• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.1-8
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• 2010

This paper presentsthe performance study of blind equalizer algorithms for impulsive-noise environments based on Gaussian kernel and constant modulus error(CME). Constant modulus algorithm(CMA) based on CME and mean squared error(MSE) criterion fails in impulsive noise environment. Correntropy blind method recently introduced for impulsive-noise resistance has shown in PAM system not very satisfying results. It is revealed in theoretical and simulation analysis that the maximization of zero-error probability based on CME(MZEP-CME) originally proposed for Gaussian noise environments produces superior performance in impulsive noise channels as well. Gaussian kernel of MZEP-CME has a strong effect of becoming insensitive to the large differences between the power of impulse-infected outputs and the constant modulus value.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.26-32
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• 2013

Blind algorithms based on Information potential of output samples and a set of symbols generated in random order at the receiver go through performance degradation when biased impulsive noise is added to the channel since the cost function composed of information potentials has no variable to deal with biased signal. Aiming at the robustness against biased impulsive noise, we propose, in this paper, a modified information potential, and derived related blind algorithms based on augmented filter structures and a set of random-order symbols. From the simulation results of blind equalization for multipath channels, the blind algorithm based on the proposed information potential produced superior convergence performance in the environments of strong biased impulsive noise.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.3-10
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• 2013

Please In this paper, to cope with biased impulsive noise problems, a new information potential is proposed that can move the transmitted symbol points by modifying the information potential designed with Dirac-delta functions. Based on the proposed information potential a new blind algorithm is derived by employing an augmented filter structure. From the simulation results in the environment of biased impulsive noise, the conventional algorithms yield performance degradation by over 15 dB, but the proposed algorithm shows no performance degradation and holds the same steady state MSE of below -25 dB as after the initial convergence regardless of the channel conditions.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.11-17
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• 2016

In this paper, the optimum weight of the algorithm based on the cross information-potential with the delta functions (CIPD) is derived and its robustness against impulsive noise is studied. From the analysis of the behavior of optimum weight, it is revealed that the magnitude controlling operation for input plays the main role of keeping optimum weight of CIPD stable from the impulsive noise. The simulation results show that the steady state weight of CIPD is equivalent to that of MSE criterion. Also in the simulation environment of impulsive noise, unlike the LMS algorithm based on MSE, the steady state weight of CIPD is shown to be kept stable.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.17-24
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• 2014

Blind algorithms designed to maximize the probability that constant modulus errors become zero carry out some summation operations for a set of constant modulus errors at an iteration time inducing heavy complexity. For the purpose of reducing this computational burden induced from the summation, a new approach to the estimation of the zero-error probability (ZEP) of constant modulus errors (CME) and its gradient is proposed in this paper. The ZEP of CME at the next iteration time is shown to be calculated recursively based on the currently calculated ZEP of CME. It also is shown that the gradient for the weight update of the algorithm can be obtained by differentiating the ZEP of CME estimated recursively. From the simulation results that the proposed estimation method of ZEP-CME and its gradient produces exactly the same estimation results with a significantly reduced computational complexity as the block-processing method does.