Title :
Identification and Reduction of F-Recursive Genetic Information
Author :
Yuying Li ; Huannli Zhang ; Kaiquan Shi ; Weirong Chen
Author_Institution :
Dept. of Comput., Ningde Normal Univ., Ningde, China
Abstract :
In order to recognize and control effectively dynamic information, the paper proposes the concept of F̅-recursive genetic information by introducing the concept of heredity in biology and using P-sets, including the concepts of F̅-recursive dominant inheritance information and -F̅-recursive recessive inheritance information. Meanwhile, the structure and characteristics about the F̅-recursive genetic information are provided. The paper gives the identification theorem and identification criterion as well as the reduction method for the F̅-recursive genetic information. Finally, the application of computer vision recognition of F-recursive genetic information is provided. The research indicates that the generated F̅-recursive genetic information is identifiable and the proposed recursive reduction method is more reliable than the non-recursive reduction method. The-recursive genetic information is a new tool to discover information, to forecast information and to control information.
Keywords :
genetics; identification; set theory; F̅-recursive dominant inheritance information; F̅-recursive recessive inheritance information; F-recursive genetic information; P-sets; biology; dynamic information; heredity; identification criterion; identification theorem; Cameras; Computer vision; Educational institutions; Genetics; Orbits; Ports (Computers); identification; recursive dominant inheritance information; recursive genetic information; recursive recessive inheritance information; reduction;
Conference_Titel :
Intelligent Systems (GCIS), 2013 Fourth Global Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4799-2885-9
DOI :
10.1109/GCIS.2013.42