To this aim, we have performed extensive measurement campaigns with wideband radios. His research encompasses fundamental theories, algorithm design, and experimentation for a broad range of real-world problems. His current research topics include network localization and navigation, network interference exploitation, intrinsic wireless secrecy, adaptive diversity techniques, ultra-wide bandwidth systems, optical transmission systems, and space communications systems.
Sumner Award. His research interests involve theory and experimentation of wireless systems and networks including network localization, adaptive diversity communications, cooperative relaying techniques, and network secrecy. Ellersick Prize. He organized and chaired a number of IEEE conferences. Currently investigated directions include high spatial resolutions, high frame rates, wide color gamut and high bit-depth rendering. The human visual system is able to perceive a wide range of colors and luminous intensities, as present in outdoor scenes in everyday real life, ranging from bright sunshine to dark shadows.
However, current traditional imaging technologies cannot capture nor reproduce such a broad range of luminance. High dynamic range HDR imaging technologies enable the capture, processing and display of images containing a much wider range of illumination compared to traditional imaging solutions. To achieve this, all aspects of the imaging pipeline need to be rethought and redesigned, which has led to an active area of research. In this tutorial, the focus is on the capture, processing and display of HDR video, presenting the state-of-the-art in hardware and software technologies and discussing the main challenges pertinent to this exciting field.
By providing a broad coverage, the tutorial is expected to be of interest to a wide audience with different backgrounds and expectations, with the ambition to offer a comprehensive understanding on several topics that encompass HDR video. He was founder and editor-in-chief of ACM Transactions on Applied Perception, and authored books on high dynamic range imaging, color imaging, computer graphics and natural image statistics.
He enjoys research that spans different disciplines, including color science, high dynamic range imaging and human visual perception. He has published more than papers in these areas, and was member of more than 50 program committees. He was program co-chair of 6 conferences and workshops, including the Eurographics Symposium on Rendering Previously, he worked as post-doc researcher in the same lab, starting from July He completed a master degree and a Ph. His research interests span different fields of image and video processing, including single and multi-view video coding, high-dynamic range imaging, video quality assessment, video surveillance, image and video forensics, image and video analysis.
He is co-author of more than 40 research publications.
Frederic received his M. He is the recipient of two ISO awards for his contributions. His research interests include image and video coding, high dynamic range imaging, distributed video coding, 3D video, visual quality assessment, video surveillance, privacy protection, image and video analysis, multimedia content search and retrieval, and video transmission over wireless network.
He is the author or co-author of more than research publications and holds 17 patents issued or pending. In this tutorial we would like to explore whether there are viable alternatives to this choice. We will see that, in order to truly overcome the inherent limitations of Fourier Acoustics, we need to rethink our analysis approach and, in particular, our signal decomposition strategy. This we do by introducing a novel wave-field decomposition methodology based on Gabor frames, which is more suitable for local in the space-time domain representations. Based on this new framework for computational acoustics, we define the plenacoustic ray-space transform and its conditions of invertibility, and we show how this new instrument can be used for efficiently and effectively approaching a far wider range of problems, ranging from simple source separation; to environment shape inference; to swift object-based manipulation of acoustic wavefields.
This tutorial is divided into three parts. In the former we offer an overview of conventional wave-field decomposition strategies, as derived from Fourier Acoustics. In the second part we push the boundaries of these tools through various generalization strategies.
In the latter we introduce an example of wave-field representation and decomposition strategy based on Gabor frames, and we show how to develop analysis and rendering solutions based on this representation. In each one of the three parts we introduce and discuss examples of application, and compare approaches.
His graduate studies included a joint graduate program with the University of California, Berkeley. His research interests are in the area of multimedia signal processing, with particular focus on audio and acoustic signal processing. He also worked on problems of multidimensional signal processing, 3D vision and nonlinear systems. He coauthored over scientific publications on international journals and congresses as well as numerous patents in the multimedia signal processing area. He then joined the Dept. His research interests are mainly on applications of signal processing to acoustics, with special emphasis on acoustic scene analysis and rendering based on microphone and loudspeaker arrays, and plenacoustic processing.
In order to enable IoT service capabilities, 5G wireless networks will need to bring a drastic energy efficiency improvement and will need to develop energy harvesting capabilities. This energy chase will cover low-energy devices and network elements, and will rely on the availability of renewable energy sources, dedicated power sources, as well as the possibility of harvesting energy directly from the radio waves that are primarily used for data transmission.
