A full neural Gray-code-based ADC

Author

Daponte, Pasquale ; Grimaldi, Domenico ; Michaeli, Linus

Author_Institution

Dept. of Comput. Sci. & Electr. Eng., Salerno Univ., Italy

Volume

45

Issue

2

fYear

1996

fDate

4/1/1996 12:00:00 AM

Firstpage

634

Lastpage

639

Abstract

In this paper a new method of designing Gray-code-based analog-to-digital converters (ADC´s) is presented. The method, derived from research on the neural networks, has the aim of replacing all functional components needed in the ADC block scheme by a simple connection of analog neurons. First, the theory underlying the method and a functional description of the new neural ADC are given. Then, in order to highlight some of the design considerations, a simulation study of the ADC is provided. Finally, an 8-bit discrete-component prototype is discussed, and the experimental results are also given

Keywords

analogue-digital conversion; circuit CAD; circuit analysis computing; digital simulation; neural nets; 8-bit discrete-component prototype; Rademacher functions; analog neurons; analog-to-digital converters; design; differential nonlinearity; errors; neural Gray-code-based ADC; neural networks; simulation; Analog-digital conversion; Computational modeling; Computer science; Design methodology; Neural networks; Neurons; Proposals; Prototypes; Switches; Voltage;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.492801

Filename

492801