• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.773-781
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• 2010

Recently, Yun [8] proposed a new three-step iterative method with the fourth-order convergence for solving nonlinear equations. By using his ideas, we develop a general form of multi-step iterative methods with higher order convergence for solving nonlinear equations, and then we study convergence analysis of the multi-step iterative methods. Lastly, some numerical experiments are given to illustrate the performance of the multi-step iterative methods.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.219-225
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• 1998

The parameters in linear models with censored normal responses are usually estimated by the iterative maximum likelihood and least square methods. However, the iterative least square method is simple but hardly has theoretical justification, and the iterative maximum likelihood estimating equations are complicatedly derived. In this paper, we justify these methods via Wedderburn (1974)'s quasi-likelihood approach. This provides an explicit justification for the iterative least square method and also directly the iterative maximum likelihood method for estimating the regression coefficients.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.280-285
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• 2012

We propose self-encoded spread spectrum with two different iterative detection methods in multi-channel communication. The centralized iterative detection outperforms the iterative detection distributed over multiple channels. The results show that self-encoded spread spectrum with the centralized iterative detection is an excellent candidate for cognitive radio network.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1363-1379
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• 2011

Halpern iterative algorithm is one of the most cited in the literature of approximation of fixed points of nonexpansive mappings. Different authors modified this iterative algorithm in Banach spaces to approximate fixed points of nonexpansive mappings. One of which is Hu [8] and Yao et al [21] modification of Halpern iterative algorithm for nonexpansive mappings in Banach spaces. It is the purpose of this paper to thoroughly analyze this modification and its convergence conditions. Unfortunately, Hu [8] and Yao et al [21] control conditions imposed on the modified Halpern iterative algorithm to have strong convergence are found to be not sufficient. In this paper, counterexamples are constructed to prove that the strong convergence conditions of Hu [8] and Yao et al [21] are not sufficient. It is also proved that with some additional conditions on the control parameters, strong convergence of the defined iterative algorithm is obtained in different Banach space settings.

• Ocean Science Journal
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• v.41 no.4
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• pp.195-199
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• 2006

Comparative study was carried out for an acoustic iterative inverse method to estimate bubble size distributions in water. Conventional bubble sizing methods consider only sound attenuation for sizing. Choi and Yoon [IEEE, 26(1), 125-130 (2001)] reported an acoustic iterative inverse method, which extracts the sound speed component from the measured sound attenuation. It can more accurately estimate the bubble size distributions in water than do the conventional methods. The estimation results of acoustic iterative inverse method were compared with other experimental data. The experimental data show good agreement with the estimation from the acoustic iterative inverse method. This iterative technique can be utilized for bubble sizing in the ocean.

• Honam Mathematical Journal
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• v.39 no.1
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• pp.1-25
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• 2017

In this paper, we introduce a new scheme namely: CUIA-iterative scheme and utilize the same to prove a strong convergence theorem for quasi contractive mappings in Banach spaces. We also establish the equivalence of our new iterative scheme with various iterative schemes namely: Picard, Mann, Ishikawa, Agarwal et al., Noor, SP, CR etc for quasi contractive mappings besides carrying out a comparative study of rate of convergences of involve iterative schemes. The present new iterative scheme converges faster than above mentioned iterative schemes whose detailed comparison carried out with the help of different tables and graphs prepared with the help of MATLAB.

• Journal of applied mathematics & informatics
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• v.28 no.5_6
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• pp.1409-1418
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• 2010

In this paper, we present a preconditioned iterative method for solving linear systems Ax = b, where A is a Z-matrix. We give some comparison theorems to show that the rate of convergence of the new preconditioned iterative method is faster than the rate of convergence of the previous preconditioned iterative method. Finally, we give one numerical example to show that our results are true.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.451-463
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• 2010

In this paper, we introduce and study a class of completely generalized quasi-variational inclusions with fuzzy mappings. A new iterative algorithm for finding the approximate solutions and the convergence criteria of the iterative sequences generated by the algorithm are also given. These results of existence, algorithm and convergence generalize many known results.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.383-392
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• 1998

This paper proposes Generalized Stationary Iterative called GSI method. It is shown that the existing stationary iterative methods are special cases of GSI method. Convergence properties of this method are provided and their numerical experiments for linear systems with symmetric positive definite matrix are also provided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.798-809
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• 2013

In this paper, we propose robust relay and destination filter design methods for the multi-user peer-to-peer amplify-and-forward relaying systems while taking imperfect channel knowledge into consideration. Specifically, the relay and destination filter sets are developed to minimize the sum mean-squared-error (MSE). We first present a robust joint optimum relay and destination filter calculation method with an iterative algorithm. Motivated by the need to reduce computational complexity of the iterative scheme, we then formulate a simplified sum MSE minimization problem using the relay filter decomposability, which lead to two robust sub-optimum non-iterative design methods. Finally, we propose robust modified destination filter design methods which require only local channel state information between relay node and a specific destination node. The analysis and simulation results verify that, compared with the optimum iterative method, the proposed non-iterative schemes suffer a marginal loss in performance while enjoying significantly improved implementation efficiencies. Also it is confirmed that the proposed robust filter design methods provide desired robustness in the presence of channel uncertainty.