A Novel Orthonormal Wavelet Network for Function Learning

2005 ◽  
pp. 358-363
Author(s):  
Xieping Gao ◽  
Jun Zhang
Keyword(s):  
Wavelet Network ◽  
Orthonormal Wavelet ◽  
Function Learning

Wavelet Network for Recursive Function Learning

2003 ◽  
pp. 710-715 ◽  
Author(s):  
Zygmunt Hasiewicz
Keyword(s):  
Recursive Function ◽  
Wavelet Network ◽  
Function Learning

An adaptive wavelet network for function learning

2009 ◽  
Vol 19 (3) ◽  
pp. 383-392 ◽  
Author(s):  
Yusuf Oysal ◽  
Sevcan Yilmaz
Keyword(s):  
Wavelet Network ◽  
Function Learning ◽  
Adaptive Wavelet

Multi-scale wavelet network algorithm for pediatric echocardiographic segmentation via hierarchical feature guided fusion

2021 ◽  
pp. 107386
Author(s):  
Cheng Zhao ◽  
Bei Xia ◽  
Weiling Chen ◽  
Libao Guo ◽  
Jie Du ◽  
...  
Keyword(s):  
Wavelet Network ◽  
Multi Scale ◽  
Network Algorithm

A new family of orthonormal wavelet bases

1998 ◽  
Vol 72 (5) ◽  
pp. 294-303 ◽  
Author(s):  
L. T. Liu ◽  
H. T. Hsu ◽  
B. X. Gao
Keyword(s):  
Orthonormal Wavelet ◽  
Wavelet Bases ◽  
New Family

Wavelet network-based classification of transients using dominant frequency signature

2008 ◽  
Vol 78 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Saibal Chatterjee ◽  
Sivaji Chakravorti ◽  
Chinmoy Kanti Roy ◽  
Debangshu Dey
Keyword(s):  
Dominant Frequency ◽  
Wavelet Network

A NEURAL NETWORK-WAVELET MODEL FOR GENERATING ARTIFICIAL ACCELEROGRAMS

2004 ◽  
Vol 02 (03) ◽  
pp. 217-235 ◽  
Author(s):  
GENE F. SIRCA ◽  
HOJJAT ADELI
Keyword(s):  
Neural Network ◽  
Geographic Location ◽  
Training Data ◽  
Wavelet Network ◽  
Design Spectrum ◽  
Earthquake Resistant Design ◽  
Earthquake Resistant ◽  
Structural Configurations ◽  
Earthquake Accelerograms ◽  
Artificial Accelerograms

In earthquake-resistant design of structures, for certain structural configurations and conditions, it is necessary to use accelerograms for dynamic analysis. Accelerograms are also needed to simulate the effects of earthquakes on a building structure in the laboratory. A new method of generating artificial earthquake accelerograms is presented through adroit integration of neural networks and wavelets. A counterpropagation (CPN) neural network model is developed for generating artificial accelerograms from any given design spectrum such as the International Building Code (IBC) design spectrum. Using the IBC design spectrum as network input means an accelerogram may be generated for any geographic location regardless of whether earthquake records exist for that particular location or not. In order to improve the efficiency of the model, the CPN network is modified with the addition of the wavelet transform as a data compression tool to create a new CPN-wavelet network. The proposed CPN-wavelet model is trained using 20 sets of accelerograms and tested with additional five sets of accelerograms available from the U.S. Geological Survey. Given the limited set of training data, the result is quite remarkable.

A three-domain fuzzy wavelet network filter using fuzzy PSO for robotic assisted minimally invasive surgery

2014 ◽  
Vol 66 ◽  
pp. 13-27 ◽  
Author(s):  
Zhi Liu ◽  
Caiyun Mao ◽  
Jing Luo ◽  
Yun Zhang ◽  
C.L. Philip Chen
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Wavelet Network ◽  
Robotic Assisted
Sign in / Sign up

Export Citation Format

Share Document