Real-Time DSP for Adaptive FIR Filters Based on LMS Algorithm

2019 ◽  
Author(s):  
Masahiro Kikuta ◽  
Shohei Beppu ◽  
Tomoyuki Nagai ◽  
Yasuo Saito ◽  
Takehiro Tsuritani ◽  
...  
Keyword(s):  
Real Time ◽  
Lms Algorithm ◽  
Fir Filters ◽  
Adaptive Fir

Neural network for real-time synthesis of FIR filters

1989 ◽  
Vol 25 (17) ◽  
pp. 1199 ◽  
Author(s):  
G. Martinelli ◽  
R. Perfetti
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Fir Filters

An Accelerator for Real-Time Digital Signal Processing with Microprocessors

1987 ◽  
Vol 24 (1) ◽  
pp. 65-72
Author(s):  
C. Ward
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Real Time ◽  
Digital Signal ◽  
Fir Filters ◽  
Minimal Cost ◽  
Hands On

An accelerator consisting of a fast digital multiplier and A/D and D/A converters is designed for the BBC microcomputer. The circuit enables ‘hands-on’ experience of digital signal processing to be provided at minimal cost. Examples of implementations of FIR filters and an autocorrelation algorithm are provided.

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.

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