Multiscale-Combined Inversion of Convolutional Model Based on Orthogonal Wavelet Transform

2002 ◽  
pp. 433-443
Author(s):  
Jianwei Ma ◽  
Huizhu Yang ◽  
Yaping Zhu
Keyword(s):  
Wavelet Transform ◽  
Orthogonal Wavelet ◽  
Model Based ◽  
Orthogonal Wavelet Transform

A CFAR detector based on orthogonal wavelet transform

2014 ◽  
Author(s):  
Tao Jian ◽  
Guisheng Liao ◽  
You He ◽  
Jian Shen
Keyword(s):  
Wavelet Transform ◽  
Orthogonal Wavelet ◽  
Orthogonal Wavelet Transform

scholarly journals SNR Improvement for Evoked Potential Estimation using Bi – Orthogonal Wavelet Transform

IJARCCE ◽  
2015 ◽  
Vol 4 (8) ◽  
pp. 408-413
Author(s):  
Shailesh M L ◽  
Dr. Anand Jatti ◽  
Madhushree K S ◽  
Siddesh M B
Keyword(s):  
Wavelet Transform ◽  
Evoked Potential ◽  
Orthogonal Wavelet ◽  
Snr Improvement ◽  
Evoked Potential Estimation ◽  
Orthogonal Wavelet Transform

Orthogonal Wavelet Transform Blind Equalization Algorithm Based on the Optimization of Artificial Fish Swarm Algorithm

2012 ◽  
Vol 198-199 ◽  
pp. 1399-1402
Author(s):  
Wei Huang ◽  
Ye Cai Guo
Keyword(s):  
Wavelet Transform ◽  
Convergence Rate ◽  
Blind Equalization ◽  
Weight Vector ◽  
Orthogonal Wavelet ◽  
Artificial Fish Swarm Algorithm ◽  
Equalization Algorithm ◽  
Artificial Fish Swarm ◽  
Swarm Algorithm ◽  
Orthogonal Wavelet Transform

According to disadvantages of big steady-state error, low convergence rate, and local convergence of traditional Constant Modulus blind equalization Algorithm (CMA), an orthogonal Wavelet Transform blind equalization Algorithm based on the optimization of Artificial Fish Swarm Algorithm(AFSA-WT-CMA) is proposed. In this proposed algorithm, the weight vector of the blind equalizer is regarded as artificial fish, the equalizer weight vector can be optimized via making full use of global search and information sharing mechanism of artificial fish school algorithm, the de-correlation ability of normalizing orthogonal wavelet transform. The computer simulations in underwater acoustic channels indicate that the proposed algorithm outperforms CMA and WT-CMA in convergence rate and mean square error.

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