English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Noise Reduction with less computational time and resources of the signal is a major requirement in signal processing. In the real-world scenario, Electromyography (EMG) signals often affect by various noises. The EMG signal requires noise reduction to obtain an accurate diagnosis process. In this study, Ladner-Fischer Adder (LFA) based Median Filter (MF) architecture is used to remove the noise from the EMG signal. The noise evaluation process is included in this proposed method to eliminate the flicker noise from the signal. The proposed LFA-MF method is simulated in the Cadence RTL compiler and Xilinx tool to evaluate the performance in terms of power, delay and Look Up Table (LUT). The objective of this work is to design the noise detection structure to avoid the denoising process for all the samples. This helps to reduce the hardware resources of the entire median filter architecture. The simulation result of LFA-MF architecture showed that it has lower power consumption and delay in noise reduction. The LFAMF architecture has a power consumption of 1006548 nW in 16-bit sample width, while the existing method has 1537940 nW power consumption.

VLSI Implementation of LFA based Median Filter with Noise Detection Architecture for EMG Denoising