• 제목/요약/키워드: TD algorithm

검색결과 77건 처리시간 0.037초

RAKE Receiver for Time Division Synchronous CDMA Mobile Terminal

  • Xiao Yang;Lee Kwang-Jae;Lee Moon-Ho
    • Journal of electromagnetic engineering and science
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    • 제6권1호
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    • pp.10-17
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    • 2006
  • For the sake of the potential ability of overcoming interference in TD-SCDMA(time division-synchronous code division multiple access) systems, pilot signal is adopted, but the presented TD-SCDMA protocol has not considered the Rake technique for their mobile terminals. This paper developed a RAKE receiver algorithm and an implementation circuit, which make use of the pilot signal in the burst structure of the TD-SCDMA base station to estimate main channel parameter(channel delays) in the downlink of TD-SCDMA wireless network. The algorithm can reduce multipath interference for the mobile units in multiusers' case. Theoretic performance analysis presented in the paper and computer simulations show that there is a range of BER for Rake receiver and confirm that the proposed RAKE receiver algorithm achieved a better performance under multipath fading propagation and multiusers conditions.

멀티-스텝 누적 보상을 활용한 Max-Mean N-Step 시간차 학습 (Max-Mean N-step Temporal-Difference Learning Using Multi-Step Return)

  • 황규영;김주봉;허주성;한연희
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제10권5호
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    • pp.155-162
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    • 2021
  • n-스텝 시간차 학습은 몬테카를로 방법과 1-스텝 시간차 학습을 결합한 것으로, 적절한 n을 선택할 경우 몬테카를로 방법과 1-스텝 시간차 학습보다 성능이 좋은 알고리즘으로 알려져 있지만 최적의 n을 선택하는 것에 어려움이 있다. n-스텝 시간차 학습에서 n값 선택의 어려움을 해소하기 위해, 본 논문에서는 Q의 과대평가가 초기 학습의 성능을 높일 수 있다는 특징과 Q ≈ Q* 경우, 모든 n-스텝 누적 보상이 비슷한 값을 가진다는 성질을 이용하여 1 ≤ k ≤ n에 대한 모든 k-스텝 누적 보상의 최댓값과 평균으로 구성된 새로운 학습 타겟인 Ω-return을 제안한다. 마지막으로 OpenAI Gym의 Atari 게임 환경에서 n-스텝 시간차 학습과의 성능 비교 평가를 진행하여 본 논문에서 제안하는 알고리즘이 n-스텝 시간차 학습 알고리즘보다 성능이 우수하다는 것을 입증한다.

차량항법 시스템을 위한 소형 음성합성 엔진 (Speech synthesis engine for car navigation systems)

  • 김경하;서흥석;박찬식;성태경;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.338-338
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    • 2000
  • This paper proposes a modified TD-PSOLA algorithm for Korean speech synthesis. A WSS (Weighted score search) algorithm is proposed for pitch detection and speech synthesis engine is designed using 46 phones database.

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Duplication with Task Assignment in Mesh Distributed System

  • Sharma, Rashmi;Nitin, Nitin
    • Journal of Information Processing Systems
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    • 제10권2호
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    • pp.193-214
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    • 2014
  • Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).

TD-SCDMA에서 셀간 간섭 억제를 위한 전송속도 제어 (Data rate control for suppression of inter-cell interference in TD-SCDMA systems)

  • 여운영;이상연
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.265-266
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    • 2008
  • TD-SCDMA combines TDMA and CDMA components to provide more efficient use of radio resources. However, since the same frequency band is used in both the uplink and downlink, serious interference may occur if the base stations are not synchronized. The interference caused by different transmission directions between neighboring cells is called cross-slot interference. This paper proposes a data rate control algorithm that can decrease the cross-slot interference in TD-SCDMA.

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Fast-convergence trilinear decomposition algorithm for angle and range estimation in FDA-MIMO radar

  • Wang, Cheng;Zheng, Wang;Li, Jianfeng;Gong, Pan;Li, Zheng
    • ETRI Journal
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    • 제43권1호
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    • pp.120-132
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    • 2021
  • A frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar employs a small frequency increment across transmit elements to produce an angle-range-dependent beampattern for target angle and range detection. The joint angle and range estimation problem is a trilinear model. The traditional trilinear alternating least square (TALS) algorithm involves high computational load due to excessive iterations. We propose a fast-convergence trilinear decomposition (FC-TD) algorithm to jointly estimate FDA-MIMO radar target angle and range. We first use a propagator method to obtain coarse angle and range estimates in the data domain. Next, the coarse estimates are used as initialized parameters instead of the traditional TALS algorithm random initialization to reduce iterations and accelerate convergence. Finally, fine angle and range estimates are derived and automatically paired. Compared to the traditional TALS algorithm, the proposed FC-TD algorithm has lower computational complexity with no estimation performance degradation. Moreover, Cramer-Rao bounds are presented and simulation results are provided to validate the proposed FC-TD algorithm effectiveness.

