EconPapers    
Economics at your fingertips  
 

Implement Multichannel Fractional Sample Rate Convertor using Genetic Algorithm

Vivek Jain and Navneet Agrawal
Additional contact information
Vivek Jain: The College of Technology and Engineering, Department of Electronics and Communication, Udaipur, India
Navneet Agrawal: The College of Technology and Engineering, Department of Electronics and Communication, Udaipur, India

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2017, vol. 8, issue 2, 10-21

Abstract: In this paper reduce power of multichannel fractional sample rate convertor by minimized hamming distance between consecutive coefficients of filter using Genetic algorithm. The main component of multichannel fractional sample rate convertor is Cascaded multiple architecture finite impulse response filter (CMFIR filter). CMFIR is implemented by cascading of cascaded integrator-comb (CIC) & multiply accumulate architecture (MAC) FIR filter. Genetic algorithm minimizes the hamming distance between consecutive coefficients of CMFIR filter. By Minimizing the hamming distance of consecutive filter coefficient reduces the transaction from 0 to 1 or 1 to 0. These techniques reduce the switching activity of CMOS transistor which is directly reduces Dynamic power consumption by multichannel sample rate convertor, it also minimizes the total power consumption of multichannel fractional sample rate convertor. later than use genetic algorithm on 1 to 128 channel Down sample rate convertor total power reduced by 3.44% to 61.56%, dynamic power reduced by 9.09% to 56.25% .1 to 128 channel Up sample rate convertor total power reduced by 2.81% to 45.42%, dynamic power reduced by 4.76% to 56%, 1 to 128 channel fractional sample rate convertor total power reduced by 1.44% to 17.17%, dynamic power reduced by 6.25% to 19.92%.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJMDEM.2017040102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jmdem0:v:8:y:2017:i:2:p:10-21

Access Statistics for this article

International Journal of Multimedia Data Engineering and Management (IJMDEM) is currently edited by Chengcui Zhang

More articles in International Journal of Multimedia Data Engineering and Management (IJMDEM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

 
Page updated 2025-03-19
Handle: RePEc:igg:jmdem0:v:8:y:2017:i:2:p:10-21