Namyong Kim, Journal of Internet Computing and Services, Vol. 15, No. 3, pp. 71-78, Jun. 2014
10.7472/jksii.2014.15.3.71, Full Text:
Keywords: cross-information potential, Dirac-delta, computational complexity, Impulsive noise, CIPD

Abstract

The equalization algorithm based on the cross-information potential concept and Dirac-delta functions (CIPD) has outstanding ISI elimination performance even under impulsive noise environments. The main drawback of the CIPD algorithm is a heavy computational burden caused by the use of a block processing method for its weight update process. In this paper, for the purpose of reducing the computational complexity, a new method of the gradient calculation is proposed that can replace the double summation with a single summation for the weight update of the CIPD algorithm. In the simulation results, the proposed method produces the same gradient learning curves as the CIPD algorithm. Even under strong impulsive noise, the proposed method yields the same results while having significantly reduced computational complexity regardless of the number of block data, to which that of the e conventional algorithm is proportional.

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