Enhancing VANET Security: Efficient Communication and Wormhole Attack Detection using VDTN Protocol and TD3 Algorithm

  • Vamshi Krishna. K;Ganesh Reddy K
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권1호
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    • pp.233-262
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    • 2024
  • Due to the rapid evolution of vehicular ad hoc networks (VANETs), effective communication and security are now essential components in providing secure and reliable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. However, due to their dynamic nature and potential threats, VANETs need to have strong security mechanisms. This paper presents a novel approach to improve VANET security by combining the Vehicular Delay-Tolerant Network (VDTN) protocol with the Deep Reinforcement Learning (DRL) technique known as the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. A store-carry-forward method is used by the VDTN protocol to resolve the problems caused by inconsistent connectivity and disturbances in VANETs. The TD3 algorithm is employed for capturing and detecting Worm Hole Attack (WHA) behaviors in VANETs, thereby enhancing security measures. By combining these components, it is possible to create trustworthy and effective communication channels as well as successfully detect and stop rushing attacks inside the VANET. Extensive evaluations and simulations demonstrate the effectiveness of the proposed approach, enhancing both security and communication efficiency.

평면파 해석을 이용한 시간영역-유한차분법의 수치적 에너지 보존성질의 증명 (A Verification of the Numerical Energy Conservation Property of the FD-TD(Finite Difference-Time Domain) Method by Using a Plane Wave Analysis)

  • Ihn-Seok Kim
    • 한국전자파학회논문지
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    • 제7권4호
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    • pp.320-327
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    • 1996
  • This paper presents that the lossy or amplification property of the Finite Difference-Time Domain(FD-TD) method based on the leap-frog scheme is theoretically verified by using a plane wave analysis. The basic algorithm of the FD-TD method is introduced in order to help understanding the analysis procedure. Since our analysis is formulated by the Von Neumann's approach, the stability inequality is also produced as an another outcome.

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목표지향적 강화학습 시스템 (Goal-Directed Reinforcement Learning System)

  • 이창훈
    • 한국인터넷방송통신학회논문지
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    • 제10권5호
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    • pp.265-270
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    • 2010
  • 강화학습(reinforcement learning)은 동적 환경과 시행-착오를 통해 상호 작용하면서 학습을 수행한다. 그러므로 동적 환경에서 TD-학습과 TD(${\lambda}$)-학습과 같은 강화학습 방법들은 전통적인 통계적 학습 방법보다 더 빠르게 학습을 할 수 있다. 그러나 제안된 대부분의 강화학습 알고리즘들은 학습을 수행하는 에이전트(agent)가 목표 상태에 도달하였을 때만 강화 값(reinforcement value)이 주어지기 때문에 최적 해에 매우 늦게 수렴한다. 본 논문에서는 미로 환경(maze environment)에서 최단 경로를 빠르게 찾을 수 있는 강화학습 방법(GORLS : Goal-Directed Reinforcement Learning System)을 제안하였다. GDRLS 미로 환경에서 최단 경로가 될 수 있는 후보 상태들을 선택한다. 그리고 나서 최단 경로를 탐색하기 위해 후보 상태들을 학습한다. 실험을 통해, GDRLS는 미로 환경에서 TD-학습과 TD(${\lambda}$)-학습보다 더 빠르게 최단 경로를 탐색할 수 있음을 알 수 있다.

$SF_6+Ar$ 혼합기체의 MCS-BE 알고리즘에 의한 전자에너지 분포함수 (A Study on the Electron Energy Distribution Function in $SF_6+Ar$ Mixtures Gas used by MCS-BE Algorithm)

  • 김상남;하성철
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 학술대회 논문집 전문대학교육위원
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    • pp.17-21
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    • 2000
  • A Study on the electron energy distribution function in $SF_6+Ar$ mixtures gas used by MCS-BE algorithm, the electron swam parameters in the 0.5% and 0.2% $SF_6+Ar$ mixtures are measured by time of flight method over the E/N(Td) range from 30 to 300(Td). A two-term approximation of the Boltzmann equation analysis and Monte Carlo simulation have been also used to study electron transport coefficients. The electron energy distribution function has been analysed in $SF_6$ gas and $SF_6+Ar$ mixtures at E/N : 200(Td) for a case of the equilibrium region in the mean electron energy. The measured results and the calculated results have been compared each other.

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