• Title/Summary/Keyword: Adaptive Gain Control

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Seaway Signal Processing using Modified RMXMS algorithm (개선한 RMXMS 알고리즘을 이용한 해파 신호 처리)

  • Lee, Seok-Pil;Kim, Youn-Ho;Youn, Hyoung-Sig;Park, Sang-Hui
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.441-444
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    • 1992
  • In this paper, for tracking and filtering seaway information which act as a control disturbance the adaptive notch filter which removes disturbance with fast convergence and stability without changing the value of gain parameter $\mu$ when statistical property of input signal varies rapidly is designed by improving conventional RMXMS(Recursive Maximum Mean Square) algorithm. Besides, in consideration of measurement noise of sensors in underwater vehicle, the system which removes the noise and the disturbance is suggested.

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A hierarchical approach to state estimation of time-varying linear systems via block pulse function (블럭펄스함수를 이용한 시스템 상태추정의 계층별접근에 관한 연구)

  • 안두수;안비오;임윤식;이재춘
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.3
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    • pp.399-406
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    • 1996
  • This paper presents a method of hierarchical state estimation of the time-varying linear systems via Block-pulse function(BPF). When we estimate the state of the systems where noise is considered, it is very difficult to obtain the solutions because minimum error variance matrix having a form of matrix nonlinear differential equations is included in the filter gain calculation. Therefore, hierarchical approach is adapted to transpose matrix nonlinear differential equations to a sum of low order state space equation from and Block-pulse functions are used for solving each low order state space equation in the form of simple and recursive algebraic equation. We believe that presented methods are very attractive nd proper for state estimation of time-varying linear systems on account of its simplicity and computational convenience. (author). 13 refs., 10 figs.

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MEMBERSHIP FUNCTION TUNING OF FUZZY NEURAL NETWORKS BY IMMUNE ALGORITHM

  • Kim, Dong-Hwa
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.3
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    • pp.261-268
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    • 2002
  • This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

Adaptive Current Gain Switching Method for Improvement of Spin Control Accuracy in HDD (적응 전류 이득 변환 방법을 이용한 스핀들 모터의 제어 성능 향상 방법)

  • Kim, Jin-Seak;Oh, Kyoung-Whan;Lee, Byoung-Kuk
    • Proceedings of the KIPE Conference
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    • 2010.11a
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    • pp.327-328
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    • 2010
  • 1980년초 미국 실리콘 밸리 소재 시게이트사에 의해 5메가 바이트 용량의 개인 컴퓨터용 하드 디스크 드라이브(HDD)가 처음 소개된 이후, HDD 개발 기술은 꾸준한 성장을 거듭하였다. 최근 인터넷의 보급으로 엄청나게 많은 정보저장용량을 요구하게 되었으며, 정보저장기기에 대한 폭발적인 수요에 부합하고 있는 기기중의 하나가 HDD이다. 드라이브에서 스핀들 모터의 제어는 주된 읽기 쓰기 동작을 위한 가장 기본적인 제반 여건이며, 단위 면적당 데이터(BPI)가 증가함에 따라서 스핀들 모터의 제어 성능은 드라이브 성능과 직결되는 더욱 중요한 인자중의 하나가 되었다. 본 논문에서는 스핀들 모터의 제어 성능 향상을 위해 스핀들 모터의 출력 이득을 조정하여 제어 분해능을 향상시키는 방법을 제시하고 있다.

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A Temporal Error Concealment Technique Using The Adaptive Boundary Matching Algorithm (적응적 경계 정합을 이용한 시간적 에러 은닉 기법)

  • 김원기;이두수;정제창
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5C
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    • pp.683-691
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    • 2004
  • To transmit MPEG-2 video on an errorneous channel, a number of error control techniques are needed. Especially, error concealment techniques which can be implemented on receivers independent of transmitters are essential to obtain good video quality. In this paper, prediction of motion vector and an adaptive boundary matching algorithm are presented for temporal error concealment. Before the complex BMA, we perform error concealment by a motion vector prediction using neighboring motion vectors. If the candidate of error concealment is not satisfied, search range and reliable boundary pixels are selected by the temporal activity or motion vectors and a damaged macroblock is concealed by applying an adaptive BMA. This error concealment technique reduces the complexity and maintains a PSNR gain of 0.3∼0.7㏈ compared to conventional BMA.

