Abstract
A self-calibrating analog-to-digital (A/D) converter employing a T-Model neural network is described. Errors of the converter due to offset and device mismatch are corrected by a simple error back propagation algorithm in the T-Model neural network. An experimental A/D converter using standard 5-μm CMOS IC circuits demonstrates high-performance analog-to-digital conversion and self-calibration.
Original language | English |
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Pages (from-to) | 533-536 |
Number of pages | 4 |
Journal | Proceedings - IEEE International Symposium on Circuits and Systems |
Volume | 1 |
State | Published - 1995 |
Event | Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, USA Duration: 1995/04/30 → 1995/05/03 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering