• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.114-116
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• 2016

본 논문은 human visual system(HVS)에 따른 주파수 민감도와 공간에서 다양한 특성들을 구현하기 위한 신호처리 방법을 개발하였다. 인간의 눈은 주파수 성분에 따라 민감도가 다르며 초점에서 멀수록 인지 가능한 해상도가 떨어진다. 주파수 민감도를 구현하기 위해서 본 논문은 영상 신호의 에너지 스펙트럼 모양이 contrast sensitivity function(CSF)의 모양이 되도록하여 영상 신호의 에너지를 증가시켰으며 신호 방향에 적응적인 multiband energy scaling 방법을 개발하였다. 기존의 시스템에서 능률만을 향상시키는 기존의 분석 모델과 비교하면 개발한 방법은 HVS에 좀 더 적절하고 선호되게 영상 신호를 처리 할 수 있다.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1034-1036
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• 1996

In this paper, an adaptive fuzzy logic controller is presented for auto-tunning of the scaling factors by using learning capability of neural networks. The proposed scheme consists of the FLC which includes the PI-type FLC and PD-type FLC in parallel form and the neural network which learns scale factors of FLC. Computer simulations were performed to illustrate the effectiveness of a proposed scheme. A proposed FLC controller was applied to the second order system and velocity control of the brushless DC motors. For the design of the FLC, tracking error, change of error, and acceleration error are selected as input variables of the FLC and three seal e factors were used in the parallel-type FLC. This scheme can be used to reduce the difficulty in the selection of the scale factors.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.221-223
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• 1993

The Hopfield model is defined as an adaptive dynamic system. In this paper we propose a modified neural network which is capable of solving linear programming problems and a set of linear equations. The model is directly implemented from the given system, and solves the problem without calculating the inverse of the matrices. We get the better stability results by the addition of scaling property and by using the nonlinearities in the linear programming neural networks.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.435-436
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• 2012

본 논문은 가변 조정계수를 이용한 적응형 MPPT 제어 기법을 제안한다. MPPT 제어 루프가 소신호 모델링을 통해 구성되며, PV array 의 동작점에 상관없이 MPPT 제어의 성능을 일정하게 유지하기 위한 가변 조정계수가 결정된다. 가변 조정계수는 오차에 대한 근사화된 곡선맞춤 다항식을 통해 결정되며, 이를 통해 사용자가 원하는 MPPT 의 동특성과 안정성을 전 MPPT 영역에 걸쳐 확보할 수 있다. 제안된 MPPT 기법의 타당성은 3KW 급 시스템에 대한 실험을 통해 검증한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.619-622
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• 2007

PDA provides an opportunity for users to study anytime and anywhere because it is portable and convenient thanks to its relatively small size. However, users may face difficulties to fully recognize the characters provided through lecture videos, due to its low resolution and small scaled screen. This thesis proposes a system of remote lecture in which the size of videos can be adjusted and transmitted on the basis of contents necessary for study, using detection of region-of-interest(ROI) image, and a method of image scaling in a bid to solve such a problem of PDAs. The experiment on 802.11b wireless network shows that the proposed system is able to provide more optimized lecture videos than in existing method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.4
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• pp.37-44
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• 2009

A novel phase-locked loop(PLL) architecture with resistance and capacitance scaling scheme has been proposed. The proposed PLL has three charge pumps. The effective capacitance and resistance of the loop filter can be scaled up/down according to the locking status by controlling the direction and magnitude of each charge pump current. This architecture makes it possible to have a narrow bandwidth and low resistance in the loop filter, which improves phase noise and reference spur characteristics. It has been fabricated with a 3.3V $0.35{\mu}m$ CMOS process. The measured locking time is $25{\mu}s$ with the measured phase noise of -105.37 dBc/Hz @1MHz and the reference spur of -50dBc at 851.2MHz output frequency

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.133-141
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• 2014

An efficient method for reducing power consumption in pipelined deep packet inspection systems is proposed. It is based on the observation that the number of memory accesses is dominant for the power consumption and the number of accesses drops drastically as the input goes through stages of the pipelined AC-DFA. A DPI system is implemented where the operating frequency of the stages that are not frequently used in the pipeline is reduced to eliminate the waste of power consumption. The power consumption of the proposed DPI system is measured upon various input character set and up to 25% of reduction of total power consumption is obtained, compared to those of the recent DPI systems. The method can be easily applied to other pipelined architecture and string searching applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1405-1411
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• 2022

Power management is still an important issue in embedded environments as hardware advances like high-performance processors. Power management methods such as DVFS control CPU frequencies in an adaptive manner for efficient power management in polling-based I/O programs such as network communication. This paper presents the problems of the existing power management method and proposes a new power management method. Through this, it is possible to reduce electric consumption by increasing the polling cycle in situations where the frequency of data reception is low, and on the contrary, in situations where data reception is frequent, it can operate at the maximum frequency without performance degradation. After implementing this as a code layer on the embedded board and observing it through Atmel's Power Debugger, the proposed method showed a performance improvement of up to 30% in energy consumption compared to the existing power management method.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.73-81
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• 2016

In general, infrared images have less sharpness and image details than visible images. So, the prior image upscaling methods are not effective in the infrared images. In order to solve this problem, this paper proposes an algorithm which initially up-scales an input infrared (IR) image by using adaptive dynamic range encoding (ADRC)-based super-resolution (SR) method, and then fuses the result with the corresponding visible images. The proposed algorithm consists of a up-scaling phase and a fusion phase. First, an input IR image is up-scaled by the proposed ADRC-based SR algorithm. In the dictionary learning stage of this up-scaling phase, so-called 'pre-emphasis' processing is applied to training-purpose high-resolution images, hence better sharpness is achieved. In the following fusion phase, high-frequency information is extracted from the visible image corresponding to the IR image, and it is adaptively weighted according to the complexity of the IR image. Finally, a up-scaled IR image is obtained by adding the processed high-frequency information to the up-scaled IR image. The experimental results show than the proposed algorithm provides better results than the state-of-the-art SR, i.e., anchored neighborhood regression (A+) algorithm. For example, in terms of just noticeable blur (JNB), the proposed algorithm shows higher value by 0.2184 than the A+. Also, the proposed algorithm outperforms the previous works even in terms of subjective visual quality.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.5
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• pp.1-12
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• 2000

In this paper we propose a design method of the adaptive fuzzy controller for autonomous navigation of mobile robots based on the fuzzy theory. We present two improvements. First, unnecessary rules in the fuzzy inference process make data processing time increase. We reduce this data processing time by generating suitable fuzzy inference rules and membership functions according to the current state of a mobile robot. It is implemented with the clustering method using input and output data pairs, and then it is possible for a mobile robot to navigate in shorter processing time with less fuzzy inference rules. Second, existing algorithms used fixed membership functions of input and output variables, hence converged slowly. We improve convergence time via scaling membership functions generated by the clustering method. To evaluate and compare the performance of the proposed method with the existing fuzzy navigation controller, computer simulations and navigation experiments of a mobile robot are Presented.