Exploration of High-Dimensional Performance Spaces via Clustering
Year: 2025
Type: article
Abstract: Performance spaces obtain all possible combinations of competing performance parameters for analog integrated circuits, like gain and bandwidth. The best combinations of those performances form the so-called Pareto front. While these spaces contain a lot of information, visualizing them—especially in high dimensions—can be overwhelming and difficult. Therefore, we present a combination of Parallel Coordinates plots together with a clustering algorithm in order to allow the exploration of performance spaces in a simple and intuitive manner. To compute approximations of those high-dimensional spaces, we use a parallelized version of a state-of-the-art box-coverage algorithm. Several numerical simulations for operational transconductance amplifiers demonstrate the functionality and efficiency of our concept for up to eight-dimensional performance spaces.
Source: IFAC-PapersOnLine
Authors: Benedikt Ohse, Christopher Schneider
Institution: Ernst Abbe University of Applied Sciences Jena
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408969460