An Immune Clonal Selection Algorithm for Synthetic Signature Generation
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-02
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The collection of signature data for system development and evaluation generally requires significant time and effort.
To overcome this problem, this paper proposes a detector generation based clonal selection algorithm for synthetic signature set generation.
The goal of synthetic signature generation is to improve the performance of signature verification by providing more training samples.
Our method uses the clonal selection algorithm to maintain the diversity of the overall set and avoid sparse feature distribution.
The algorithm firstly generates detectors with a segmented r-continuous bits matching rule and P-receptor editing strategy to provide a more wider search space.
Then the clonal selection algorithm is used to expand and optimize the overall signature set.
We demonstrate the effectiveness of our clonal selection algorithm, and the experiments show that adding the synthetic training samples can improve the performance of signature verification.
American Psychological Association (APA)
Song, Mofei& Sun, Zhengxing. 2014. An Immune Clonal Selection Algorithm for Synthetic Signature Generation. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-463558
Modern Language Association (MLA)
Song, Mofei& Sun, Zhengxing. An Immune Clonal Selection Algorithm for Synthetic Signature Generation. Mathematical Problems in Engineering No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-463558
American Medical Association (AMA)
Song, Mofei& Sun, Zhengxing. An Immune Clonal Selection Algorithm for Synthetic Signature Generation. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-463558
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-463558