The Scientific World Journal

Computational Intelligence Techniques for Real-Time Signal Processing in Embedded Systems

Publishing date
17 Apr 2015
Submission deadline
28 Nov 2014

Lead Editor

1Incheon National University, Yeonsu-gu, Republic of Korea

2Università degli Studi di Milano, Milano, Italy

3Xidian University, Xi'an, China

4Sichuan University, Chengdu, China

This issue is now closed for submissions.

Computational Intelligence Techniques for Real-Time Signal Processing in Embedded Systems

This issue is now closed for submissions.


In many cases, signal processing algorithms for embedded systems that are developed and verified theoretically sound for certain embedded systems applications. However, during the actual applications, trade-off analysis is needed to accomplish its real-time performance. Meanwhile, computational intelligence-based signal processing approaches have strongly established themselves as practical mathematical tools. This special issue is destined to solve the embedded system issues between the theory and practice of signal processing by computational intelligence-based approaches. We invite investigators to contribute original research articles as well as review articles that will stimulate the continuing efforts to understand the real-time computational intelligence techniques for embedded systems.

Potential topics include, but are not limited to:

  • Real-time digital images and watermarking
  • Modeling of multimedia systems
  • Real-time signal compression and analysis
  • Artificial intelligence for multimedia systems design methodologies and case studies
  • Multimedia processors and reconfigurable architectures
  • Spatial and temporal estimation and protection of media streams
  • Artificial learning systems for signal and information processing and evidential reasoning for recognition
  • Circuits and architectures for embedded multimedia systems
  • Software optimization and compiler techniques
  • Timing aspects of media streams
  • Scheduling of media processing
  • Resource and QoS management methods
  • Real-time kernels, OS, and middleware support
  • Fuzzy and rough sets for signal processing and vision
  • Neuronal mechanisms of signal processing
  • Artificial learning systems medical images
  • Color and illumination processing
  • Tracking for inferring shapes and 3D motions
  • Performance assessment algorithms
  • Validation and verification
  • Emerging trends
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