Neural Network Pattern Recognition Employing Multicriteria Extracted From Signal Projections In Multiple Transform Domains
In this paper, we propose a novel one and multidimensional signal classification system that employs a set of criteria extracted from the signal representation in different transform domains, denoted the Multicriteria Multitransform (MCMT) classifier. The signal projection, in each appropriately selected transform domain, reveals unique signal characteristics. These characteristics in the different domains are properly formulated to obtain classification criteria with efficient implementation properties such as speed and accuracy. Results for image classification confirm the improved classification performance relative to existing techniques. In addition to the improved computational efficiency, the proposed technique maintains higher classification accuracy in the presence of additive noise.
Proceedings of 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, ISIMP 2001
Number of Pages
Article; Proceedings Paper
Source API URL
Abdelwahab, Manal M. and Mikhael, Wasfy B., "Neural Network Pattern Recognition Employing Multicriteria Extracted From Signal Projections In Multiple Transform Domains" (2001). Scopus Export 2000s. 46.