• Journal of Digital Convergence
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• v.14 no.1
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• pp.203-209
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• 2016

In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.4
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• pp.151-158
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• 2014

In this paper, we introduce an inference system using hard scatter partition method and model the nonlinear process. To do this, we use the hard scatter partition method that partition the input space in the scatter form with the value of the membership degree of 0 or 1. The proposed method is implemented by C-Means clustering algorithm. and is used for the initial center values by means of binary split. by applying the LBG algorithm to compensate for shortcomings in the sensitive initial center value. Hard-scatter-partitioned input space forms the rules in the rule-based system modeling. The premise parameters of the rules are determined by membership matrix by means of C-Means clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. The data widely used in nonlinear process is used to model the nonlinear process and evaluate the characteristics of nonlinear process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.793-799
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• 2007

Generally, a semiconductor chip measured with a few micro units is captured by line scan camera for higher inspection accuracy. However, the faulty inspection requires an exact boundary detection algorithm, because it is very sensitive to scan speed and lighting conditions. In this paper we propose boundary detection with subpixel edge detection in order to increase the accuracy of bump faulty detection on chips. The bump edge is detected by first derivative to four directions from bump center point and the exact edge positions are searched by the subpixel method. Also, the exact bump boundary to calculate the actual bump size is computed by LSM(Least Squares Method) to minimize errors since the bump size is varied such as bump protrusion, bump bridge, and bump discoloration. Experimental results exhibit that the proposed algorithm shows large improvement comparable to the other conventional boundary detection algorithms.

• Journal of IKEEE
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• v.27 no.4
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• pp.624-629
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• 2023

Estimation of signal parameters via rotational invariance techniques (ESPRIT) is an algorithm that estimates the angle of a signal arriving at an array antenna using the shift invariance property of an array antenna. ESPRIT offers the good trade-off between performance and complexity. However, the ESPRIT algorithm still requires high-complexity operations such as covariance matrix and eigenvalue decomposition, so implementation with a hardware processor is essential to estimate the angle of arrival in real time. In addition, ESPRIT processors should have high performance. The performance is related to the number of antennas, and the number of antennas required for each application are different. Therefore, we proposed an ESPRIT processor that provides 2 to 8 variable antenna configurations to meet the performance and complexity requirements according to the applied field. The proposed ESPRIT processor was designed using the Verilog-HDL and implemented on a field programmable gate array (FPGA).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.82-88
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• 2001

This paper considers the problem of the identification of the time invariant parameters of distributed systems. In general, the parameters are identified by using the CBPOM(Conventional Block Pulse Operational Matrices), but in this paper, the parameters ard identified by using the EBPOMS(Extended Block Pulse Operational Matrices) which can reduce the burden of operation md the volume of error caused by matrices multiplication. The simulation cloves the effectiveness of the proposed method.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.7-12
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• 2005

Scattered look-ahead(SLA) pipelining method can be efficiently used for high-speed or low-power applications of digital II R filters. Although the pipelined filters are guaranteed to be stable by this method, these filters suffer from large roundoff noise when the poles are crowded within some critical regions. An angle and radius constrained II R fille. design approach using modified Remez exchange algorithm and least squares algorithm is proposed to avoid tight pole-crowding in pipelined filters, resulting in improved frequency responses and reduced coefficient sensitivities. Experimental results demonstrate that our proposed method leads to chip area reduction by $33{\%}$ and low power by $45{\%}$ against the conventional method.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.586-592
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• 2012

One approach of the control of a nonlinear system that has gained some success employs a fuzzy structure in cooperation with a neural network(ANFIS). The traditional ANFIS can only model and control the process in single-dimensional output nature in spite of multi-dimensional input. The membership function parameters are tuned using a combination of least squares estimation and back-propagation algorithm. In the case of a mobile robot, we need to drive left and right wheel respectively. In this paper, we proposed the control system architecture for a mobile robotic system that employs the 2-input 2-output ANFIS controller for trajectory tracking. Simulation results and preliminary evaluation show that the proposed architecture is a feasible one for mobile robotic systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.1-7
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• 2017

The maximum zero error probability (MZEP) algorithm outperforms MSE (mean squared error)-based algorithms in impulsive noise environment. The magnitude controlled input (MCI) which is inherent in that algorithm is known to plays the role in keeping the algorithm undisturbed from impulsive noise. In this paper, a new approach to normalize the step size of the MZEP with average power of the MCI is proposed. In the simulation under impulsive noise with the impulse incident rate of 0.03, the performance enhancement in steady state MSE of the proposed algorithm, compared to the MZEP, is shown to be by about 2 dB.

• Journal of Drive and Control
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• v.15 no.3
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• pp.8-13
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• 2018

This paper presents a phase portrait analysis-based safety control algorithm for excavators, using adaptive sliding mode control. Since working postures and material types cause the excavator's rotational inertia to vary, the rotational inertia was estimated, and this estimation was used to design an adaptive sliding mode controller for collision avoidance of the excavator. In order to estimate the rotational inertia, the recursive least-squares estimation with multiple forgetting was applied with the information of the swing velocity of the excavator. For realistic evaluation, an actual working scenario-based performance evaluation was conducted. Based on the estimated rotational inertia and an analysis of estimation errors, sliding mode control inputs were computed. The actual working scenario-based performance evaluation of the designed safety algorithm was conducted, and the results showed that the developed safety control algorithm can efficiently avoid a collision with an object in consideration of rotational inertia variations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.8
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• pp.371-378
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• 2002

This paper presents the rapid and accurate algorithm for fault detection and location estimation in the transmission line. This algorithm uses wavelet transform for fault detection and harmonics elimination and utilizes least square error method for fault impedance estimation. Wavelet transform decomposes fault signals into high frequence component Dl and low frequence component A3. The former is used for fault phase detection and fault types classification and the latter is used for harmonics elimination. After fault detection, an adaptive data window technique using LSE estimates fault impedance. It can find a optimal data window length and estimate fault impedance rapidly, because it changes the length according to the fault disturbance. To prove the performance of the algorithm, the authors test relaying signals obtained from EMTP simulation. Test results show that the proposed algorithm estimates fault location within a half cycle after fault irrelevant to fault types and various fault conditions.