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Journals / Turkish Journal of Electrical Engineering and Computer Science / 2011 / Cilt: 19 - Sayı: 1

Neuro-fuzzy soft-switching hybrid filter for impulsive noisy environments

Şaban ÖZER
Hasan ZORLU
Pages
73–85
Publication Date
2011-01-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the simulation results; the proposed hybrid filter has better performance than the adaptive FIR, WMy, and WMd filters, and has the ability of effectively suppressing the impulsive noisy environments.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, a new soft-switching hybrid filter based on a neuro-fuzzy network for impulsive noisy environments is proposed.
📊
Key Findings & Data:Performance of the hybrid filter was tested in a-stable noisy situations and compared with adaptive FIR, WMy, and weighted median (WMd) filter performances.
💡
Conclusion & Impact:According to the simulation results; the proposed hybrid filter has better performance than the adaptive FIR, WMy, and WMd filters, and has the ability of effectively suppressing the impulsive noisy environments.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:a-stable noise · nonlinear filtering · myriad filter

Abstract

In this study, a new soft-switching hybrid filter based on a neuro-fuzzy network for impulsive noisy environments is proposed. The hybrid filter was built by combining an adaptive finite impulse response (FIR) filter, an adaptive weighted myriad (WMy) filter, and a soft-switching mechanism based on a neuro-fuzzy (NF) network. Performance of the hybrid filter was tested in a-stable noisy situations and compared with adaptive FIR, WMy, and weighted median (WMd) filter performances. According to the simulation results; the proposed hybrid filter has better performance than the adaptive FIR, WMy, and WMd filters, and has the ability of effectively suppressing the impulsive noisy environments.

Özet

In this study, a new soft-switching hybrid filter based on a neuro-fuzzy network for impulsive noisy environments is proposed. The hybrid filter was built by combining an adaptive finite impulse response (FIR) filter, an adaptive weighted myriad (WMy) filter, and a soft-switching mechanism based on a neuro-fuzzy (NF) network. Performance of the hybrid filter was tested in a-stable noisy situations and compared with adaptive FIR, WMy, and weighted median (WMd) filter performances. According to the simulation results; the proposed hybrid filter has better performance than the adaptive FIR, WMy, and WMd filters, and has the ability of effectively suppressing the impulsive noisy environments.

🔖

Cite This Article

ÖZER, Ş., ZORLU, H. (2011). Neuro-fuzzy soft-switching hybrid filter for impulsive noisy environments. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 19 - Sayı: 1, 73–85. https://ajindex.com/articles/188874

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