• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 하계종합학술대회 논문집(1)
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• pp.265-268
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• 2004

In this paper. we propose an adaptive step-size algorithm for the adaptive interference canceller (AIC) in the space-time trellis coded DS-CDMA system. In the AIC, the performance of the blind LMS algorithms that updates the tap-weight vector of the AIC is heavily dependent on the choice of step-size. To improve the performance of the fixed step-size AIC (FS-AIC), the regular adaptive step-size algorithm is extended in complex domain and applied to the joint AIC and ML decoder scheme. Simulation results show that the joint adaptive step-size AIC (AS-AIC) and ML decoder scheme using the proposed algorithm has boner performance than not only the conventional ML decoder but also the joint FS-AIC and ML decoder scheme without much increase of the decoding delay and complexity.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.442-442
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• 2000

The intelligent auto-tuning method fur a strongly stable adaptive control system of a DC motor with great load inertia variation is proposed. The stable characteristic polynomial that is designed by an optimal servo is specified for the adaptive pole placement control system. The appropriate adaptive control system can be derived, by adjusting automatically the weight of a performance criterion in optimal control by means of the fuzzy inference on the basis of the stability index.

• 융합신호처리학회논문지
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• 제11권3호
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• pp.238-243
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• 2010

A new implementation method for MPDSAP(Maximally Polyphase Decomposed Subband Affine Projection) adaptive filter is proposed. The affine projection(AP) adaptive filter achieves fast convergence speed, however, its implementation is so expensive because of the matrix inversion for a weight-updating of adaptive filter. The maximally polyphase decomposed subband filtering allows the AP adaptive filter to avoid the matrix inversion, moreover, by using a pipelining technique, the simple subband structured AP is suitable for VLSI implementations concerning throughput, power dissipation and area. Computer simulations are presented to verify the performance of the proposed algorithm.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2002년도 추계종합학술대회
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• pp.311-316
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• 2002

In this paper, an adaptive beamforming algorithm, based on the Minimum Mean Squared Error (MMSE) criterion, is devised fer adaptive antenna applied to an MC-CDMA system. A new method for updating the weight vector is derived. Computer simulations show that proposed algorithm is capable of rejecting co-channel interference that affects the MC-CDMA system. Thus, the BER performance of the MC-CDMA system is improved compared with that of the MC-CDMA system without using adaptive antenna and that of the DS-CDMA system with adaptive antenna in multi-path Ricean fading channel.

• 한국멀티미디어학회논문지
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• 제8권7호
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• pp.961-973
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• 2005

본 논문은 비트플레인 및 다중채널 특성을 이용한 컬러 영상의 적응 스테가노그라피 방법을 제안하였다. RGB 채널의 모든 비트플레인에 고정 임계값을 적용하여 정보를 삽입한 결과, 채널에 따른 화질 열화의 차이를 알 수 있었다. 따라서 본 연구에서는 BPCS (bit-plane complexity steganography) 방법의 고정 임계값 문제점을 해결하고 삽입용량과 화질을 개선하기 위하여 각 채널과 비트플레인 가중치를 정의하였다. 또한 비트플레인의 삽입 용량을 적응적으로 증가시키기 위하여, 커버 영상의 비트플레인 복잡도와 채널별 가중치를 이용하여 새로운 적응 임계값 설정 방법을 제안하였다. 실험에서는 컬러 영상에 동일한 화질과 동일한 정보량을 삽입하고, 이에 따른 삽입 용량과 채널별 화질을 비교하였다. 그 결과, 제안한 방법이 기존의 BPCS 방법보다 삽입 용량의 증가와 채널별 화질도 향상되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.1959-1975
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• 2011

Adaptive Bit Loading (ABL) in Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) is often used to achieve the desired Bit Error Rate (BER) performance in wireless systems. In this paper, we discuss some of the bit loading algorithms, compare them in terms of the BER performance, and present an effective and concise Adaptive Grouped Loading (AGL) algorithm. Furthermore, we propose a "weight factor" for loading algorithm to converge rapidly to the final solution for various data rate with variable Signal to Noise Ratio (SNR) gaps. In particular, we consider the bit loading in near optimal Singular Value Decomposition (SVD) based MIMO-OFDM system. While using SVD based system, the system requires perfect Channel State Information (CSI) of channel transfer function at the transmitter. This scenario of SVD based system is taken as an ideal case for the comparison of loading algorithms and to show the actual enhancement achievable by our AGL algorithm. Irrespective of the CSI requirement imposed by the mode of the system itself, ABL demands high level of feedback. Grouped Loading (GL) would reduce the feedback requirement depending upon the group size. However, this also leads to considerable degradation in BER performance. In our AGL algorithm, groups are formed with a number of consecutive sub-channels belonging to the same transmit antenna, with individual gains satisfying predefined criteria. Simulation results show that the proposed "weight factor" leads a loading algorithm to rapid convergence for various data rates with variable SNR gap values and AGL requires much lesser CSI compared to GL for the same BER performance.

• 한국멀티미디어학회논문지
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• 제13권2호
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• pp.216-224
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• 2010

RAM 기반 신경망은 빠른 처리 속도와 하드웨어 구현의 용이성 등의 장점을 가지고 있지만 반면에 메모리의 포화 문제, 반복학습, 일반화 패턴 추출의 어려움 등의 단점도 가지고 있다. 이런 단점을 극복하기 위해 누적 다중 판별자를 가지는 3차원 뉴로 시스템(3DNS) 등이 제안되었지만 메모리 포화 문제는 해결하지는 못하였다. 본 논문에서는 메모리 포화 문제를 해결하기 위하여 적응적 가중치를 가지는 AWN (Adaptive Weight Neuron)을 사용한 적응적 가중치 누적 신경망(AWCNN)을 제안한다. 제안된 모델은 AWN으로 3DNS을 개선하여 인식률과 메모리 포화 문제 해결을 향상하였다. 제안된 시스템의 평가는 전처리 과정 없이 NIST의 MNIST에서 제공하는 자료를 이용하여 실험하였다. AWCNN은 3DNS보다 1.5%이상의 향상된 인식률을 보였고 일반화 패턴을 이용한 인식에서는 모든 입력 패턴의 교육된 것과 비슷한 성능을 얻었다.

• 전기전자학회논문지
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• 제24권2호
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• pp.570-578
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• 2020

본 논문에서는 적응 2차 볼테라 필터를 효율적으로 구현할 수 있는 새로운 방법을 제안한다. 연산량 감소를 위해 제안된 UCFD-SVF는 수렴 성능이 저하되는 단점이 있다. UCFD-SVF의 적응 필터 계수가 적응이 진행되면서 그 에너지가 급격하게 증가하지 않는다는 점을 이용하여 적응 필터 계수를 주기적으로 초기화는 방법을 제안하였다. 또한 일정한 수렴 성능을 보장하기 위해 가변적인 간격으로 적응 필터 계수를 초기화하는 방법을 제안하였고, 비정상 환경에서 우수한 수렴 특성을 가짐을 적응 시스템 확인 응용을 위한 컴퓨터 모의 실험을 통해 보였다.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2006년도 춘계학술대회 논문집
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2976-2990
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• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.