能量極小化的一種啟發(fā)式遺傳算法
A HEURISTIC GENETIC ALGORITHMS FOR ENERGY MINIMIZATION
-
摘要: Chakradhar et.al(1988,1990)將組合電路表示為Hopfield神經(jīng)網(wǎng)絡(luò),將測試生成問題轉(zhuǎn)化為一個組合優(yōu)化問題。本文在傳統(tǒng)遺傳算法的基礎(chǔ)上,結(jié)合電路的拓?fù)湫畔?提出了一種用于組合電路神經(jīng)網(wǎng)絡(luò)模型能量極小化的啟發(fā)式遺傳算法。
-
關(guān)鍵詞:
- 神經(jīng)網(wǎng)絡(luò); 優(yōu)化; 遺傳算法; 測試生成
Abstract: Chakradhar, et al(1988, 1990) represent the combinational circuit as a Hopfield neural network and formulate the test generation problem as an optimization problem. In this paper, a heuristic genetic algorithms is proposed based on traditional GA and circuit topology information. The algorithm is used for energy minimization of combinaitonal circuit s neural networks. -
Chakradhar S T, Bushnell M L, Agrawal V D. Automatic test generation using neural netwarks. IEEE Int. Conf. on CAD, Santa chara: 1988, 416-419.[2]Chakradhar S T, Bushnell M L, Agrawal V D. Toward massively parallel automatic test generation. IEEE Trans. on CAD, 1990, CAD-9(9): 981-994.[3]Holland J H. Adaptation in natural and artifical system. Ann Arbor: The University of Michigan Press. 1975.[4]Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning. Reading, Mass: Addison-Wesley, 1989, Chapter 5, 147-214. -
計量
- 文章訪問數(shù): 2050
- HTML全文瀏覽量: 116
- PDF下載量: 408
- 被引次數(shù): 0
下載:
