Application of Signal Processing and Computational Intelligence in High-Energy Calorimeter Systems
This special issue belongs to the section "Computing and Artificial Intelligence".
Special Issue Information
Dear Colleagues,
High-energy physics experiments rely on calorimeter systems to provide better measurements of the subproducts of particle collisions. In modern HEP experiments, calorimeter readout electronics need to cope with increases in the data rate and complexity of the experiments through the use of advanced digital signal processing (DSP) techniques and computational intelligence approaches.
In this Special Issue, we invite submissions of theoretical and experimental studies, as well as comprehensive review and survey papers, exploring cutting-edge research and recent advances in the following topics related to high-energy calorimetry:
- Data acquisition strategies;
- Signal conditioning circuits;
- Noise estimation methods;
- Signal estimation and detection;
- Optimal filtering methods;
- Nonlinear strategies for signal estimation;
- Linear and nonlinear computational modeling;
- Statistical signal processing;
- Optimization methods;
- Neural network systems;
- Artificial intelligence applications;
- FPGA solutions for signal processing;
- Real-time applications.
Dr. Bernardo Peralva
Dr. Gustavo Barbosa Libotte
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the Special Issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- data acquisition strategies
- signal conditioning circuits
- noise estimation methods
- signal estimation and detection
- optimal filtering methods
- nonlinear strategies for signal estimation
- linear and nonlinear computational modeling
- statistical signal processing
- optimization methods
- neural network systems
- artificial intelligence applications
- FPGA solutions for signal processing
- real-time applications
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Published Papers
Appl. Sci. - ISSN 2076-3417