• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.10
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• pp.46-52
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• 2009

A Multi-Core/Multi-Thread architecture is adopted for the Shader processor to enhance the processing performance. The Shader processor is designed to utilize its processing core IP for multiple purposes, such as Vertex-Shading, Rasterization, Pixel-Shading, etc. In this paper, we propose a 'Rasterization based on Vector Algorithm' that makes parallel pixels processing possible with Multi-Core and Multi-Thread architecture on the Shader Core. The proposed algorithm takes only 2% operation counts of the Scan-Line Algorithm and processes pixels independently.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1243-1257
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• 2019

As current algorithms unable to perform effective fusion processing of unknown complex radar signals lacking database, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complex radar signals based on evidence theory as a solution to this problem. Specifically, the real-time database is initially established, accompanied by similarity model based on parameter type, and then similarity matrix is calculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity of parameters concerning each signal and the trust value concerning target framework of each signal in order. The signals are ultimately combined and perfected. The results of simulation experiment reveal that the proposed algorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency and less time, maintaining stable processing even of considerable samples.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.7
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• pp.641-647
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• 2015

In this paper, Analyzed the multi-channel signal processing algorithms for digital-transponder. To analyze suitable multi-channel signal processing algorithms, compare algorithms about four criteria. Four criteria are as follows, perfect reconstruction, interference rejection, resource usage and power consumption. Analysis for each algorithm in accordance with these four criteria. then propose the multi-channel signal processing algorithms for digital satellite communication system.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.2
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• pp.103-111
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• 2021

A series of experiments have been carried out by using National Geographic Information Institute(NGII)'s Continuously Operating Reference Station (CORS) data with various strategies to analyze the impact of multi-GNSS measurements on baseline processing. The results of baseline processing were compared in terms of ambiguity fixing rate, precision, and hypothesis tests were conducted to confirm the statistical difference. The combination of multi-GNSS measurements has helped to improve ambiguity fixing rate, especially under harsh positioning environments. Combination of GPS, Galileo, BeiDou could get better precision than that of GPS, GLONASS, Galileo, and adding QZSS made the baseline solution's vertical component more precisely. The hypothesis tests have statistically confirmed that the inclusion of the multi-GNSS in the baseline processing enables not only to reduce field observation time length but also to enhance the solution's precision. However, it is of interest to notice that results of the baseline solution are dependent upon the software used. Hence, comprehensive studies should be performed shortly to derive the best practice to select the appropriate software.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.363-364
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• 2007

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3105-3112
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• 2000

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.743-744
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• 2006

This paper presents implementation of parallel processing system for image processing. The parallel processing system proposed consisted of 16 processing elements, and multi-access memory system, and interface modules. The multi-access memory system we introduced is made up of a memory module selection, a data routing module, and an address calculation and routing module.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.555-555
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• 2000

This study is concentrated on the development of hight speed multi-object image processing algorithm, and based on these a1gorithm, vision control scheme is developed for the robot's position control in real time. Recently, the use of vision system is rapidly increasing in robot's position centre. To apply vision system in robot's position control, it is necessary to transform the physical coordinate of object into the image information acquired by CCD camera, which is called image processing. Thus, to control the robot's point position in real time, we have to know the center point of object in image plane. Particularly, in case of rigid body, the center points of multi-object must be calculated in a image plane at the same time. To solve these problems, the algorithm of multi-object for rigid body control is developed.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.471-482
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• 2012

For disaster exploration and surveillance application, this paper aims to present a novel application of a multi-robot agent based on WSN and to evaluate a multi-hop communication caused by the robotics correspondingly, which are used in the uncertain and unknown subterranean tunnel. A Primary-Scout Multi-Robot System (PS-MRS) was proposed. A chain topology in a subterranean environment was implemented using a trimmed ZigBee2006 protocol stack to build the multi-hop communication network. The ZigBee IC-CC2530 modular circuit was adapted by mounting it on the PS-MRS. A physical experiment based on the strategy of PS-MRS was used in this paper to evaluate the efficiency of multi-hop communication and to realize the delivery of data packets in an unknown and uncertain underground laboratory environment.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.232-239
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• 2023

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multi-description ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multi-description ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point's position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.