Advancements in Digital Signal Processing: Emerging Applications and Optimized Implementations
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 20 March 2027 | Viewed by 1064
Special Issue Editor
Interests: digital signal processing (DSP); adaptive signal processing; blind equalization/identification; fast computational algorithms; parallel and VLSI algorithms and architectures for communications and DSP; high-level DSP design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the new era of digital revolution, new advanced DSP applications have appeared. The advances in modern DSP applications, such as multimedia, big data, IoT, etc., have increased the importance of the optimization and efficient implementation of DSP algorithms and architectures, both for a VLSI or a software VLSI implementation. We can say that they represent an essential part of the research in such modern applications.
For real-time implementations of such modern DSP applications, an efficient optimization of such algorithms and architectures for an efficient VLSI implementation is often a critical and challenging issue. For example, real-time multimedia applications have increasingly greater performance requirements due to data processing and transmission of huge data volumes at high speeds, with resource constraints specific to portable devices.
This Special Issue focuses on papers that demonstrate how these design challenges can be overcome using innovative solutions.
Topics of interest for this Special Issue include, but are not limited to, the following:
- VLSI signal processing;
- Signal processing methods for efficient implementation;
- Optimization of the VLSI implementation of multimedia blocks;
- Low-power circuits and systems for DSP applications;
- Efficient adaptive/learning algorithms (low complexity/fast versions, optimized parameters, etc.);
- Tensor-based signal processing (efficient decomposition methods, low-rank approximations, etc.);
- Sparsity-aware algorithms.
Prof. Dr. Doru Florin Chiper
Guest Editor
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Keywords
- VLSI signal processing
- signal processing methods
- efficient implementation
- multimedia blocks
- low power circuits and systems
- efficient adaptive algorithms
- learning algorithms
- efficient decomposition methods
- low-rank approximations
- sparsity exploitation
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