• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.176-179
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• 2010

In this paper, we propose a fast implementation of Bilateral filter for tone mapping algorithm. Bilateral filter is able to preserve detail while at the same time prevent halo-ing artifacts because of improper scale selection by ensuring image smoothed that not only depend on pixel closeness, but also similarity. We accelerate Bilateral filter by using a piecewise linear approximation and recursive Gaussian filter as its domain filter. Recursive Gaussian filter is scale independent filter that combines low cost 1D filter which makes this filter much faster than conventional convolution filter and filtering in frequency domain. The experiment results show that proposed method is simpler and faster than previous method without mortgaging the quality.

• ETRI Journal
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• v.42 no.4
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• pp.619-632
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• 2020

Highly dispersive S-boxes are desirable in cryptosystems as nonlinear confusion sublayers for resisting modern attacks. For a near optimal cryptosystem resistant to modern cryptanalysis, a highly nonlinear and low differential probability (DP) value is required. We propose a method based on a piecewise linear chaotic map (PWLCM) with optimization conditions. Thus, the linear propagation of information in a cryptosystem appearing as a high DP during differential cryptanalysis of an S-box is minimized. While mapping from the chaotic trajectory to integer domain, a randomness test is performed that justifies the nonlinear behavior of the highly dispersive and nonlinear chaotic S-box. The proposed scheme is vetted using well-established cryptographic performance criteria. The proposed S-box meets the cryptographic performance criteria and further minimizes the differential propagation justified by the low DP value. The suitability of the proposed S-box is also tested using an image encryption algorithm. Results show that the proposed S-box as a confusion component entails a high level of security and improves resistance against all known attacks.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.589-603
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• 2014

When consecutive data follows different distributions(depending on the time interval) change-point detection infers where the changes occur first and then finds further inferences for each sub-interval. In this paper, we investigate the Bayesian detection of multiple change points. Utilizing the reversible jump MCMC, we can explore parameter spaces with unknown dimensions. In particular, we consider a model where the signal is a piecewise linear function. For the Bayesian inference, we propose a new Bayesian structure and build our own MCMC algorithm. Through the simulation study and the real data analysis, we verified the performance of our method.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.2
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• pp.56-64
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• 1998

Multi-layered perceptrons that are a nonlinear neural network model, have been widely used for various applications mainly thanks to good function approximation capability for nonlinear fuctions. However, for digital hardware implementation of the multi-layere perceptrons, the quantization scheme using "look-up tables (LUTs)" is commonly employed to handle nonlinear signmoid activation functions in the neworks, and thus requires large amount of storage to prevent unacceptable quantization errors. This paper is concerned with a new effective methodology for digital hardware implementation of multi-layered perceptrons, and proposes a "piecewise affine approximation" method in which input domain is divided into (small number of) sub-intervals and nonlinear sigmoid function is linearly approximated within each sub-interval. Using the proposed method, we develop an expression and an error backpropagation type learning algorithm for a multi-layered perceptron, and compare the performance with the quantization method through Monte Carlo simulations on XOR problems. Simulation results show that, in terms of learning convergece, the proposed method with a small number of sub-intervals significantly outperforms the quantization method with a very large storage requirement. We expect from these results that the proposed method can be utilized in digital system implementation to significantly reduce the storage requirement, quantization error, and learning time of the quantization method.quantization method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1388-1393
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• 1999

A more reliable algorithm for detecting a high impedance fault (HIF) requires fault currents at the relaying point containing information of load condition as well as HIF characteristics. This paper presents a modeling method of an HIF in a distribution system using EMTP. From the voltage and current waveforms of HIF experiment, the voltage-current characteristic is obtained and then piecewise linearized. The proposed method gets several points on the linearized voltage-current curve and then represents nonlinearity as piecewise linear resistances using Transient Analysis of Control Systems (TACS) in EMTP. Thus, an HIF is represented as a voltage source in the first and third quadrants of voltage-current plane. The method is implemented in EMTP and thus the voltage and current at the relaying point can be obtained when an HIF occurs. In this paper, an HIF was simulated on various load conditions and fault conditions in 22.9 [kV] distribution systems.

• KIEE International Transactions on Power Engineering
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• v.4A no.4
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• pp.254-261
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• 2004

Traditionally, electrical power systems had formed the vertically integrated industry structures based on the economics of scale. However, power systems have been recently reformed to increase their energy efficiency. According to these trends, the Korean power industry underwent partial reorganization and competition in the generation market was initiated in 2001. In competitive electric markets, accurate load data is one of the most important issues to maintaining flexibility in the electric markets as well as reliability in the power systems. In practice, the measuring load data can be uncertain because of mechanical trouble, communication jamming, and other issues. To obtain reliable load data, an efficient evaluation technique to adjust the missing load data is required. This paper analyzes the load pattern of historical real data and then the tuned ARIMA (Autoregressive Integrated Moving Average), PCHIP (Piecewise Cubic Interpolation) and Branch & Bound method are applied to seek the missing parameters. The proposed method is tested under a variety of conditions and also tested against historical measured data from the Korea Energy Management Corporation (KEMCO).

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.204-210
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• 2005

This paper presents online identification algorithm for TSK fuzzy model. The proposed algorithm identify structure of premise part by using distance, and obtain the parameters of the piecewise linear function consisting consequent part by using recursive least square. Only input space was considered in Most researches on structure identification, but input and output space is considered in the proposed algorithm. By doing so, outliers are excluded in clustering effectively. The existing other algorithm has disadvantage that it is sensitive to noise by using data itself as cluster centers. The proposed algorithm is non-sensitive to noise not by using data itself as cluster centers. Model can be obtained through one pass and it is not needed to memorize many data in the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.322-328
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• 2009

This paper proposes new simplified sum-product (SSP) decoding algorithm to improve BER performance for low-density parity-check codes. The proposed SSP algorithm can replace multiplications and divisions with additions and subtractions without extra computations. In addition, the proposed SSP algorithm can simplify both the In[tanh(x)] and tanh-1 [exp(x)] by using two quantization tables which can reduce tremendous computational complexity. Moreover, the simulation results show that the proposed SSP algorithm can improve about $0.3\;{\sim}\;0.8\;dB$ of BER performance compared with the existing modified sum-product algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.56-64
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• 2013

We propose an efficient minimum-time cornering motion planning algorithms for differential-driven wheeled mobile robots with motor control input constraint, under piecewise constant control input sections. First, we established mobile robot's kinematics and dynamics including motors, divided the cornering trajectory for collision-free into one translational section, followed by one rotational section with angular acceleration, and finally the other rotational section with angular deceleration. We constructed an efficient motion planning algorithm satisfying the bang-bang principle. Various simulations and experiments reveal the performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2430-2434
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• 2003

This paper provides a new approach to analyze the stability of TCP Vegas, which is a kind of feedback-based congestion control algorithm. Whereas the conventional approaches use the approximately linearized model of the TCP Vegas along equilibrium points, this approach uses the exactly characterized dynamic model to get a new stability criterion via a piecewise and delay-dependent Lyapunov-Krasovskii function. Especially, the resulting stability criterion is formulated in terms of linear matrix inequalities (LMIs). Using the new criterion, this paper shows that the current TCP Vegas algorithm is stable in the sufficiently wide region of network delay and link capacity.