Topic Editors

Dr. Nestor Evmorfopoulos
Department of Electrical and Computer Engineering, University of Thessaly, 38221 Volos, Greece
Prof. Dr. Alkiviadis Hatzopoulos
School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Prof. Dr. George I. Stamoulis
Department of Electrical and Computer Engineering, University of Thessaly, 38221 Volos, Greece

New Developments for Circuit Design: Synthesis, Modeling, Simulation, and Applications

Abstract submission deadline
5 August 2024
Manuscript submission deadline
5 October 2024
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898

Topic Information

Dear Colleagues,

This Topic will present New Developments for Circuit Design: Synthesis, Modeling, Simulation, and Applications. These developments include modeling, simulation, and synthesis for Analog, Mixed-signal, RF (AMS/RF), and multi-domain (nanoelectronics, biological, MEMS, optoelectronics, etc.) integrated circuits and systems, as well as, emerging technologies and applications. Open-source tools and methods for IC design and experiences with modeling, simulation, and synthesis techniques in diverse application areas are also welcomed. Objective technologies include CMOS, beyond CMOS, and More-than-Moore such as MEMs, power devices, sensors, passives, etc.

This topic seeks to publish original reviews, original articles or communications. We encourage submissions of manuscripts focusing on, but not limited to, current research, novel concepts, technologies and approaches in basic and advanced aspects of Circuit Design.

  1. CAD and EDA methodologies and tools for AMS systems (CAD/EDA)

Synthesis, Sizing and Optimization

  • Multi-level Synthesis Methods
  • Physical Synthesis Methods
  • High-frequency Circuits and Systems Design
  • Low-Power and Energy-Aware Design
  • Parasitic-Aware Design
  • Variability-aware & Reliability-Aware Design
  • Sizing and Optimization Methods
  • Procedural Design Methods

Modeling

  • Performance Modeling
  • Power and Electro-thermal Modeling
  • Reliability and Variability Modeling
  • RF/microwave/mm-wave Modeling
  • Model Order Reduction
  • Modeling for Signal Integrity / Power Integrity
  • Electromagnetic Compatibility and Signal Integrity
  • Electromagnetic Theory and Modeling
  • Transmission Line Theory and Modeling
  • Automated Model Generation

Simulation, Verification and Test

  • Behavioral Simulation
  • Numerical and Symbolic Simulation Methods
  • RF Circuit Simulation Methods
  • Multilevel Simulation Techniques
  • Analysis of Variability Effects
  • Simulation for Signal Integrity/Power Integrity
  • Formal and Functional Verification
  • Functional Safety
  • Test and Design-for-Test Techniques
  1. Emerging technologies and applications (ETA)

CAD for/using Emerging Technologies

  • CAD for Bio-Electronic Devices, Bio-Sensors
  • CAD for Multi-Domain Devices and Circuits
  • CAD for Nanophotonics and Optical Devices / Interconnects
  • CAD using AI and ML Algorithms
  • CAD using Cloud Computing
  • AMS CAS Soft and Hard IP Blocks Generating Methodologies

Emerging Devices and Paradigms

  • Emerging Device Modeling (Steep-Slope, TFET, NCFET, PTM, Memristor)
  • Design Strategies using Emerging Devices
  • Emerging Devices in Security
  • Devices, Hardware and Methods for Bio-Inspired and Neuromorphic Computing

Hardware Security

  • Hardware Security primitives (PUFs, RNGs, ...)
  • Attacks and Countermeasures
  • Anticounterfeiting
  • Methods, Architectures and Tools for Secure Design
  1. AMS ICs and multi-domain design applications (DES)

Design Applications

  • Internet of Everything
  • Automotive Systems
  • Biomedical and Bio-inspired CAS
  • Low-Power Low Voltage CAS
  • Sensors and Sensing Systems
  • Security Systems
  • Aerospace Systems
  • Renewable Energy Systems

Dr. Nestor Evmorfopoulos
Prof. Dr. Alkiviadis Hatzopoulos
Prof. Dr. George I. Stamoulis
Topic Editors

Keywords

  • integrated circuits
  • mixed-signal
  • RF
  • nanoelectronics
  • biological
  • MEMS
  • optoelectronics

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Automation
automation
- 2.9 2020 20.6 Days CHF 1000 Submit
Electronics
electronics
2.6 5.3 2012 16.8 Days CHF 2400 Submit
Eng
eng
- 2.1 2020 28.3 Days CHF 1200 Submit
Hardware
hardware
- - 2023 15.0 days * CHF 1000 Submit
Micromachines
micromachines
3.0 5.2 2010 17.7 Days CHF 2600 Submit
Signals
signals
- 3.2 2020 26.1 Days CHF 1000 Submit

* Median value for all MDPI journals in the first half of 2024.


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Published Papers (1 paper)

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13 pages, 688 KiB  
Article
Deterministic Multi−Objective Optimization of Analog Circuits
by Zihan Xu, Zhenxin Zhao and Jun Liu
Electronics 2024, 13(13), 2510; https://doi.org/10.3390/electronics13132510 - 26 Jun 2024
Viewed by 352
Abstract
Stochastic optimization approaches benefit from random variance to produce a solution in a reasonable time frame that is good enough for solving the problem. Compared with them, deterministic optimization methods feature faster convergence rates and better reproducibility but may get stuck at a [...] Read more.
Stochastic optimization approaches benefit from random variance to produce a solution in a reasonable time frame that is good enough for solving the problem. Compared with them, deterministic optimization methods feature faster convergence rates and better reproducibility but may get stuck at a local optimum that is insufficient to solve the problem. In this paper, we propose a group−based deterministic optimization method, which can efficiently achieve comparable performance to heuristic optimization algorithms, such as particle swarm optimization. Moreover, the weighted sum method (WSM) is employed to further improve our deterministic optimization method to be multi−objective optimization, making it able to seek a balance among multiple conflicting circuit performance metrics. With a case study of three common analog circuits tested for our optimization methodology, the experimental results demonstrate that our proposed method can more efficiently reach a better estimation of the Pareto front compared to NSGA−II, a well−known multi−objective optimization approach. Full article
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