z-logo
open-access-imgOpen Access
Genetic Algorithms and Particle Swarm Optimization Mechanisms for Through-Silicon Via (TSV) Noise Coupling
Author(s) -
Khaoula Ait Belaid,
Hassan Belahrach,
Hassan Ayad
Publication year - 2021
Publication title -
applied computational intelligence and soft computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 10
eISSN - 1687-9732
pISSN - 1687-9724
DOI - 10.1155/2021/8830395
Subject(s) - particle swarm optimization , noise (video) , coupling (piping) , genetic algorithm , computer science , electronic engineering , transfer function , algorithm , engineering , artificial intelligence , electrical engineering , machine learning , image (mathematics) , mechanical engineering
In this paper, two intelligent methods which are GAs and PSO are used to model noise coupling in a (ree-Dimensional Integrated Circuit (3D-IC) based on TSVs.(ese techniques are rarely used in this type of structure. (ey allow computing all the elements of the noise model, which helps to estimate the noise transfer function in the frequency and time domain in 3D complicated systems. Noise models include TSVs, active circuits, and substrate, which make them difficult to model and to estimate. Indeed, the proposed approaches based on GA and PSO are robust and powerful. To validate the method, comparisons among the results found by GA, PSO, measurements, and the 3D-TLMmethod, which presents an analytical technique, are made. According to the obtained simulation and experimental results, it is found that the proposed methods are valid, efficient, precise, and robust.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom