Journal
2015 IEEE 45TH INTERNATIONAL SYMPOSIUM ON MULTIPLE-VALUED LOGIC
Volume -, Issue -, Pages 103-108Publisher
IEEE
DOI: 10.1109/ISMVL.2015.13
Keywords
-
Categories
Funding
- Grants-in-Aid for Scientific Research [15K06030] Funding Source: KAKEN
Ask authors/readers for more resources
An analog-to-digital converter (ADC) based on neural networks is proposed, and the feasibility of using nonbinary coding is discussed with circuit simulation. An amoeba-inspired computing technique is used to construct the present ADC, where switched-capacitor circuits are used as unit neurons. Dummy units are also added to improve the stability of circuit operation. For an ADC with a radix of 2, large quantization errors were observed due to the local minima. It was found that introducing a radix smaller than 2 effectively reduced the quantization error. Low-power operation can be expected by using a dynamic analog circuit technique in the present neuro-ADC.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available