IEEE Workshop on Signal Processing Systems, Taipei, Taiwan

Abbrevation

SiPS

Link

http://www.sips2013.org/

City

Taipei

Country

Taiwan

Deadline Paper

2013-04-19

Start Date

2013-10-16

End Date

2013-10-18

Abstract

IEEE Workshop on Signal Processing Systems (SiPS) is a major international forum for discussion of new technology progress and innovations in the design and implementation of signal processing systems. The focus is on emerging state–of–the–art signal processing systems (Cloud/Multimedia/Communications/Biosystems) and cutting–edge design platforms (VLSI/SoC/FPGA/Multicore/GPU) for current and future challenges in research and development. Proceedings will be published electronically and will be accessible on the IEEE Xplore Digital library. Prospective authors are invited to submit manuscripts on topics including, but not limited to: 1. Optimization of Signal Processing Algorithms and Architectures 1.1 Dataflow–based design and methodology 1.2 Optimization of signal processing algorithms 1.3 Compilers and tools for signal processing system design 1.4 Algorithm transformation and algorithm–to–architecture mapping 2. Software Based Design and Implementation of Signal Processing Systems 2.1 Low–power software techniques for green systems 2.2 Programmable digital signal processor architecture and systems 2.3 Application specific instruction–set processor (ASIP) architecture and systems 2.4 SIMD, VLIW, and multi–core CPU architecture and systems 2.5 Graphic processing unit (GPU) based massively parallel implementation 3. VLSI Based Design and Implementation of Signal Processing Systems 3.1 Low–power signal processing circuits and applications 3.2 High performance VLSI systems 3.3 FPGA and reconfigurable architecture based systems 3.4 System–on–chip and network–on–chip 4. Signal Processing Application Systems 4.1 Environmental awareness signal processing application systems 4.2 Biomedical signal processing and biosystems 4.3 Image, video, audio, speech and multimedia signal processing 4.4 Information forensics, security and cryptography 4.5 Communications and networking 4.6 Machine learning for signal processing 4.7 Sensing and sensor signal processing IEEE Workshop on Signal Processing Systems (SiPS) is a major international forum for discussion of new technology progress and innovations in the design and implementation of signal processing systems. The focus is on emerging state–of–the–art signal processing systems (Cloud/Multimedia/Communications/Biosystems) and cutting–edge design platforms (VLSI/SoC/FPGA/Multicore/GPU) for current and future challenges in research and development. Proceedings will be published electronically and will be accessible on the IEEE Xplore Digital library. Prospective authors are invited to submit manuscripts on topics including, but not limited to: 1. Optimization of Signal Processing Algorithms and Architectures 1.1 Dataflow–based design and methodology 1.2 Optimization of signal processing algorithms 1.3 Compilers and tools for signal processing system design 1.4 Algorithm transformation and algorithm–to–architecture mapping 2. Software Based Design and Implementation of Signal Processing Systems 2.1 Low–power software techniques for green systems 2.2 Programmable digital signal processor architecture and systems 2.3 Application specific instruction–set processor (ASIP) architecture and systems 2.4 SIMD, VLIW, and multi–core CPU architecture and systems 2.5 Graphic processing unit (GPU) based massively parallel implementation 3. VLSI Based Design and Implementation of Signal Processing Systems 3.1 Low–power signal processing circuits and applications 3.2 High performance VLSI systems 3.3 FPGA and reconfigurable architecture based systems 3.4 System–on–chip and network–on–chip 4. Signal Processing Application Systems 4.1 Environmental awareness signal processing application systems 4.2 Biomedical signal processing and biosystems 4.3 Image, video, audio, speech and multimedia signal processing 4.4 Information forensics, security and cryptography 4.5 Communications and networking 4.6 Machine learning for signal processing 4.7 Sensing and sensor signal processing