Comparative performance analysis of FPGA-based MAC unit using non-conventional number system in TVL domain for signal processing algorithm
by Aniruddha Ghosh; Amitabha Sinha
International Journal of Nanoparticles (IJNP), Vol. 12, No. 1/2, 2020

Abstract: Today, the complication of binary digital hardware system is progressively growing. Due to this fact, new methodologies for efficiently describing and realising the digital systems are explored in this paper. Multi-valued logic methodology offers a few preferences over existing binary digital system. One of the well-known multi-valued logic systems is ternary value logic (TVL) system. It is seen that all kind of digital signal processing (DSP) algorithms widely use multiply-accumulate (MAC) operation for superior digital processing system. To implement high performance DSP algorithms MAC unit is used extensively. In current scenario, it is seen that non-conventional, non-binary number system-based architecture is also exhibited better performance. The example of such non-conventional, non-binary number systems is ternary residue number systems (TRNSs) and double base ternary number system (DBTNS). Here, a comparative study is made on performance analysis of MAC unit using various non-conventional, non-binary number system. All the architecture is mapped on FPGA for analysis its performance.

Online publication date: Tue, 24-Mar-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Nanoparticles (IJNP):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com