• Title/Summary/Keyword: Gauss-Markov Algorithm

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A Novel Shadow Clustering Mechanism based on Gauss-Markov Mobility Model in Nested Heterogeneous Networks (중첩 이종 네트워크 환경에서의 가우스-마코프 이동 모델 기반의 효율적인 새도우 클러스터 메카니즘)

  • Park, Je-Man;Kim, Won-Tae;Park, Yong-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.2B
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    • pp.143-150
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    • 2009
  • In this paper, we propose a novel shadow clustering mechanism including a mobility estimation algorithm based on Gauss-Markov mobility model which analyses patterns of moving direction and speed of a mobile terminal respectively and a selection algorithm of the most suitable network for the requirements of mobile terminals. The proposed mechanism makes much less shadow cluster area than that of the legacy methods, and reduces unnecessary resource reservation. It is compared the proposed algorithm with traditional methods under various scenarios.

Tolerance Optimization with Markov Chain Process (마르코프 과정을 이용한 공차 최적화)

  • Lee, Jin-Koo
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.2
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    • pp.81-87
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    • 2004
  • This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

Precise Positioning from GPS Carrier Phase Measurement Applying Stochastic Models for Ionospheric Delay (전리층 지연 효과의 통계적 모델을 이용한 반송파 정밀측위)

  • Yang, Hyo-Jin;Kwon, Jay-Hyoun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.4
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    • pp.319-325
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    • 2007
  • In case of more than 50km baseline length, the correlation between receivers is reduced. Therefore, there are still some rooms for improvement of its positional accuracy. In this paper, the stochastic modeling of the ionospheric delay is applied and its effects are analyzed. The data processing has been performed by constructing a Kalman filter with states of positions, ambiguities, and the ionospheric delays in the double differenced mode. Considering the medium or long baseline length, both double differenced GPS phase and code observations are used as observables and LAMBDA has been applied to fix the ambiguities. The ionospheric delay is stochastically modeled by well-known 1st order Gauss-Markov process. And the correlation time and variation of 1st order Gauss-Markov process are calculated. This paper gives analyzed results of developed algorithm compared with commercial software and Bernese.

Routing Method based on Prediction of Link State between UAVs in FANET (FANET에서 UAV간 링크 상태 예측에 기반한 라우팅 기법)

  • Hwang, HeeDoo
    • Journal of Korea Multimedia Society
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    • v.19 no.11
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    • pp.1829-1836
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    • 2016
  • Today, the application area and scope of FANET(Flying Ad Hoc Network) has been extended. As a result, FANET related research are actively conducted, but there is no decision yet as the routing protocol for FANET. In this paper, we propose the OLSR-Pds (Prediction with direction and speed) which is added a method to predict status of link for OLSR protocol. The mobility of nodes are modeled using Gauss-Markov algorithm, and relative speed between nodes were calculated by derive equation of movement, and thereby we can predict link status. An experiment for comparing AODV, OLSR and, OLSR-Pds was conducted by three factors such as packet delivery ratio, end to end delay, and routing overhead. In experiment result, we were confirm that OLSR-Pds performance are superior in these three factors. OLSR-Pds has the disadvantage that requires time-consuming calculations for link state and required for computing resources, but we were confirm that OLSR-Pds is suitable for routing to the FANET environment because it has all the characteristics of proactive protocol and reactive protocol.

On-line Vector Quantizer Design Using Stochastic Relaxation (Stochastic Relaxation 방법을 이용한 온라인 벡터 양자화기 설계)

  • Song, Geun-Bae;Lee, Haing-Sei
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.5
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    • pp.27-36
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    • 2001
  • This paper proposes new design algorithms based on stochastic relaxation (SR) for an on-line vector quantizer (VQ) design. These proposed SR methods solve the local entrapment problems of the conventional Kohonen learning algorithm (KLA). These SR methods cover two different types depending upon the use of simulated annealing (SA) : the one that uses SA is called the OLVQ SA and the other the OLVQ SR. These methods arc combined with the KLA and therefore preserve the its convergence properties. Experimental results for Gauss Markov sources, real speech and image demonstrate that the proposed algorithms can consistently provide better codebooks than the KLA.

