A new Delayless subband adaptive filter based on Discrete Cosine Harmonic Wavelet Transform (CHWT)

2010 ◽  
Author(s):  
S. V. Narasimhan ◽  
S. Veena
Keyword(s):  
Wavelet Transform ◽  
Adaptive Filter ◽  
Harmonic Wavelet ◽  
Subband Adaptive Filter

The Design of a Wavelet-Based Neural Network Adaptive Filter

2013 ◽  
Vol 860-863 ◽  
pp. 2791-2795
Author(s):  
Qian Xiao ◽  
Yu Shan Jiang ◽  
Ru Zheng Cui
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Real Time ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Distributed Storage ◽  
Hopfield Neural Network ◽  
Lms Algorithm ◽  
The Neural Network ◽  
Simulation Results

Aiming at the large calculation workload of adaptive algorithm in adaptive filter based on wavelet transform, affecting the filtering speed, a wavelet-based neural network adaptive filter is constructed in this paper. Since the neural network has the ability of distributed storage and fast self-evolution, use Hopfield neural network to implement adaptive filter LMS algorithm in this filter so as to improve the speed of operation. The simulation results prove that, the new filter can achieve rapid real-time denoising.

scholarly journals An Effective Method to Denoiseeeg, ECG and PPG Signals based on Meyer Wavelet Transform

2018 ◽  
Vol 7 (3.34) ◽  
pp. 678
Author(s):  
P Thamarai ◽  
Dr K.Adalarasu
Keyword(s):  
Wavelet Transform ◽  
Adaptive Filter ◽  
Wavelet Decomposition ◽  
Motion Artifact ◽  
Signal Quality ◽  
Frequency Noise ◽  
Meyer Wavelet ◽  
Discrete Transform ◽  
Reference Input

In this analysis, the prevailing role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the constant and the discrete transform are considered in turn.A Wavelet denoising is functional on the original signal to eradicate high frequency noise, and then a process based on Meyer wavelet transform combined with adaptive filter is functional to eradicate the motion artifact. This approach uses Meyer Wavelet decomposition to extract the motion artifact, which is subsequently utilized as the reference input of an adaptive filter for noise cancellation. The technique diminishes the overhead of the circuit because it does not need a separate collection of reference input signal which link to noise. Testing results illustrate that this approach can efficiently remove motion artifact and make better the signal quality. 

Sign in / Sign up

Export Citation Format

Share Document