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This leads to a new design space, where the availability of energy is not deterministic anymore but may depend on environmental factors, the interference may not necessarily be harmful as it may be a natural source electromagnetic-based power to be used for replenishing the batteries of low-energy devices, and the intended signals may be exploited for both data transmission and energy harvesting. This paradigm-shift introduces a new concept in the design of 5G wireless networks: energy-neutrality. Energy-neutral networks are systems that not only make an efficient use of the available energy, but, more importantly, that operate in a complete self-powered fashion.
The present tutorial provides the audience with a complete survey of the potential benefits, research challenges, implementation efforts and application of technologies and protocols for achieving energy-neutrality, as well as the mathematical tools for their modeling, analysis and optimization. This tutorial is unique of its kind, as it tackles both system-level modeling and optimization aspects, which are usually treated independently. Special focus will be put on two methodologies for enabling the system-level modeling and the system-level and distributed optimization of energy-neutral 5G wireless networks: stochastic geometry and fractional programming.
In the proposed tutorial, we illustrate how several candidate transmission technologies, communication protocols, and network architectures for 5G can be modeled, studied, optimized, and compared for their energy-neutral operation. Brief biography of presenters Dr.
Alessio Zappone was born in in Rome, Italy. He obtained his Master degree in telecommunication engineering and his Ph. His Ph. After obtaining his Ph. Alessio's research interests lie in the area of communication networks and signal processing, with main focus on resource allocation techniques for energy efficiency optimization. He received the Laurea cum laude and the Ph. Eduard A.
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Jorswieck was born in in Berlin, Germany. He received his Diplom-Ingenieur M.
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- ECE - Digital Signal Processing Laboratory :: ECE ILLINOIS.
- Digital signal processing?
Eduard's main research interests are in the area of signal processing for communications and networks, applied information theory, and communications theory. He has published more than 80 journal papers, more than conference papers, 3 monographs, and 10 book chapters papers on these topics, and has filed 5 patents.
Several structured laboratory exercises, such as sampling, digital filtering, and modulation, followed by an extensive DSP project of the student's choice. To familiarize students with the fundamentals of operating and analyzing real time digital signal processing systems, including the required theory, the hardware used to sample and process the signals, and real time software development environments. An extensive project emphasis develops system-level design skills in a complex, unstructured problem context. Conference papers describing the ECE course design, goals, methods, and philosophies have been published in:.
Kramer, M. Haun, S.
- Modular Functions of One Variable IV: Proceedings of the International Summer School, University of Antwerp, RUCA, July 17 – August 3, 1972.
- Dancing in the Dark (My Struggle, Book 4);
- Lectures — European School of Information Theory.
Appadwedula, D. Sachs, and D.
Jun, D. Jones, M. ECE serves several primary and a number of secondary educational goals. Primary goals include:. The course can be divided roughly into two halves a uniform component with weekly laboratory exercises and oral examinations, and a design project phase each of which addresses somewhat different subsets of primary and secondary course goals. By the completion of the uniform weekly laboratory assignments after about eight weeks , the students should be able to do the following:. Use a modern real-time DSP hardware system and development environment to implement, debug, and test real-time signal processing algorithms.
Understand basic DSP microprocessor architecture. Program a DSP microprocessor in embedded language. Understand and explain sampling and filter theory, including basic multirate theory, and recognize and analyze artifacts such as aliasing. Theoretical DSP analyses and derivations are typically performed on discrete-time signal models with no amplitude inaccuracies quantization error , "created" by the abstract process of sampling.
Numerical methods require a quantized signal, such as those produced by an ADC. The processed result might be a frequency spectrum or a set of statistics. But often it is another quantized signal that is converted back to analog form by a digital-to-analog converter DAC.
In DSP, engineers usually study digital signals in one of the following domains: time domain one-dimensional signals , spatial domain multidimensional signals , frequency domain , and wavelet domains. They choose the domain in which to process a signal by making an informed assumption or by trying different possibilities as to which domain best represents the essential characteristics of the signal and the processing to be applied to it.
A sequence of samples from a measuring device produces a temporal or spatial domain representation, whereas a discrete Fourier transform produces the frequency domain representation.