[HTML][HTML] An exponential variation based PSO for analog circuit sizing in constrained environment

KG Shreeharsha, RK Siddharth, CG Korde… - … -International Journal of …, 2024 - Elsevier
This work presents an Exponential Variation based Particle Swarm Optimization (EV-PSO)
algorithm to improve the convergence rate and find an optimal solution to analog circuit …

Partition bound random number-based particle swarm optimization for analog circuit sizing

KG Shreeharsha, RK Siddharth, MH Vasantha… - IEEE …, 2023 - ieeexplore.ieee.org
This work introduces a Partition Bound Particle Swarm Optimization (PB-PSO) algorithm to
enhance convergence rates in analog circuit optimization. Two new parameters, and, are …

The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design

SK Ata, ZH Kong, A James, L Cai… - … on Circuits and …, 2024 - ieeexplore.ieee.org
Active learning, which aims to enhance modeling efficiency, precision, and cost
effectiveness through selective labeling, is emerging as a promising strategy for analog …

Space Sampling Techniques Comparison for a Synthetic Low-Pass Filter Bayesian Neural Network

J Dávalos-Guzmán, JL Chavez-Hurtado… - 2023 IEEE MTT-S …, 2023 - ieeexplore.ieee.org
This paper presents a comparative analysis of three sampling techniques for generating
space points to develop a Bayesian neural network (BNN) surrogate model of a synthetic …

Towards Safe and Efficient Analog Circuit Design: Active Learning for Feasibility Region Exploration

SK Ata, ZH Kong, A James, L Cai… - 2024 IEEE Asia …, 2024 - ieeexplore.ieee.org
Active learning (AL), a machine learning paradigm, allows models to focus on the most
informative data points, reducing reliance on extensive labeled data. This is particularly …