• Bulletin of the Korean Mathematical Society
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• v.56 no.3
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• pp.757-777
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• 2019

In this paper, we study the convergence analysis of the sequences generated by the proximal point method for an infinite family of pseudo-monotone equilibrium problems in Banach spaces. We first prove the weak convergence of the generated sequence to a common solution of the infinite family of equilibrium problems with summable errors. Then, we show the strong convergence of the generated sequence to a common equilibrium point by some various additional assumptions. We also consider two variants for which we establish the strong convergence without any additional assumption. For both of them, each iteration consists of a proximal step followed by a computationally inexpensive step which ensures the strong convergence of the generated sequence. Also, for this two variants we are able to characterize the strong limit of the sequence: for the first variant it is the solution lying closest to an arbitrarily selected point, and for the second one it is the solution of the problem which lies closest to the initial iterate. Finally, we give a concrete example where the main results can be applied.

• ETRI Journal
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• v.46 no.3
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• pp.421-431
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• 2024

In this study, a direct position tracking method for non-circular (NC) signals using distributed passive arrays is proposed. First, we calculate the initial positions of sources using a direct position determination (DPD) approach; next, we transform the tracking into a compensation problem. The offsets of the adjacent time positions are calculated using a first-order Taylor expansion. The fusion calculation of the noise subspace is performed according to the NC characteristics. Because the proposed method uses the signal information from the previous iteration, it can realize automatic data associations. Compared with traditional DPD and two-step localization methods, our novel process has lower computational complexity and provides higher accuracy. Moreover, its performance is better than that of the traditional tracking methods. Numerous simulation results support the superiority of our proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.691-698
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• 2003

We extend the sue of the method of least square to develop a recursive algorithm for the design of adaptive transversal filters such that, given the least-square estimate of this vector of the filter at iteration n-l, we may compute the updated estimate of this vector at iteration n upon the arrival of new data. We begin the development of the RLS algorithm by reviewing some basic relations that pertain to the method of least squares. Then, by exploiting a relation in matrix algebra known as the matrix inversion lemma, we develop the RLS algorithm. An important feature of the RLS algorithm is that it utilizes information contained in the input data, extending back to the instant of time when the algorithm is initiated. In this paper, we propose new tap weight updated RLS algorithm in adaptive transversal filter with data-recycling buffer structure. We prove that convergence speed of learning curve of RLS algorithm with data-recycling buffer is faster than it of exiting RLS algorithm to mean square error versus iteration number. Also the resulting rate of convergence is typically an order of magnitude faster than the simple LMS algorithm. We show that the number of desired sample is portion to increase to converge the specified value from the three dimension simulation result of mean square error according to the degree of channel amplitude distortion and data-recycle buffer number. This improvement of convergence character in performance, is achieved at the B times of convergence speed of mean square error increase in data recycle buffer number with new proposed RLS algorithm.

• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.845-849
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• 2012

The next-generation wireless communication requires fast transmission speeds with various services and high reliability. In order to satisfy these needs we study MIMO system used layered space time coded system (LST) combining space time trellis codes (STTC) with turbo codes. In LST, two codes that are inner and outer codes are concatenated in the serial fashion. The inner codes are turbo Pi codes suggested in DVB-RCS NG system, and outer codes are STTC codes proposed by Blum. The interleaver technique is used to efficiently combine two codes. And we proposed and simulated that a full iteration method between turbo decoder and BCJR decoder to improve the performance instead of only processing inner-iteration turbo decoder. The simulation results of proposed effective layered method show improving BER performance about 1.3~1.5dB than conventional one.

• 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.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.2
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• pp.43-53
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• 1993

There exist two difficulties in the nonlinear wave-body problems. First is the abrupt behavior near the intersection point between the body and the free surface, and second is the far field treatment. In this paper, the far field treatment is considered. The main idea is the Taylor series expansion of free-surface geometry and the application of F.F.T. algorithm. The numerical step is as follows. The velocity potential is expressed by the Green's theorem. and the solution is obtained by iteration method. In the iteration stage, the expressions by the Green's theorem are transformed to the convolution forts with the expansion of free surface by the wave slope. Here F.F.T. is applied, so the computing time can be of O(Nlog N) where N is the number of unknowns. The numerical analysis is carried out and the results are compared with other results in linear floating body problem and nonlinear moving pressure patch problem, and good agreements are obtained. Finally nonlinear floating body radiation problem is carried out with computing time of O(Nlog N).

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.1
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• pp.65-73
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• 2007

In the inverse perturbation method, enormous computational resource was required to obtain reliable results, because all unspecified DOFs were considered as unknown variables. Thus, in the present study, a reduced system method is used to condense the unspecified DOFs by using the specified DOFs, and to improve the computational efficiency as well as the solution accuracy. In most of the conventional reduction methods, transformation errors occur in the transformation matrix between the unspecified DOFs and the specified DOFs. Thus it is hard to obtain reliable and accurate solution of inverse perturbation problems by reduction methods due to the error in the transformation matrix. This numerical trouble is resolved in the present study by adopting iterative improved reduced system(IIRS) as well as by updating the transformation matrix at every step. In this reduction method, system accuracy is related to the selection of the primary DOFs and Iteration time. And both are dependent to each other So, the two level condensation method (TLCS) is selected as Selection method of primary DOFs for increasing accuracy and reducing iteration time. Finally, numerical verification results of the present iterative inverse perturbation method (IIPM) are presented.

• ETRI Journal
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• v.34 no.6
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• pp.869-878
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• 2012

A beam design method based on signal-to-leakage-plus-noise ratio (SLNR) has been recently proposed as an effective scheme for multiuser multiple-input multiple-output downlink channels. It is shown that its solution, which maximizes the SLNR at a transmitter, can be simply obtained by the generalized eigenvectors corresponding to the dominant generalized eigenvalues of a pair of covariance matrices of a desired signal and interference leakage plus noise. Under time-varying channels, however, generalized eigendecomposition is required at each time step to design the optimal beam, and its level of complexity is too high to implement in practical systems. To overcome this problem, a predictive beam design method updating the beams according to channel variation is proposed. To this end, the perturbed generalized eigenvectors, which can be obtained by a perturbation theory without any iteration, are used. The performance of the method in terms of SLNR is analyzed and verified using numerical results.

• Coupled systems mechanics
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• v.1 no.2
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• pp.183-204
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• 2012

A method for the analysis of wave scattering in 3-D elastic full space is developed by means of the coupled boundary-volume integral equation, which takes into account the effects of both the boundary of inclusions and the uctuation of the wave field. The wavenumber domain formulation is used to construct the Krylov subspace by means of FFT. In order to achieve the wavenumber domain formulation, the boundary-volume integral equation is transformed into the volume integral equation. The formulation is also focused on this transform and its numerical implementation. Several numerical results clarify the accuracy and effectiveness of the present method for scattering analysis.