상호 정보 포텐셜과 델타함수를 이용한 블라인드 알고리듬의 복잡도 개선

Abstract

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 w eight update process. In this paper, for the purpose of reducin g the computational complexity, a new method of the gradient calc ulation 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 sa me gradient learning curves as the CIPD algorithm. Even under stro ng 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. ☞ keyword : cross-information potential, Dirac-delta, computation al complexity, impulsive noise, CIPD.