CMOS Analog Artificial Neural Network
This paper focuses on the design and simulation of low power analog artificial neural network (ANN) using 180nm CMOS technology in Cadence Virtuoso. The neurons here are designed in such a manner that they could perform key biological functions, namely multiplication of the signal, summation, and thresholding. The design exploits advantages of analog computation, leading to lower power dissipation and better processing speed in comparison to purely digital implementations. This makes it particularly suitable for real-time applications. Simulations are performed at different process corners for power consumption analysis to ensure the performance of the network, establishing its efficiency for low-power AI solutions. The key design components include Gilbert cell multipliers for weight multiplication and CMOS-based sigmoid activation functions to provide efficient analog alternatives of the traditional digital elements of a neural network.
Authors
- Suman Lata Tripathi (ORCID: https://orcid.org/0000-0002-1684-8204)
- S Harshith
- K. Ramesh Babu
- Jagmeet Singh
Institutions
- Lovely Professional University (IN)
Publication Details
- Published
- 2025-04-05
- DOI
- https://doi.org/10.1109/devic63749.2025.11012358
- Primary Topic
- Analog and Mixed-Signal Circuit Design
- Type
- article
- Field-Weighted Citation Impact
- 0.00