Journal of Signal Processing Systems is an academic journal published by Springer. (ISSN 1939-8018, impact factor 1.8).
Aims and scope
Journal of Signal Processing Systems publishes research papers on the design and implementation of systems for signal processing and machine learning. The journal is published in twelve issues and is distributed to engineers, researchers, and educators in the general field of signal processing systems.
The key subject areas of interest to the journal are:
System Design and Implementation
• Algorithm/architecture co-design
• Design methods and implementation approaches for DSP algorithms, machine learning, pattern recognition, and image/video/multimedia processing
• System design methodologies
• Embedded systems for signal processing and machine learning
• FPGA and ASIC implementations
• System-on-Chip and Network-on-Chip designs
• Software implementations for signal processing and machine learning
• System performance analysis (including measurement, modeling, and simulation) of signal processing systems
Architectures
• Architectures for embedded signal processing
• Accelerators for signal processing and machine learning
• Accelerators for embedded computer vision
• Multi-core and many-core signal processors
• Architectures for emerging signal processing and machine learning applications
Applications
• Machine learning
• Acoustics and speech processing
• Image/video/multimedia
• Biomedical signal processing
• Wireless communication and sensor networks
• Genomic signal processing
• Emerging applications in signal processing and machine learning
Journal of Signal Processing Systems considers original, peer-reviewed content as well as extended versions of high quality workshop, symposium, and conference papers related to design and implementation of signal processing and machine learning systems. Among other areas, the journal provides an excellent forum for special issues on signal processing and machine learning applications, algorithms, and architectures of timely interest.
Authors benefit from Online FirstTM Publication – in which articles are available and citable online by their DOI (Digital Object Identifier) in advance of print publication. This ensures a fast time-to-publication for accepted papers and enables a wide electronic readership for the journal content.