A study on Scalable Video Coding Signals Transmission using inter-layer Differential OVSF code allocation scheme in MC-CDMA (MC-CDMA 기반의 SVC 전송 시스템에서 계층 간 차등 OVSF코드 할당 기법에 관한 연구)

  • Shin, Hyung-Song;Kim, Kyun-Tak;Lee, Kyu-Jin;Lee, Kye-San
    • Journal of Convergence Society for SMB
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    • v.6 no.3
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    • pp.49-55
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    • 2016
  • This paper proposes an adaptive video signal transmission scheme in order to ensure the QoS (Quality of Service) of user requirements. SVC (Scalable Video Coding) is an effective transmission scheme, because that can transmit video signal according to the video layer's weight. However, in previous works, those adaptive transmission systems which are considered about the various channel environments and user requirements have not been insufficiently studied. So, we propose the SVC signal transmission using inter-layer differential OVSF code allocation scheme in MC-CDMA. The proposed scheme is able to obtain each layer signal's protection order and control the sub-block of MC-CDMA by feedback information from receiver. Therefore, our proposed scheme is possible to provide the video quality for each users according to variable channel environments. The simulation results demonstrate the enhancement of proposed system in terms of BER performance.

Adaptive Detector Design for the Performance Improvement of Massive Antenna Systems (대용량 안테나 시스템의 성능 향상을 위한 적응형 검파기 설계)

  • Seo, Bangwon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.1
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    • pp.43-48
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    • 2021
  • One of the effective ways to increase data transmission rate is to use massive antenna technique where tens or hundreds of antennas are deployed in base station and spatial diversity gain is improved by multiuser method. If multiuser method is applied, there will be inter-user interference and maximal ratio combiner (MRC) is conventionally used to reduce the complexity of the receiver and to eliminate interference. However, as the number of mobile devices increases, the performance of the conventional receiver becomes deteriorated. To solve this problem, we propose a new detector that completely eliminates the interference from the registered devices and reduces that from the unregistered devices. Then, to reduce the complexity of the proposed scheme, we propose adaptive algorithm of the proposed scheme. Through simulation, we show that the proposed scheme has better bit error rate performance than the conventional scheme.

STPI Controller of IPMSM Drive using Neural Network (신경회로망을 이용한 IPMSM 드라이브의 STPI 제어기)

  • Ko, Jae-Sub;Choi, Jung-Sik;Chung, Dong-Hwa
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.44 no.2 s.314
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    • pp.24-31
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    • 2007
  • This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

Adaptive Denoising for Low Light Level Environment Using Frequency Domain Analysis (주파수 해석에 따른 저조도 환경의 적응적 잡음제거)

  • Yi, Jeong-Youn;Lee, Seong-Won
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.128-137
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    • 2012
  • When a CCD camera acquires images in the low light level environment, not only the image signals but also noise components are amplified by the AGC (auto gain control) circuit. Since the noise level in the images acquired in the dark is very high, it is difficult to remove noise with existing denoising algorithms that are targeting the images taken in the normal light condition. In this paper, we proposed an adaptive denoising algorithm that can efficiently remove significant noises caused by the low light level. First, the window including a target pixel is transformed to the frequency domain. Then the algorithm compares the characteristics of equally divided four frequency bands. Finally the noises are adaptively removed according to the frequency characteristics. The proposed algorithm successfully improves the quality of low light level images than the existing algorithms do.

Path Metric Comparison-based Adaptive QRD-M Algorithm for MUHO Systems (Path Metric 비교 기반 적응형 QRD-M MIMO 검출 기법)

  • Kim, Bong-Seok;Kim, Han-Nah;Choi, Kwon-Hue
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.6C
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    • pp.487-497
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    • 2008
  • This paper proposes a new adaptive QRD-M algorithm for MIMO systems. The proposed scheme controls the number of survivor paths,0 based on the channel condition at each layer. The original QRD-M algorithm used fixed M at each layer and it needs large M to achieve near-MLD (maximum-likelihood detection) performance. However, using the large M increases the computation complexity. In this paper, we further effectively control M by employing the channel indicator which includes not only the channel gain, but also instantaneous noise information without necessity of SNR measurement. We found that the ratio of the minimum path metric to the second minimum is good reliability indicator for the channel condition. By adaptively changing M based on this ratio, the proposed scheme effectively achieves near MLD performance and computation complexity of the proposed scheme is significantly smaller than the conventional QRD-M algorithms.