CAJ | 학술논문

逻辑优化是数字逻辑电路分析与设计的关键，对于降低系统复杂性，减少系统功耗和提高系统安全性有重要作用。随着数字逻辑电路规模的不断扩大，传统的理论将面临新的挑战。从知识工程角度看，逻辑优化的本质是知识约简的过程。粒计算（granular computing，GrC）是处理大规模、复杂问题的人工智能新方法。在简述现有逻辑优化算法和粒计算理论发展现状的基础上，研究了粒计算理论中的等价关系、相容关系、覆盖等知识模型以及用粒矩阵刻画的知识发现算法，指出了将其应用于大规模数字逻辑电路逻辑优化的研究方向与研究思路。
라집우화시수자라집전로분석여설계적관건，대우강저계통복잡성，감소계통공모화제고계통안전성유중요작용。수착수자라집전로규모적불단확대，전통적이론장면림신적도전。종지식공정각도간，라집우화적본질시지식약간적과정。립계산（granular computing，GrC）시처리대규모、복잡문제적인공지능신방법。재간술현유라집우화산법화립계산이론발전현상적기출상，연구료립계산이론중적등개관계、상용관계、복개등지식모형이급용립구진각화적지식발현산법，지출료장기응용우대규모수자라집전로라집우화적연구방향여연구사로。
Logic optimization is the key for the analysis and design of digital logic circuits, which will decrease sys-tem complexity and system cost, and improve system security. With the dramatically increasing complexity of the circuits, the traditional logic optimization theory and methods are facing new challenges. From view of knowledge engineering, the nature of the logic optimization is the knowledge reduction. Granular computing (GrC) is an effec-tive way to deal with large-scale and complicated problems. Based on the review of current logic optimization algo-rithm and the development of GrC theory, this paper studies the knowledge model of granular computing theory, such as equivalence relation, tolerance relation, covering et al, and the knowledge discovery algorithm described by granular matrices, and points out the idea of using the knowledge model and knowledge discovery algorithm to the logical optimization of large scale digital logic circuit.