• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.20-26
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• 2011

In this paper, we propose an efficient algorithm for reducing the complexity of LDPC code decoding by using node monitoring (NM) and Piecewise Linear Function Approximation (NP). This NM algorithm is based on a new node-threshold method, and the message passing algorithm. Piecewise linear function approximation is used to reduce the complexity for more. This algorithm was simulated in order to verify its efficiency. Simulation results show that the complexity of our NM algorithm is reduced to about 20%, compared with thoes of well-known method.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1231-1238
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• 2015

In this paper, we proposed an efficient algorithm using Node monitoring (NM) and Piecewise Linear Function Approximation(: NP) for reducing the complexity of LDPC code decoding. Proposed NM algorithm is based on a new node-threshold method together with message passing algorithm. Piecewise linear function approximation is used to reduce the complexity of the algorithm. This new algorithm was simulated in order to verify its efficiency. Complexity of our new NM algorithm is improved to about 20% compared with well-known methods according to simulation results.

• Journal of Broadcast Engineering
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• v.2 no.2
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• pp.194-205
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• 1997

In video compression standards such as MPEG and H.263. rate control is one of the key components for good coding performance. This paper presents a simple adaptive rate control scheme using a piecewise linear approximation model. While conventional buffer control approach is performed by adjusting the quantization parameter linearly according to the buffer fullness. the proposed approach uses a piecewise linear approximation model derived from logarithmic relation between the quantization parameter and bitrate in data compression. In addition. a forward analyzer performed in the spatial domain is used to improve image quality. Simulation results demonstrate that the proposed method provides better performance than the conventional one and reduces the fluctuation of the PSNR per frame while maintaining the quality of the reconstructed frames at a relatively stable level.

• Journal of Power Electronics
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• v.11 no.3
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• pp.327-334
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• 2011

Single-phase power factor correction (PFC) converter circuits are non-linear systems due to the contribution of their multiplier. This non-linearity causes difficulties in analysis and design. Models that reduce the system to a linear system involve considerable approximation, and produce results that are susceptible to instability problems. In this paper a piecewise affine (PWA) system is introduced for describing the nonlinear averaged model. Then robust output feedback controllers are established in terms of the linear matrix inequality (LMI). Simulation and experiments results show the effectiveness of the proposed control method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1122-1127
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• 2003

Typical application of detecting piecewise-linear curves includes vectorizing of scanned drawings whirh is a vital step in installing any geographic information system. This paper considers the problem of optimally approximating a piecewise linear curve to a set of digital points while satisfying given intersection angles between each pair of neighboring lines. The criterion for optimality is to minimize the sum of squared deviations. The problem is formulated as an unconstrained nonlinear programming model. An algorithm which guarantees an optimal solution is then proposed and its validity is tested with both a synthetically generated image and a real image. The test results illustrate the excellent performance of the proposed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.26-36
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• 2021

The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.1
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• pp.7-14
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• 1983

Linear feature such as lines and curves are one of important features in image processing. In this paper, new method of linear feature detection is suggested. Also, we have studied approximation technique which transforms detected linear feature into data structure for the practical. This method is based on graph theory and principle of this method is based on minimal spanning tree concept which is widely used in edge linking process. By postprocessing, Hairs and inconsistent line segments are removed. To approximate and describe traced linear feature, piecewise linear approximation is adapted. The algorithm is demonstrated through computer simulations.

• ETRI Journal
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• v.15 no.2
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• pp.35-51
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• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

• Korean Journal of Mathematics
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• v.22 no.4
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• pp.599-609
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• 2014

We refer to the saturation assumptions on the finite element approximation for a one dimensional convection-diffusion model. By examining piecewise linear finite elements with refined mesh by half and hierarchical bases, we verify the saturation results, respectively.

• ETRI Journal
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• v.30 no.1
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• pp.170-172
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• 2008

A substitution box (S-box) plays a central role in cryptographic algorithms. In this paper, an efficient method for designing S-boxes based on chaotic maps is proposed. The proposed method is based on the mixing property of piecewise linear chaotic maps. The S-box so constructed has very low differential and linear approximation probabilities. The proposed S-box is more secure against differential and linear cryptanalysis compared to recently proposed chaotic S-boxes.