DocumentCode
1597618
Title
Computing Gabor expansion coefficients by TH neural network
Author
Meng, Hongyig ; Liu, Guizhong
Author_Institution
Inst. for Inf. Eng., Xi´´an Jiaotong Univ., China
Volume
2
fYear
1996
Firstpage
1389
Abstract
It is proposed that the Gabor (1946) expansion coefficients of a periodic (or finite) discrete signal in both the critical sampling case and the oversampling case can be computed by TH neural networks. Theoretical analysis and simulations show that this network will certainly provide approximate solutions arbitrarily close to the accurate one within the time of the order of time constants of this network without any programming complexity
Keywords
neural nets; signal representation; signal sampling; Gabor expansion coefficients; TH neural network; approximate solutions; critical sampling; finite discrete signal; oversampling; periodic discrete signal; signal analysis; signal representation; simulations; time constants; Analytical models; Binary search trees; Computed tomography; Computer networks; Hopfield neural networks; Image analysis; Image coding; Image segmentation; Neural networks; Signal analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 1996., 3rd International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-2912-0
Type
conf
DOI
10.1109/ICSIGP.1996.566575
Filename
566575
Link To Document