Fpga-Based Implementation Of Signal Processing Systems, 2Nd Edition

There is now a growing interest in using FPGAs for an increasing range of applications, notably Big Data. The 2^nd edition of FPGA-based Implementation of Signal Processing will be extensively updated to reflect the latest evolution in FPGA technology, and addressing the considerable interest which has developed in applying acceleration using FPGAs to Big Data applications in areas such as bioinformatics, and oil and gas data sets.

Roger Woods is a full professor and Research Director for the Electronics and Computer Engineering Cluster at Queens University Belfast. His research interests include heterogeneous programmable systems and system-level tools for data, signal and image processing and telecommunications. He is on the Advisory Board for the IEEE Technical Advisory Group on the Design and Implementation of Signal Processing Systems, on the Editorial Board for the ACM Transactions on Reconfigurable Technology and Systems, Journal of VLSI Signal Processing Systems and IET Proceedings on Computer and Digital Techniques, and on the program committee of a number of IEEE FPGA-based conferences. He has co-founded a spin-off company, Analytics Engines Ltd., which looks to accelerate data analytics and acts as their Chief Scientist. He holds 4 patents and has published over 200 papers.

John McAllister is an academic at Queen’s University Belfast. His research interest lies in domain-specific embedded computing for signal and data processing, including dataflow languages and system design, distributed signal processing and machine learning and compilation and system synthesis. This work spans a wide spectrum of applications, from biomedical through software defined radio, neuromorphic systems and large-scale analytics. He is an Associate Editor of IEEE Transactions on Signal Processing, a member of the Editorial Board of Journal of Signal Processing Systems, a member of the Advisory Board to the IEEE Technical Committee on Design and Implementation of Signal Processing Systems, founding Chief Editor of the IEEE Signal Processing Society Resource Center (http://rc.signalprocessingsociety.org/) and a co-founder of Analytics Engines Ltd.

Gaye Lightbody is a Lecturer within the School of Computing and Mathematics in Ulster University. She received an M.Eng. (1995) and a PhD (2000) in Electrical and Electronic Engineering from Queen’s University Belfast. Her PhD, High Performance VLSI Architectures for Recursive Least Squares Adaptive Filtering, involved the research and development into a scalable efficient architecture for highly intensive adaptive beamforming applications. Gaye worked in industry from 2000 to 2005 for Amphion Semiconductor developing intellectual property cores for ASIC and FPGA solutions in the areas of audio, image and video processing. Since joining Ulster University, after Amphion, her research interests have included biomedical signal processing, Brain Computer Interfaces, FPGAs and high performance computing.

Ying Yi is currently a Senior Software Engineer at SN Systems, a wholly owned subsidiary of Sony Interactive Entertainment Inc. She has a PhD on DSP architectural Synthesis Tools for FPGAs from the School of Electrical and Electronic Engineering, Queen’s University Belfast, 2003. She was a Research Fellow at Integrated Micro and Nano Systems (IMNS) Institute, University of Edinburgh from 2004 to 2009 and a Senior Software Engineer at Spiral Gateway Ltd. from 2007 to 2009. Her research interests include software tool flow for the reconfigurable architecture and the single-chip multi-core architectures, compiler optimisation and code generation. She holds 1 patent and has published more than 30 refereed research papers on Journal of VLSI Signal Processing, IEEE Transactions on Computer-Aided Design, IEEE Transactions on Very Larger Scale Integration (VLSI) Systems, and Scalable Computing: Practice and Experience, Scientific International Journal for Parallel and Distributed Computing, and various IEEE conferences.