E6.4 - Biological Neural Coding for Adaptive Spiking Analog to Digital Conversion
- Event
- SMSI 2023
2023-05-08 - 2023-05-11
Nürnberg - Band
- Lectures
- Chapter
- E6 - Sensor Interface Electronics
- Author(s)
- H. Abd, A. König - Technical University of Kaiserslautern, Kaiserslautern (Germany)
- Pages
- 270 - 271
- DOI
- 10.5162/SMSI2023/E6.4
- ISBN
- 978-3-9819376-8-8
- Price
- free
Abstract
A conventional ADC in leading-edge integration technologies faces numerous challenges due to manufacturing deviations, signal swings, noise, etc. Designers of ADCs are shifting to the time domain and digital design techniques to manage these challenges. Consequently, we aim to design a novel self-adaptive spiking neural ADC (SN-ADC) with promising properties, e.g., low-voltage operation, technology scaling issues, noise-robust conditioning, and low power. In this work, we focus on designing one building block of our concept, a decoder that converts place coding to digital code.