• Journal of Industrial Technology
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• v.10
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• pp.15-20
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• 1990

A parallel processing algorithm for discrete Kalman filter, which is one of the most commonly used filtering technique in modern control, signal processing, and communication, is proposed. Previously proposed parallel algorithms to decrease the number of computations needed in the Kalman filter are the hierachical structures by distributed processing of measurements, or the systolic structures to disperse the computational burden. In this paper, a new parallel Kalman filter employing a structure similar to recursive doubling is proposed. Estimated values of state variables by the new algorithm converge with two times faster data processing speed than that of the conventional Kalman filter. Moreover it maintains the optimality of the conventional Kalman filter.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1057-1065
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• 1990

A parallel processing algorithm for the discrete Kalman filter, which is one of the most commonly used filtering techniques in modern control, signal processing, and communication, is proposed. To decrease the number of computations critical in the Kalman filter, previously proposed parallel algorithms are of the hierarchical structure by distributed processing of measurements, or of the systolic structure to disperse the computational burden. In this paper, a new parallel Kalman filter employing a structure similar to recursive doubling is proposed. Estimated valuse of state variables by the new algorithm converge faster to the true values because the new algorithm can process data twice faster than the conventional Kalman filter. Moreover, it maintains the optimality of the conventional Kalman filter.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.64-67
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• 1990

A parallel processing algorithm for discrete Kalman filter, which is one of the most commonly used filtering technique in modern control, signal processing, and communication. is proposed. Previously proposed parallel algorithms to decrease the number of computations needed in the Kalman filter are the hierachical structures by distributed processing of measurements, or the systolic structures to disperse the computational burden. In this paper, a new parallel Kalman filter employing a structure similar to recursive doubling is proposed. Estimated values of state variables by the new algorithm converge with two times faster data processing speed than that of the conventional Kalman filter. Moreover it maintains the optimality of the conventional Kalman filter.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1284-1286
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• 2003

There is a growing demand on remotely sensed and GIS data services in modern society. However, conventional WEB applications based on client/server pattern can not meet the criteria in the future . Grid computing provides a promising resolution for establishing spatial information system toward future applications. Here, a new architecture of the distributed environment for remotely sensed data processing based on the middleware technology was proposed. In addition, in order to utilize the new environment, a problem had to be algorithmically expressed as comprising a set of concurrently executing sub-problems or tasks. Experiment of the algorithm was implemented, and the results show that the new environmental can achieve high speedups for applications compared with conventional implementation.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.24-30
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• 1996

The ray tracing method, which is one of many photorealistic rendering techniques, requires heavy computational processing to synthesize images. Parallel processing can be used to reduce the computational processing time. A parallel algorithm for the ray tracing has been implemented and executed for various images on transputer systems. In order to develop a scalable parallel algorithm, a processor farming technique has been exploited. Since each image is divided and distributed to each farming processor, the scalability of the parallel system and load balancing are achieved naturally in the proposed algorithm. Efficiency of the parallel algorithm is obtained up to 95% for nine processors. However, the best size of a distributed task is much higher in simple images due to less computational requirement for every pixel. Efficiency degradation is observed for large granularity tasks because of load unbalancing caused by the large task. Overall, transputer systems behave as good scalable parallel processing system with respect to the cost-performance ratio.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.7
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• pp.791-797
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• 2014

In order to create an environment for Apache Hadoop for parallel distributed processing system of Bigdata, by connecting a plurality of computers, or to configure the node, using the configuration of the virtual nodes on a single computer it is necessary to build a cloud fading environment. However, be constructed in practice for education in these systems, there are many constraints in terms of cost and complex system configuration. Therefore, it is possible to be used as training for educational institutions and beginners in the field of Bigdata processing, development of learning systems and inexpensive practical is urgent. Based on the Raspberry Pi board, training and analysis of Big data processing, such as Hadoop and NoSQL is now the design and implementation of a learning system of parallel distributed processing of possible Bigdata in this study. It is expected that Bigdata parallel distributed processing system that has been implemented, and be a useful system for beginners who want to start a Bigdata and education.

• Journal of the Korea Society for Simulation
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• v.1 no.1
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• pp.64-76
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• 1992

The DEVS(discrete event system specificaition) formalism specifies a discrete event system in a hierarchical, modular form. DEVSIM++ is a C++based general purpose DEVS abstract simulator which can simulate systems modeled by the DEVS formalism in a sequential environment. This paper describes P-DEVSIM++which is a parallel version of DEVSIM++ . In P-DEVSIM++, the external and internal event of DEVS models can by processed in parallel. For such processing, we propose a parallel, distributed optimistic simulation algorithm based on the Time Warp approach. However, the proposed algorithm localizes the rollback of a model within itself, not possible in the standard Time Warp approach. An advantage of such localization is that the simulation time may be reduced. To evaluate its performance, we simulate a single bus multiprocessor architecture system with an external common memory. Simulation result shows that significant speedup is made possible with our algorithm in a parallel environment.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.631-633
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• 2003

인터넷 가반 분산/병렬 처리 프레임 워크 PDP(Parallel/Distributed Processing Scheme on Web)는 네트워크 내 유휴 상태 호스트들을 활용하여 대용량 작업을 병렬로 처리한다. 본 논문에서는 이러한 서브 작업을 할당받는 자원이 동작하는 네트워크 환경을 모니터링 함으로써 수시로 변화하는 네트워크 환경에 대처하는 방안을 제시한다. 특히 네트워크 환경 모니터링 예측 결과를 PDP의 작업 할당 알고리즘에 적용하여 네트워크 과부하 및 결함 등으로 인해 발생되는 작업 지연 요소에 적응적 대처함으로써 전체 작업 수행 처리율 향상을 도모하는 방법을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.101-108
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• 2007

Parallel processing algorithms, coupled with advanced networking and distributed computing architectures, improve the overall computational performance, dependability, and versatility of a digital signal processing system In this paper, novel parallel algorithms are introduced and investigated for advanced sonar algorithm, conventional matched-field processing (CMFP). Based on a specific domain, each parallel algorithm decomposes the sequential workload in order to obtain scalable parallel speedup. Depending on the processing requirement of the algorithm, the computational performance of the parallel algorithm reveals different characteristics. The high-complexity algorithm, CMFP shows scalable parallel performance on the array of DSP processors. The impact on parallel performance due to workload balancing, communication scheme, algorithm complexity, processor speed, network performance, and testbed configuration is explored.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.40-45
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• 2004

This paper presents the parallel distributed control scheme for shaping of the bent glass. The designed system consists of a PC, a main controller and 11 servo-controllers, the precision motion controllers. Each elements are connected by using RS-232C and 8-bit data bus. In order to guarantee the stability and the control performance, we use a precision PID motion controller and a H-bridge on the servo-drivers. PC calculates position values of 11 DC motors by using the pre-determined curvature value and offers the user interface environment operator. The main controller provides the control instructions and parameter values to 11 servo-controllers by chip enable signal, simultaneously. Using the received commands and parameter values, the servo-controllers control the positions of the DC motors based on PID control scheme.