New signal-processing algorithms have been shown to help mitigate the impact of turbulence in free-space optical experiments, potentially bringing ‘free space’ internet a step closer to reality. The ...

Technology is continuously advancing and exponentially increasing the amount of data produced. Data comes from a multitude of sources and formats, requiring systems to process different algorithms.

Signal processing algorithms, architectures, and systems are at the heart of modern technologies that generate, transform, and interpret information across applications as diverse as communications, ...

Compressive sensing is a paradigm shift in signal acquisition and processing that exploits the intrinsic sparsity of many natural and engineered signals to enable ...

Signal processing is pervasive in today’s vehicles, in applications ranging from engine controllers to entertainment systems. With annual automotive sales now at roughly 60 million units worldwide, it ...

The notion of “signal processing” might seem like something impenetrably complex, even to scientists. However, the fact is that most of them have already being doing it for a long time, albeit in an ...

As processors have steadily become faster and less expensive, systems with signal processing algorithms have increasingly been implemented as software running on a processor. One of the first steps in ...

Figure | Working principle of the intelligent metasurface. Concept and workflow of the no-code multimodal OCT platform. An illustrative schematic demonstrating the primary capabilities of the ...

The residue number system (RNS) offers a non-positional arithmetic framework in which integers are represented as sets of residues with respect to a chosen moduli set. In digital signal processing ...

UD's Signal and Image Processing Lab is designed to support graduate and undergraduate research in the areas of signal and image processing. The lab provides office space for graduate students and has ...

CATALOG DESCRIPTION: discrete-time random process, second-order statistics, autoregressive and moving average processes, linear prediction, Wiener filter, stochastic gradient (Least Mean Square) ...