Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/59263| Title: | Particle swarm optimization of a rail-to-rail delay element for maximum linearity |
| Authors: | Gauci, Jordan Lee Gatt, Edward Casha, Owen De Cataldo, Giacinto Grech, Ivan Micallef, Joseph |
| Keywords: | Mathematical models Transistors Integrated circuits -- Design and construction Genetic algorithms |
| Issue Date: | 2019 |
| Publisher: | Institute of Electrical and Electronics Engineers |
| Citation: | Gauci, J. L., Gatt, E., Casha, O., De Cataldo, G., Grech, I., & Micallef J. (2019). Particle swarm optimization of a rail-to-rail delay element for maximum linearity. 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT), Paris. |
| Abstract: | This paper illustrates the use of the Particle Swarm Optimization (PSO) algorithm to maximize the linearity of a rail-to-rail delay element. Previous approaches relied on approximating the piecewise time-delay model of the delay element through either the Newton Polynomial or the Lagrange Polynomial methods. While adequate linearity was achieved in both cases, this could be further improved. This work successfully employed the PSO algorithm to improve the linearity by reducing the mean square error such that the delay element exhibits a spurious-free dynamic range of 29.62 dB, with a delay range of 170.4 ns. The results were verified in Cadence using the X-FAB 0.18 μm technology. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/59263 |
| Appears in Collections: | Scholarly Works - FacICTMN |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Particle_swarm_optimization_of_a_rail-to-rail_delay_element_for_maximum_linearity_2019.pdf Restricted Access | 354.32 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.