• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.85-90
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• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.19-26
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• 2009

In this paper, a minimum Euclidian distance criterion between error PDF and Dirac delta function is introduced and a constant modulus type blind equalizer algorithm based on the criterion is proposed. The proposed algorithm using constant modulus error in place of actual error term of the criterion has superior convergence and steady state MSE performance, and the error signal of the proposed algorithm exhibits more concentrated density function in blind equalization environments. Simulation results indicate that the proposed method can be a reliable candidate for blind equalizer algorithms for multipoint communications.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.4
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• pp.295-299
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• 2011

Blind equalization techniques have been widely used in wireless communication systems. In this paper, we propose to apply the balanced information potentials to the criterion of minimum Euclidian distance between two PDFs with constant modulus errors for adaptive blind equalizers. One of the two PDFs is constructed with constant modulus error samples and another does with Dirac delta functions. Two information potentials derived from the criterion are balanced in order to have better performance by putting a weighting factor to each information potentials. The proposed blind algorithm has shown in the MSE convergence performance that it can produce enhanced performance by over 3 dB of steady state MSE.

• ETRI Journal
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• v.24 no.3
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• pp.239-246
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• 2002

We investigate an alternative blind adaptive multiuser detection scheme based on a non-canonical linearly constrained constant modulus (LCCM) criterion and prove that, under the constrained condition, the non-canonical linearly constrained constant modulus algorithm (LCCMA) can completely remove multiple -access interference. We further demonstrate that the non-canonical LCCM criterion function is strictly convex in the noise-free state, and that under the constrained condition, it is also strictly convex even where small noise is present. We present a simple method for selecting the constant as well as a stochastic gradient algorithm for implementing our scheme. Numerical simulation results verify the scheme's efficiency.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.87-95
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• 2009

As information theoretic learning techniques, error entropy minimization criterion (MEE) and maximum cross correntropy criterion (MCC) have been studied in depth for supervised learning. MEE criterion leads to maximization of information potential and MCC criterion leads to maximization of cross correlation between output and input random processes. The weighted combination scheme of these two criteria, namely, minimization of Error Entropy with Fiducial points (MEEF) has been introduced and developed by many researchers. As an approach to unsupervised, blind channel equalization, we investigate the possibility of applying constant modulus error (CME) to MEE criterion and some problems of the method. Also we study on the application of CME to MEEF for blind equalization and find out that MEE-CME loses the information of the constant modulus. This leads MEE-CME and MEEF-CME not to converge or to converge slower than other algorithms dependent on the constant modulus.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.283-287
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• 2004

In this paper, a method of designing the efficient batch blind equalization with low complexity using a micro genetic algorithm (GA), is presented. In general, the blind equalization techniques that are focused on the complexity reduction might be carried out with minor effect on the performance. Among the advanced various subjects in the field of GAs, a micro genetic algorithm is employed to identity the unknown channel impulse response in order to reduce the search space effectively. A new cost function with respect to the constant modulus criterion is suggested considering its relation to the Wiener criterion. We provide simulation results to show the superiority of the proposed techniques compared to other existing techniques.

• Geomechanics and Engineering
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• v.22 no.4
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• pp.277-290
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• 2020

This paper presents an elastic-plastic solution for the circular tunnel of elastic-strain softening behavior considering the pressure-dependent Young's modulus and the nonlinear dilatancy. The proposed solution is verified by the results of the field measuring and numerical simulation from a practical project, and a published closed-form analysis solution. The influence of each factor is discussed in detail, and the ability of Young's modulus and dilatancy characterizing the mechanical response of surrounding rock is investigated. It is found that, in low levels of support pressure, adopting the constant Young's modulus model will seriously misestimate the surrounding rock deformation. Using the constant dilatancy model will underestimate the surrounding rock deformation. When adopting the constant dilatancy model, as the dilation angle increases, the range of the plastic region increases, and the surrounding rock deformation weakens. When adopting the nonlinear dilatancy, the plastic region range and the surrounding rock deformation are the largest. The surrounding rock deformation using pressure-dependent Young's modulus model is between those resulted from two constant Young's modulus models. The constant α of pressuredependent Young's modulus model is the main factor affecting the tunnel displacement. The influence of α using a constant dilatancy model is much more apparent than that using a nonlinear dilatancy model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.760-767
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• 2010

For complex channel blind equalization, this study presents the performance and characteristics of two complex blind information theoretic learning algorithms (ITL) which are based on minimization of Euclidian distance (ED) between probability density functions compared to constant modulus algorithm which is based on mean squared error (MSE) criterion. The complex-valued ED algorithm employing constant modulus error and the complex-valued ED algorithm using a self-generated symbol set are analyzed to have the fact that the cost function of the latter forces the output signal to have correct symbol values and compensate amplitude and phase distortion simultaneously without any phase compensation process. Simulation results through MSE convergence and constellation comparison for severely distorted complex channels show significantly enhanced performance of symbol-point concentration with no phase rotation.

• 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.