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A Study on the Fast Search Algorithm for Vector Quantization (벡터 양자화를 위한 고속 탐색 알고리듬에 관한 연구)

  • 지상현;김용석;이남일;강상원
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.4
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    • pp.293-298
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    • 2003
  • In this paper. we propose a fast search algorithm for nearest neighbor vector quantization (NNVQ). The proposed algorithm rejects those codewords which can not be the nearest codeword and reduces the search range of codebook. Hence it reduces computational time and complexity in encoding process, while it provides the same SD performance as the conventional full search algorithm. We apply the proposed algorithm to the adaptive multi-rate (AMR) speech coder and a general vector quantizer designed by LBG. algorithm. Simulation results show effectiveness of the proposed algorithm.

Kalman filter modeling for the estimation of tropospheric and ionospheric delays from the GPS network (망기반 대류 및 전리층 지연 추출을 위한 칼만필터 모델링)

  • Hong, Chang-Ki
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_1
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    • pp.575-581
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    • 2012
  • In general, various modeling and estimation techniques have been proposed to extract the tropospheric and ionospheric delays from the GPS CORS. In this study, Kalman filter approach is adopted to estimate the tropospheric and ionospheric delays and the proper modeling for the state vector and the variance-covariance matrix for the process noises are performed. The coordinates of reference stations and the zenith wet delays are estimated with the assumption of random walk stochastic process. Also, the first-order Gauss-Markov stochastic process is applied to compute the ionospheric effects. For the evaluation of the proposed modeling technique, Kalman filter algorithm is implemented and the numerical test is performed with the CORS data. The results show that the atmospheric effects can be estimated successfully and, as a consequence, can be used for the generation of VRS data.

The Effect of Noise Injection into Inputs in the Kohonen Learning (Kohonen 학습의 입력에 잡음 주입의 효과)

  • 정혁준;송근배;이행세
    • Proceedings of the IEEK Conference
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    • 2001.06d
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    • pp.265-268
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    • 2001
  • This paper proposes the strategy of noise injection into inputs in the Kohonen learning algorithm (KKA) to improve the local convergence problem of the KLA. Noise strengths are high in the begin of the learning and gradually lowered as the teaming proceeds. This strategy is a kind of stochastic relaxation (SR) method which is broadly used in the general optimization problems. It is convenient to implement and improves the convergence properties of the KLA with moderately increased computing time compared to the KLA. Experimental results for Gauss-Markov sources and real speech demonstrate that the proposed method can consistently provide better codebooks than the KLA.

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A Single Mobile Target Tracking in Voronoi-based Clustered Wireless Sensor Network

  • Chen, Jiehui;Salim, Mariam B.;Matsumoto, Mitsuji
    • Journal of Information Processing Systems
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    • v.7 no.1
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    • pp.17-28
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    • 2011
  • Despite the fact that the deployment of sensor networks and target tracking could both be managed by taking full advantage of Voronoi diagrams, very little few have been made in this regard. In this paper, we designed an optimized barrier coverage and an energy-efficient clustering algorithm for forming Vonoroi-based Wireless Sensor Networks(WSN) in which we proposed a mobile target tracking scheme (CTT&MAV) that takes full advantage of Voronoi-diagram boundary to improve detectability. Simulations verified that CTT&MAV outperforms random walk, random waypoint, random direction and Gauss-Markov in terms of both the average hop distance that the mobile target moved before being detected and lower sensor death rate. Moreover, we demonstrate that our results are robust as realistic sensing models and also validate our observations through extensive simulations.

Determination of Optimal Cell Capacity for Initial Cell Planning in Wireless Cellular Networks

  • Hwang, Young-Ha;Noh, Sung-Kee;Kim, Sang-Ha
    • Journal of Information Processing Systems
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    • v.2 no.2
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    • pp.88-94
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    • 2006
  • In wireless cellular networks, previous researches on admission control policies and resource allocation algorithm considered the QoS (Quality of Service) in terms of CDP (Call Dropping Probability) and CBP (Call Blocking Probability). However, since the QoS was considered only within a predetermined cell capacity, the results indicated a serious overload problem of systems not guaranteeing both CDP and CBP constraints, especially in the hotspot cell. That is why a close interrelationship between CDP, CBP and cell capacity exists. Thus, it is indispensable to consider optimal cell capacity guaranteeing multiple QoS (CDP and CBP) at the time of initial cell planning for networks deployment. In this paper, we will suggest a distributed determination scheme of optimal cell capacity guaranteeing both CDP and CBP from a long-term perspective for initial cell planning. The cell-provisioning scheme is performed by using both the two-dimensional continuous-time Markov chain and an iterative method called the Gauss-Seidel method. Finally, numerical and simulation results will demonstrate that our scheme successfully determines an optimal cell capacity guaranteeing both CDP and CBP constraints for initial cell planning.