• Agribusiness and Information Management
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• v.1 no.2
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• pp.43-60
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• 2009

To improve the performance of wide-issue superscalar processors, it is essential to increase the width of instruction fetch and the issue rate. Removal of control hazard has been put forward as a significant new source of instruction-level parallelism for superscalar processors and the conditional branch prediction is an important technique for improving processor performance. Branch mispredictions, however, waste a large number of cycles, inhibit out-of-order execution, and waste electric power on mis-speculated instructions. Hence, the branch predictor with higher accuracy is necessary for good processor performance. In global-history-based predictors like gshare and GAg, many mispredictions come from commit update of the branch history. Some works on this subject have discussed the need for speculative update of the history and recovery mechanisms for branch mispredictions. In this paper, we present a new mechanism for recovering the branch history after a misprediction. The proposed mechanism adds an age_counter to the original predictor and doubles the size of the branch history register. The age_counter counts the number of outstanding branches and uses it to recover the branch history register. Simulation results on the SimpleScalar 3.0/PISA tool set and the SPECINT95 benchmarks show that gshare and GAg with the proposed recovery mechanism improved the average prediction accuracy by 2.14% and 9.21%, respectively and the average IPC by 8.75% and 18.08%, respectively over the original predictor.

• ETRI Journal
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• v.35 no.2
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• pp.193-199
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• 2013

This paper addresses nonnegative independent component analysis (NICA), with the aim to realize the blind separation of nonnegative well-grounded independent source signals, which arises in many practical applications but is hardly ever explored. Recently, Bertrand and Moonen presented a multiplicative NICA (M-NICA) algorithm using multiplicative update and subspace projection. Based on the principle of the mutual correlation minimization, we propose another novel cost function to evaluate the diagonalization level of the correlation matrix, and apply the multiplicative exponentiated gradient (EG) descent update to it to maintain nonnegativity. An efficient approach referred to as the EG-NICA algorithm is derived and its validity is confirmed by numerous simulations conducted on different types of source signals. Results show that the separation performance of the proposed EG-NICA algorithm is superior to that of the previous M-NICA algorithm, with a better unmixing accuracy. In addition, its convergence speed is adjustable by an appropriate user-defined learning rate.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.145-149
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• 1993

This paper considers the adaptive predictive control problem of a system characterized by a multiplexed measurements and multirate sampling mechanism. Plant outputs are measured in various sampling rates through a multiplexed measurement system where a single common instrument is shared by several controllers. In general, output measurement sampling rate is assumed to be slower that input update rate. An adaptive predictive control algorithm is developed for systems with multiplexed measurements.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.11
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• pp.592-600
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• 2001

To improve the performance of wide-issue Superscalar microprocessors, it is essential to increase the width of instruction fetch and issue rate. Data dependences are major hurdle to exploit ILP(Instruction-Level Parallelism) efficiently, so several related works have suggested that the limits imposed by data dependences can be overcome to some extent with the use of the data value prediction. But the suggested mechanisms may access the same value prediction table entry again before they have been updated with a real data value. They will cause incorrect value prediction by using stable data and incur misprediction penalty and lowering performance. In this paper, we propose a new hybrid value predictor which achieve high performance by reducing stale data. Because the proposed hybrid value predictor can update the prediction table speculatively, it efficiently reduces the number of mispredicted instruction due to stable due to stale data. For SPECint95 benchmark programs on the 16-issue superscalar processors, simulation results show that the average prediction accuracy increase from 59% for non-speculative update to 72% for speculative update.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.159-167
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• 2009

The vehicles play a significant role in modern people's life as economy grows. The development of car navigation system(CNS) provides various convenience because it shows the driver where they are and how to get to the destination from the point of source. However, the existing map-based CNS does not consider any environments such as traffic congestion. Given the same starting point and destination, the system always provides the same route and the required time. This paper proposes a path planning method with traffic prediction by applying historical driving information to the Fuzzy theory and Bayesian update. Fuzzy theory classifies the historical driving information into groups of leaving time and speed rate, and the traffic condition of each time zone is calculated by Bayesian update. An ellipse area including starting and destination points is restricted in order to reduce the calculation time. The accuracy and practicality of the proposed scheme are verified by several experiments and comparisons with real navigation.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.68-74
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• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.49-57
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• 2009

This paper has proposed Flow Holding Time based Link State Update(LSU) Algorithm that can improve the performance of the existing LSU algorithms. As the existing LSU algorithms are based on the network traffic information, the proposed algorithm is based on flow holding time so we can minimize the LSU message overhead and has not had a strong influence on the depreciation of QoS routing performance. We apply a flow holding time in order to decrease the number of LSU message. We have evaluated the performance of the proposed model and the existing algorithms on MCI simulation network using the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.65-71
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• 2008

This paper proposes a structure of haptic collaboration system over high resolution tiled-display, and proposes a QoE (quality of experience) increase scheme in integrated system. Both haptic system and tiled-display system have requirements of computational power. A haptic device is unstable if haptic rendering rate is less than 1kHz, A requirement of tiled-display systeme is frame rate of display. It requires update of 30 frame fer sec. If we use these systems independently, we can satisfy each requirements. However, if we integrate two systems, performance of entire system significantly decreases because of lack of resources, and QoE of users also decrease. In this paper, therefore, we propose a QoE guaranty scheme which selectively allocates cpu resource between display update and haptic rendering. In order to increase QoE, we set a priority for visual and haptic in order to allocate more resource on visual or haptic. If a user sensitive about touch, then proposed scheme increases haptic rendering rate by allocating more resource. Otherwise a user more sensitive about visual than haptic, proposed scheme decreases haptic rendering rate and increases tiled-display update rate. Therefore, by selectively allocating limited cpu resource, proposed scheme guaranties QoE of both haptic and visual.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1995.10a
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• pp.32-32
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• 1995

선박의 운항 상태를 재현하기 위한 시뮬레이터의 가시화 프로그램은 컴퓨터 그래픽 기법을 이용하여 사용자에게 실제로 선박을 운항하는 현실감을 제공하는 기능을 가져야 한다. 시뮬레이터를 위한 3차원 그래픽의 특성은 실제 상황을 실시간(real-time)으로 재현(15∼30Hz Update rates)해야 하는 기능이 요구되기 때문에 시점 변화에 빠른 그래픽 관련 계산 및 화면 표시에 필요한 시간 제약이 비교적 적은 CAD나 Animation용 3차원 그래픽 시스템과 달리, 시뮬레이션 대상 물체의 운동 상태를 정확히 표현하기 위한 빠른 3차원 그래픽 재현 기능이 매우 중요한 요소가 된다. 그러나 현실감 재현의 관점에서 광고 및 영화용 Animation시스템에서와 같은 Poto-Realistic한 현실감 재현 기능도 무시할 수 없는 요소이고, 현재 최신 컴퓨터 그래픽 기술의 발전과 고성능 그래픽 장비의 개발로 빠른 update rate의 현실감 있는 화면 재현이 가능해 지고 있고 이러한 기능의 요구가 점차 높아지고 있다.