• Communications of the Korean Mathematical Society
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• v.25 no.4
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• pp.655-669
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• 2010

In this paper we propose new primal-dual interior point methods (IPMs) for $P_*(\kappa)$ linear complementarity problems (LCPs) and analyze the iteration complexity of the algorithm. New search directions and proximity measures are defined based on a class of kernel functions, $\psi(t)=\frac{t^2-1}{2}-{\int}^t_1e{^{q(\frac{1}{\xi}-1)}d{\xi}$, $q\;{\geq}\;1$. If a strictly feasible starting point is available and the parameter $q\;=\;\log\;\(1+a{\sqrt{\frac{2{\tau}+2{\sqrt{2n{\tau}}+{\theta}n}}{1-{\theta}}\)$, where $a\;=\;1\;+\;\frac{1}{\sqrt{1+2{\kappa}}}$, then new large-update primal-dual interior point algorithms have $O((1\;+\;2{\kappa})\sqrt{n}log\;n\;log\;{\frac{n}{\varepsilon}})$ iteration complexity which is the best known result for this method. For small-update methods, we have $O((1\;+\;2{\kappa})q{\sqrt{qn}}log\;{\frac{n}{\varepsilon}})$ iteration complexity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.153-158
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• 2017

This paper investigates a robust low-complexity design problem for tracking control of uncertain switched pure-feedback systems in the presence of unknown control direction. The completely unknown non-affine nonlinearities are assumed to be arbitrarily switched. By combining the nonlinear error transformation technique and Nussbaum-type functions, a robust tracking controller is designed without using any adaptive function approximators. Thus, compared with existing results, the proposed control scheme has the low-complexity property. From Lyapunov stability theory, it is shown that the tracking error remains within the preassigned transient and steady-state error bounds.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.153-164
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• 2010

A program consumes energy by executing its instructions. The amount of cosumed power is mainly proportional to algorithm complexity and it can be calculated by using complexity information. Generally, the complexity of a S/W is estimated by the microprocessor simulator. But, the simulation takes long time why the simulator is a software modeled the hardware and it only provides the information about computational complexity quantitatively. In this paper, we propose a complexity estimation method of analysis of S/W on source code level and produce the complexity metric mathematically. The function-wise complexity metrics give the detailed information about the calculation-concentrated location in function. The performance of the proposed method is compared with the result of the gate-level microprocessor simulator 'SimpleScalar'. The used softwares for performance test are $4{\times}4$ integer transform, intra-prediction and motion estimation in the latest video codec, H.264/AVC. The number of executed instructions are used to estimate quantitatively and it appears about 11.6%, 9.6% and 3.5% of error respectively in contradistinction to the result of SimpleScalar.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.10C
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• pp.887-901
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• 2002

Software management model divided into the software project model and design estimation model, software matrices model, reliability growth model, process improvement model(or process maturity model) etc. Among these software management models, software complexity model make an estimated of the product software. For a practice of software managed, need to guideline of the static analysis of software. Especially, Software complexity model introduced for the estimation of software quantity and program complexity. In case of measurement the software matrices, its need for us to analysis of software quality and products. On the other hand, we known that complexity program include many defects and consuming of source cost. So, we apply to complexity model using of the program complexity, control structure and volume matrices, interface metrics, process complexity metrics method. In this paper, we represent that the analysis of fault data detected during the system test. Also, we analysis of program control structure and interface, volume matrices in various aspect of switching software. Others, their results utilized similar of project and system development.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.16-26
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• 2001

This paper develops the fast dynamic programming technique to construct the subband structure yielding the maximum coding gain for given filter bases and a given limit of implementation complexity. We first derive the unified coding gain which can be applied to non-orthogonal filter basis as well as orthogonal filter basis and to arbitrary subband decompositions. Then, we verify that the unified coding gains in real systems are monotonically increasing function for the implementation complexities which are proportional to the number of subbands. By using this phenomenon, the implementation complexity and the coding gain are treated in the same way as the rate and distortion function. This makes it possible to use the Lagrangian multiplier method for finding the optimal subband decomposition producing the maximum coding gain [or a given limit of implementation complexity.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.384-390
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• 2004

In this paper we compare the performance of 4 different algorithms for converting the sampling frequency of an audio from 44.1KHz to 48KHz. The algorithms considered here include the basic polyphase method. sine function based method. multi-stage method. and B-spline based method. For a fair comparison, the sampling rate converters using the 4 algorithms are redesigned under a high fidelity condition. Then, their H/W complexities are compared in terms of the computational complexity and the memory size. As a result, it is shown that the basic polyphase method and sine function based method outperform the other two in terms of the computational complexity, while the B-spline based method requires less memory than the others.

• Communications of the Korean Mathematical Society
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• v.20 no.4
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• pp.827-835
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• 2005

As a tool of measuring the irregularity of curve, fractal dimensions can be used. For an irregular function, fractional calculus are more available. However, to know its fractional differentiability which is related to its complexity is complicated one. In this paper, variants of the Hausdorff dimension and the packing dimension as well as the derivative order are defined and the relations between them are investigated so that the differentiability of fractal curve can be explained through its complexity.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.4
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• pp.227-238
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• 2008

In this paper we extend primal-dual interior point algorithm for linear optimization (LO) problems to $P_*({\kappa})$ linear complementarity problems(LCPs) ([1]). We define proximity functions and search directions based on kernel functions, ${\psi}(t)=\frac{t^{p+1}-1}{p+1}-{\log}\;t$, $p{\in}$[0, 1], which is a generalized form of the one in [16]. It is the first to use this class of kernel functions in the complexity analysis of interior point method(IPM) for $P_*({\kappa})$ LCPs. We show that if a strictly feasible starting point is available, then new large-update primal-dual interior point algorithms for $P_*({\kappa})$ LCPs have $O((1+2{\kappa})nlog{\frac{n}{\varepsilon}})$ complexity which is similar to the one in [16]. For small-update methods, we have $O((1+2{\kappa})\sqrt{n}{\log}{\frac{n}{\varepsilon}})$ which is the best known complexity so far.

• Science of Emotion and Sensibility
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• v.8 no.1
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• pp.63-74
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• 2005

This research basically defines that relationship among simplicity/complexity, other product aesthetics and consumer preference. The goal of this research is to find answer 'How much the simplicity/complexity influence expressed functional shapes on products?' and 'What is relationship between simplicity/complexity and consumer preference?' This is process that first we make categorize products by analysis, and second we analyze each category group for fading propensity from consumers, and finally we verify through design process.

• ETRI Journal
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• v.44 no.3
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• pp.400-412
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• 2022

In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).