Title :
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
fDate :
4/1/1996 12:00:00 AM
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;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
