• Title/Summary/Keyword: rate adaptation algorithm

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Early Rate Adaptation Protocol in DiffServ for Multimedia Applications (멀티미디어 서비스를 위한 DiffServ 망에서의 빠른 혼잡 제어 알고리즘)

  • Park Jonghun;Yoo Myungsik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.1B
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    • pp.39-46
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    • 2005
  • As the multimedia application traffic takes more portion in the internet traffic, it is necessary to control the network congestion through the congestion control protocol. In addition, the QoS-enabled networks such as DiffServ become an indispensable technology when running the multimedia applications. However, the previously proposed end-to-end congestion control algorithms take the round trip time to react the network congestion. Thus, as the RTT becomes larger, the reaction against the congestion gets delayed further, while the network congestion gets worse. In addition the performance of end-to-end congestion control algorithm is degraded if the QoS-enabled network runs the congestion control mechanism in the network level without any coordination between them. In this paper, we propose the early rate adaptation protocol for the DiffServ network which effectively linke the congestion control algorithm at the host and the congestion mechanism in the network together. By taking advantage of early congestion notification from the network it is possible to react the network congestion more quickly and effectively.

Performance Improvement Using Fuzzy Logic In Adapative Control (퍼지논리를 이용한 적응제어기의 성능개선에 관한 연구)

  • Ryu, Keun-Bae;Yi, Keon-Young;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 1991.07a
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    • pp.708-712
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    • 1991
  • This paper presents a new adaptive structure with fuzzy logic applied to adaptive controller. In the conventional adaptive control, good performance cannot be expected due to the adaptation gain of gradient algorithm fined as a constant. To change adaptation gain property, fuzzy rules, which are based on the output error and its rate of change, have been established. The proposed fuzzy adaptive law shows fast parameter convergence and improved performance. The fuzzy logic base is added to the conventional adaptive structure and little additional computation time is required.

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Adaptation for Object-based MPEG-4 Content with Multiple Streams (다중 스트림을 이용한 객체기반 MPEG-4 컨텐트의 적응 기법)

  • Cha Kyung-Ae
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.3
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    • pp.69-81
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    • 2006
  • In this paper, an adaptive algorithm is proposed in streaming MPEG-4 contents with fluctuating resource amount such as throughput of network conditions. In the area of adaptive streaming issue, a lot of researches have been made on how to represent encoded media(such as video) bitstream in scalable way. By contrast, MPEG-4 supports object-based multimedia content which is composed of various types of media streams such as audio, video, image and other graphical elements. Thus, it can be more effective to provide individual media streams in scalable way for streaming object-based content to heterogeneous environment. The proposed method provides the multiple media streams corresponding to an object with different qualities and bit rate in order to support object based scalability to the MPEG-4 content. In addition, an optimal selection of the multiple streams for each object to meet a given constraint is proposed. The selection process is adopted a multiple choice knapsack problem with multi-step selection for the MPEG-4 objects with different scalability levels. The proposed algorithm enforces the optimal selection process to maintain the perceptual qualities of more important objects at the best effort. The experimental results show that the set of selected media stream for presenting objects meets a current transmission condition with more high perceptual quality.

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Adaptive Milling Process Modeling and Nerual Networks Applied to Tool Wear Monitoring (밀링공정의 적응모델링과 공구마모 검출을 위한 신경회로망의 적용)

  • Ko, Tae-Jo;Cho, Dong-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.1
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    • pp.138-149
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    • 1994
  • This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

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New Variable Step-size LMS Algorithm with Low-Pass Filtering of Instantaneous Gradient Estimate (순시 기울기 벡터의 저주파 필터링을 사용한 새로운 가변 적응 인자 LMS 알고리즘)

  • 박장식;문건락;손경식
    • Journal of Korea Multimedia Society
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    • v.4 no.3
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    • pp.230-237
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    • 2001
  • Adaptive filters are widely used for acoustic echo canceler, adaptive equalizer and adaptive noise canceler. Coefficients of adaptive filters are updated by NLMS algorithm. However, Coefficients are misaligned by ambient noises when they are adapted by NLMS algorithm. In this Paper, a method determined the adaptation constant by low-pass filtered instantaneous gradient vector of LMS algorithm using orthognality principles of optimal filter is proposed. At initial states, instantaneous gradient vector, that is the cross-correlation of input signals and estimation error signals, has large value because input signals are remained in estimation error signals. When an adaptive filter is conversed, the cross-correlation will be close to zero. It isn's affected by ambient noises because ambient noises are uncorrelated with input signals. Determining adaptation constant with the cross-correlation, adaptive filters can be robust to ambient noises and the convergence rate doesn't slower As results of computer simulations, it is shown that the performance of proposed algorithm is betted than that of conventional algorithms.

