A novel ROM-less architecture for Direct Digital Frequency Synthesizer based on Linear Neural Networks

Author

Karthikeyan, G.C. ; Lakshmanan, K. ; Hariharan, K.

fYear

2015

fDate

19-20 March 2015

Firstpage

1

Lastpage

4

Abstract

In Conventional Direct Digital Frequency Synthesizer, the presence of ROM results in large size and complexity. Some DDFS is based on a mathematical series which also has some computational time delay. This paper deals with the Artificial Neural Network based DDFS architecture with linear transfer function, unlike the non-linear transfer function [3], which has low complexity, low computational delay and high spectral purity. The proposed DDFS has a high SNR (Signal to Noise Ratio) of about 48dB.

Keywords

circuit analysis computing; direct digital synthesis; neural nets; read-only storage; ROM-less architecture; artificial neural network based DDFS architecture; computational time delay; direct digital frequency synthesizer; high SNR; high signal-to-noise ratio; high spectral purity; linear neural networks; linear transfer function; low complexity; low computational delay; mathematical series; Biological neural networks; Complexity theory; Computer architecture; Frequency synthesizers; Generators; Hardware; Neurons; Artificial Neural Network; Direct Digital Frequency Synthesis; low complexity; spectral purity;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-6817-6

Type

conf

DOI

10.1109/ICIIECS.2015.7192855

Filename

7192855