scholarly journals Space-Time Joint Interference Cancellation Using Fuzzy-Inference-Based Adaptive Filtering Techniques in Frequency-Selective Multipath Channels

2006 ◽  
Vol 2006 (1) ◽  
Author(s):  
Chia-Chang Hu ◽  
Hsuan-Yu Lin ◽  
Yu-Fan Chen ◽  
Jyh-Horng Wen
Keyword(s):  
Adaptive Filtering ◽  
Interference Cancellation ◽  
Fuzzy Inference ◽  
Space Time ◽  
Multipath Channels ◽  
Frequency Selective ◽  
Filtering Techniques

FETAL ECG EXTRACTION USING WAVELET AND ADAPTIVE FILTERING TECHNIQUES

2016 ◽  
Vol 4 (2) ◽  
pp. 1
Author(s):  
PRASAD K. PURUSHOTHAM ◽  
ANURADHA B. ◽  
◽  
Keyword(s):  
Adaptive Filtering ◽  
Fetal Ecg ◽  
Filtering Techniques

scholarly journals Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 196
Author(s):  
Jun Lu ◽  
Qunfei Zhang ◽  
Wentao Shi ◽  
Lingling Zhang ◽  
Juan Shi
Keyword(s):  
Adaptive Filtering ◽  
Interference Cancellation ◽  
Impulsive Noise ◽  
Weight Vector ◽  
Filtering Algorithm ◽  
Convergence Performance ◽  
Simulation Results ◽  
Robust Adaptive ◽  
Arctangent Cost Function ◽  
Simultaneous Transmission

Self-interference (SI) is usually generated by the simultaneous transmission and reception in the same system, and the variable SI channel and impulsive noise make it difficult to eliminate. Therefore, this paper proposes an adaptive digital SI cancellation algorithm, which is an improved normalized sub-band adaptive filtering (NSAF) algorithm based on the sparsity of the SI channel and the arctangent cost function. The weight vector is hardly updated when the impulsive noise occurs, and the iteration error resulting from impulsive noise is significantly reduced. Another major factor affecting the performance of SI cancellation is the variable SI channel. To solve this problem, the sparsity of the SI channel is estimated with the estimation of the weight vector at each iteration, and it is used to adjust the weight vector. Then, the convergence performance and calculation complexity are analyzed theoretically. Simulation results indicate that the proposed algorithm has better performance than the referenced algorithms.

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