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Design and Implementation of Bandwidth Management Algorithm for Video Conference System (화상회의 시스템을 위한 대역폭 관리 알고리즘 설계 및 구현)

  • 구명모;정상운;김상복
    • Journal of Korea Multimedia Society
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    • v.3 no.4
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    • pp.399-406
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    • 2000
  • There are sendee_based research and receiver_based research for dynamic adaptation to network congestion which arises from multicast video conference ; the former results in bandwidth waste of receivers who use high available bandwidth on account of average loss rate in transmission rate, the latter in short of the method that divides layers of available bandwidth of receivers dynamically. In order to do so, in this paper, we established two multicast groups divided into non-congestion status and congestion status according to receiver's network state, and implemented the bandwidth management algorithm which is designed for providing receivers with profitable qualities for available bandwidth by letting them choose each group dynamically in reference to loss rate. As a result, experiments proved that bandwidth waste problem was improved by receiver's dynamic choice according to loss rate.

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Feature Variance and Adaptive classifier for Efficient Face Recognition (효과적인 얼굴 인식을 위한 특징 분포 및 적응적 인식기)

  • Dawadi, Pankaj Raj;Nam, Mi Young;Rhee, Phill Kyu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2007.11a
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    • pp.34-37
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    • 2007
  • Face recognition is still a challenging problem in pattern recognition field which is affected by different factors such as facial expression, illumination, pose etc. The facial feature such as eyes, nose, and mouth constitute a complete face. Mouth feature of face is under the undesirable effect of facial expression as many factors contribute the low performance. We proposed a new approach for face recognition under facial expression applying two cascaded classifiers to improve recognition rate. All facial expression images are treated by general purpose classifier at first stage. All rejected images (applying threshold) are used for adaptation using GA for improvement in recognition rate. We apply Gabor Wavelet as a general classifier and Gabor wavelet with Genetic Algorithm for adaptation under expression variance to solve this issue. We have designed, implemented and demonstrated our proposed approach addressing this issue. FERET face image dataset have been chosen for training and testing and we have achieved a very good success.

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A Modification of The Fuzzy Logic Based DASH Adaptation Algorithm for Performance Improvement (성능 향상을 위한 퍼지 논리 기반 DASH 알고리즘의 수정)

  • Kim, Hyun-Jun;Son, Ye-Seul;Kim, Joon-Tae
    • Journal of Broadcast Engineering
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    • v.22 no.5
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    • pp.618-631
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    • 2017
  • In this paper, we propose a modification of fuzzy logic based DASH adaptation algorithm(FDASH) for seamless media service in time-varying network conditions. The proposed algorithm selects more appropriate bit-rate for the next segment by the modification of the Fuzzy Logic Controller(FLC) and reduces the number of video bit-rate changes by applying Segment Bit-rate Filtering Module(SBFM). Also, we apply the Start Mechanism for clients not to watch the low quality videos in the very beginning stage of streaming service and add the Sleeping Mechanism to avoid any buffer overflow expected. Ultimately, we verified by using NS-3 Network Simulator that the proposed method shows better performance compared to FDASH. According to the experimental results, there is no buffer underflow/overflow within the limited buffer size, which is not guaranteed in FDASH on the other hand. Also, we confirmed that mFDASH has almost the same level of average video quality against FDASH and reduces about 50% of number of video bit-rate changes compared to FDASH in Point-to-Point network and Wi-Fi network.

Combination of Two Affine Projection Algorithm Filters with Different Update Interval based on Independent Adaptation (독립적 적응을 기반으로 한 업데이트 간격이 다른 Affine Projection 알고리즘 필터의 조합)

  • Kim, Kwang-Hoon;Choi, Young-Seok;Song, Woo-Jin
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.895-896
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    • 2008
  • We propose a adaptive combination of affine projection algorithm (APA) filters with different update interval. Two APA filters with different update interval are adapted independently in order to keep the advantages of both component filters. This novel scheme provides improvement of performance in term of the convergence rate and the steady-state error. Experimental results show good properties of the proposed algorithm.

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A Design of Adaptive Steering Controller of AGV using Immune Algorithm

  • Lee, Chang-Hoon;Lee, Jin-Woo;Lee, Kwon-Soon;Lee, Young-Jin
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.120.3-120
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    • 2002
  • 1. Introduction $\textbullet$ Immune system is an evolutionary biological system to protect innumerable foreign materials such as virus, germ cell, and etc. Immune algorithm is the modeling of this system's response that has adaptation and reliableness when disturbance occur. $\textbullet$ In this paper, Immune algorithm is applied to the Steering Controller of AGV in container yard. $\textbullet$ And then the computer simulation result from the viewpoint of yaw rate and lateral displacement is analyzed and compared with result of conventional PID controller. 2. Dynamic Modeling of AGV $\textbullet$ Dynamic modeling has high degree of freedom. But, basic assumptions of this model are that the center of gravity(CG)...

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