An efficient analog circuit sizing method based on machine learning assisted global optimization
Machine learning-assisted global optimization methods for speeding up analog integrated
circuit sizing is attracting much attention. However, often a few typical analog integrated …
circuit sizing is attracting much attention. However, often a few typical analog integrated …
Distributed and expensive evolutionary constrained optimization with on-demand evaluation
Expensive optimization problems (EOPs) are common in industry and surrogate-assisted
evolutionary algorithms (SAEAs) have been developed for solving them. However, many …
evolutionary algorithms (SAEAs) have been developed for solving them. However, many …
A multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems
Integrating data-driven surrogate models and simulation models of different accuracies (or
fidelities) in a single algorithm to address computationally expensive global optimization …
fidelities) in a single algorithm to address computationally expensive global optimization …
An efficient method for complex antenna design based on a self adaptive surrogate model-assisted optimization technique
Surrogate models are widely used in antenna design for optimization efficiency
improvement. Currently, the targeted antennas often have a small number of design …
improvement. Currently, the targeted antennas often have a small number of design …
Joint optimization of sizing and layout for AMS designs: Challenges and opportunities
Recent advances in analog device sizing algorithms show promising results on the
automatic schematic design. However, the majority of the sizing algorithms are based on …
automatic schematic design. However, the majority of the sizing algorithms are based on …
Dnn-opt: An rl inspired optimization for analog circuit sizing using deep neural networks
Analog circuit sizing takes a significant amount of manual effort in a typical design cycle.
With rapidly developing technology and tight schedules, bringing automated solutions for …
With rapidly developing technology and tight schedules, bringing automated solutions for …
A hybrid regressor and classifier-assisted evolutionary algorithm for expensive optimization with incomplete constraint information
Surrogate-assisted evolutionary algorithms (SAEAs) have become a popular tool to solve
expensive optimization problems and have been gradually used to deal with expensive …
expensive optimization problems and have been gradually used to deal with expensive …
Efficient global optimisation of microwave antennas based on a parallel surrogate model‐assisted evolutionary algorithm
Computational efficiency is a major challenge for evolutionary algorithm (EA)‐based
antenna optimisation methods due to the computationally expensive electromagnetic …
antenna optimisation methods due to the computationally expensive electromagnetic …
[HTML][HTML] CMOS Operational Amplifier Design for Industrial and Biopotential Applications: Comprehensive Review and Circuit Implementation
This paper provides a detailed exploration of CMOS operational amplifiers (Op-Amps)
aimed at enhancing understanding of their development, design, and application. To …
aimed at enhancing understanding of their development, design, and application. To …
SADEA-II: A generalized method for efficient global optimization of antenna design
Efficiency improvement is of great significance for simulation-driven antenna design
optimization methods based on evolutionary algorithms (EAs). The two main efficiency …
optimization methods based on evolutionary algorithms (EAs). The two main efficiency …