Adjustment of adaptive digital filter coefficients in modular codes

The main advantage of adaptive digital filters is the minimum error of their output response. It is reached by recalculation of values of coefficients of the filter. The conducted researches have shown that the known algorithms of adjustment of coefficients of the adaptive digital filter are inexped...

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Bibliographic Details
Published in:2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) pp. 1167 - 1170
Main Authors: Veligosha, Alexander V., Kaplun, Dmitry I., Bogaevskiy, Danil V., Gulvanskiy, Vyacheslav V., Voznesenskiy, Alexander S., Kalmykov, Igor A.
Format: Conference Proceeding
Language:English
Published: IEEE 01.01.2018
Subjects:
adaptive digital filter
Adaptive filters
digital filter
Filtering algorithms
Filtering theory
Finite impulse response filters
modular codes
orthogonal bases
output sample
rank of a number
residue number system
Signal processing algorithms
Wiener filters
ISBN:9781538643396, 1538643391
Online Access:Get full text
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Summary:The main advantage of adaptive digital filters is the minimum error of their output response. It is reached by recalculation of values of coefficients of the filter. The conducted researches have shown that the known algorithms of adjustment of coefficients of the adaptive digital filter are inexpedient to be used at their implementation in the RNS codes. The new consecutive algorithm of recalculation of coefficients which application allows to carry out adjustment of coefficients of modular digital filters much quicker, than the existing algorithms is presented in article. At the same time for carrying out recalculation of each coefficient of the modular digital filter it is necessary to execute one operation of subtraction, one operation of multiplication and one transaction of addition of the module, i.e. time of recalculation is proportional to a filter order. Thus, it is obvious that use of the developed algorithm allows to reduce time expenditure in comparison with earlier known algorithms of adaptation.
ISBN:9781538643396
1538643391
DOI:10.1109/EIConRus.2018.8317298