Abstract
The implementation of analog neural network and online analog learning circuits based on memristive crossbar has been intensively explored in the recent years. The design of various activation functions is important for neuromorphic circuits and systems, especially deep leaning neural networks. There are several implementations of sigmoid and tangent activation function, while the analog hardware implementation of the neural networks with linear activation functions is an open problem. Therefore, this paper introduces a multilayer perceptron design with linear activation function using TSMC 130 μ mCMOS technology. In this paper, the performance of the proposed linear activation function is illustrated. In addition, the temperature variation and noise analysis are shown.
Original language | English |
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Title of host publication | Proceedings of the 2nd International Conference on Computing and Network Communications, CoCoNet 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 245-249 |
Number of pages | 5 |
ISBN (Electronic) | 9781538659281 |
DOIs | |
Publication status | Published - Sep 28 2018 |
Event | 2nd International Conference on Computing and Network Communications, CoCoNet 2018 - Astana, Kazakhstan Duration: Aug 15 2018 → Aug 17 2018 |
Conference
Conference | 2nd International Conference on Computing and Network Communications, CoCoNet 2018 |
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Country | Kazakhstan |
City | Astana |
Period | 8/15/18 → 8/17/18 |
Keywords
- Crossbar
- Linear Activation Function
- Memristor
- Multilayer perceptron
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Electrical and Electronic Engineering