

Battery parameter identification is a key challenge for battery management systems, as
parameterizing lithium-ion batteries is resource-intensive. Electrical circuit models (ECMs) …

Here, a novel image‐based quantized compressive sensing (QCS) framework based on
complex‐valued Vandermonde (Vander) matrix is proposed. In the proposed QCS …

Within the compressive sensing (CS) paradigm, sparse signals can be reconstructed based
on a reduced set of measurements, whereby reliability of the solution is determined by its …

The virtual (software) instrument with a statistical analyzer for testing algorithms for
biomedical signals' recovery in compressive sensing (CS) scenario is presented. Various …

Battery parameter identification is a main challenge to battery management systems today.
The parameterization of electrochemical processes in lithium-ion battery cells is both …

In this paper, a model-based firmware generator is presented towards complex sampling
schemes. The framework is capable of automatically generating a fixed-rate Shannon …