• Title/Summary/Keyword: 자유 공간 병렬처리

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Optical CBC Block Encryption Method using Free Space Parallel Processing of XOR Operations (XOR 연산의 자유 공간 병렬 처리를 이용한 광학적 CBC 블록 암호화 기법)

  • Gil, Sang Keun
    • Korean Journal of Optics and Photonics
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    • v.24 no.5
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    • pp.262-270
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    • 2013
  • In this paper, we propose a modified optical CBC(Cipher Block Chaining) encryption method using optical XOR logic operations. The proposed method is optically implemented by using dual encoding and a free-space interconnected optical logic gate technique in order to process XOR operations in parallel. Also, we suggest a CBC encryption/decryption optical module which can be fabricated with simple optical architecture. The proposed method makes it possible to encrypt and decrypt vast two-dimensional data very quickly due to the fast optical parallel processing property, and provides more security strength than the conventional electronic CBC algorithm because of the longer security key with the two-dimensional array. Computer simulations show that the proposed method is very effective in CBC encryption processing and can be applied to even ECB(Electronic Code Book) mode and CFB(Cipher Feedback Block) mode.

Synthesis of Asynchronous Circuits from Free-Choice Signal Transition Graphs with Timing Constraints (시간 제한 조건을 가진 자유 선택 신호 전이 그래프로부터 비동기 회로의 합성)

  • Jeong, Seong-Tae;Jeong, Seok-Tae
    • The KIPS Transactions:PartA
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    • v.9A no.1
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    • pp.61-74
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    • 2002
  • This paper presents a method which synthesizes asynchronous circuits from free-choice Signal Transition Graphs (STGs) with timing constraints. The proposed method synthesizes asynchronous circuits by analyzing: the relations between signal transitions directly from the STGs without generating state graphs. The synthesis procedure decomposes a free-choice STG into deterministic STGs which do not have choice behavior. Then, a timing analysis extracts the timed concurrency and tamed causality relations between any two signal transitions for each deterministic STG. The synthesis procedure synthesizes circuits for each deterministic STG and synthesizes the final circuit by merging the circuits for each deterministic STG. The experimental results show that our method achieves significant reductions in synthesis time for the circuits which have a large state space, and generates circuits that have nearly the same area as compared to previous methods.

Parallel $XY{\theta}$ Table Design and Implementation for Precision Positioning (고정밀 위치 제어용 병렬 $XY{\theta}$ 테이블 설계 및 구현)

  • Han, Joo-Hun;Oh, Choon-Suk;Ryu, Young-Kee
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.7
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    • pp.62-70
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    • 1999
  • To achieve precision positioning, working area is required within $5mm{\times}5mm$ and positioning error is allowed within minimum ${\pm}4{\mu}m$. As a general three-layered table takes working range from several centimeters and a few tens of centimeters, it has disadvantages compared with precision positioning table, such as larger working range and rough accuracy. In this paper we design and implement a parallel $XY{\theta}$ table with three linear actuators, where one is on the horizontal direction and the others on the vertical direction on behalf of a degree of $XY{\theta}$ freedom. Finally, the experimental results of precision positioning is showed by using new image processing algorithms with two CCD cameras.

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On Developing The Intellingent contro System of a Robot Manupulator by Fussion of Fuzzy Logic and Neural Network (퍼지논리와 신경망 융합에 의한 로보트매니퓰레이터의 지능형제어 시스템 개발)

  • 김용호;전홍태
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.1
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    • pp.52-64
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    • 1995
  • Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

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