Method of minimization of finite recognizer

doi:10.3778/j.issn.1002-8331.2009.27.009

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (27): 28-30.DOI: 10.3778/j.issn.1002-8331.2009.27.009

• 研究、探讨 • Previous Articles Next Articles

Method of minimization of finite recognizer

HUANG Fei-dan

Department of Mathematics，Bijie College，Bijie，Guizhou 551700，China

Received:2008-12-19 Revised:2009-02-17 Online:2009-09-21 Published:2009-09-21
Contact: HUANG Fei-dan

有限识别器的最小化方法

黄飞丹

毕节学院数学系，贵州毕节 551700

通讯作者: 黄飞丹

Abstract

Abstract: In this paper，a method of minimization of a deterministic finite recognizer is given，and for a kind of non-deterministic finite recognizer，a method of minimization of it is given.

Key words: deterministic finite recognizer, non-deterministic finite recognizer, minimization

摘要： 给出确定型有限识别器最小化的一种方法，并给出一类非确定型有限识别器最小化的方法。

关键词: 确定型有限识别器, 非确定型有限识别器, 最小化

CLC Number:

TP301.1

HUANG Fei-dan. Method of minimization of finite recognizer[J]. Computer Engineering and Applications, 2009, 45(27): 28-30.

黄飞丹. 有限识别器的最小化方法[J]. 计算机工程与应用, 2009, 45(27): 28-30.

[1]	WANG Jie, JIN Zhengmeng, FENG Can. Adaptive Generalized Total Variation Algorithm for Poisson Noise Removal [J]. Computer Engineering and Applications, 2021, 57(20): 203-209.
[2]	MA Chengqi, LI Xuehua, ZHANG Lanjie, XIANG Wei. Anti-oclusion Monocular Depth Estimation Algorithm [J]. Computer Engineering and Applications, 2021, 57(2): 217-222.
[3]	ZHENG Xinglin, WANG Yue, LIU Wei. Partially Connected Hybrid Precoding Design for Millimeter Wave MIMO System [J]. Computer Engineering and Applications, 2020, 56(18): 97-103.
[4]	YAN Liping1, MA Jiajun1, CHEN Wenxing2. Sparse Structured Least Squares Twin Support Vector Regression Machine [J]. Computer Engineering and Applications, 2019, 55(3): 10-14.
[5]	NIE Dongdong, HE Yueyue. Fast face recognition based on dictionary expansion [J]. Computer Engineering and Applications, 2018, 54(8): 201-206.
[6]	YANG Hairong1, JIN Hui2. Improved IRLS algorithm for nonconvex compressive sensing [J]. Computer Engineering and Applications, 2018, 54(24): 46-51.
[7]	WU Yajuan, XU Liming. Total variation blind restoration using high-order P-Laplace [J]. Computer Engineering and Applications, 2017, 53(2): 220-224.
[8]	LUO Hao1，2, LIU Yu1，2, WU Sijin3. Comprehensive comparative study of protein-peptide docking algorithms performance [J]. Computer Engineering and Applications, 2017, 53(14): 111-116.
[9]	WANG Zhendao, CHEN Yi. Binary Decision Diagram variable ordering based on catastrophe genetic algorithm [J]. Computer Engineering and Applications, 2015, 51(3): 55-60.
[10]	LIN Zhihong, LI Guang, LUO Shouhua. Ring artifact correction via total variation minimization [J]. Computer Engineering and Applications, 2015, 51(21): 195-198.
[11]	SONG Jinping, ZHENG Changyan. Fast image inpainting of high-order model [J]. Computer Engineering and Applications, 2015, 51(11): 154-157.
[12]	ZHENG Xiaoqing, WEI Jiang, GE Wenfeng, GE Ming. First-principle modeling and solving method for universal Gibbs reactor [J]. Computer Engineering and Applications, 2014, 50(19): 241-244.
[13]	LIU Zhen, JIANG Hui, WANG Libin. SAR ATR method based on sparse representation [J]. Computer Engineering and Applications, 2014, 50(10): 212-215.
[14]	CHEN Chu1, REN Pinghong1, YU Jiguo1, MA Bingxian2. Perfect state-judging list based minimization algorithm for DFA [J]. Computer Engineering and Applications, 2013, 49(6): 48-51.
[15]	LI Junhua1, GAO Linqing2, LI Haijun3. Key theorem of learning theory with samples corrupted by noise on pan-space [J]. Computer Engineering and Applications, 2012, 48(27): 49-52.

Method of minimization of finite recognizer

有限识别器的最小化方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics