Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
489671 | Procedia Computer Science | 2015 | 8 Pages |
Abstract
In this paper, we have implemented an adaptive noise canceller (ANC) for ECG signals with the help of Modified Particle Swarm Optimization (MPSO). Implementing MPSO on ANC provides better performance than any other optimization technique used to enhance the ECG signal. In this work, the various modes of MPSO for finding fidelity parameters like signal to noise ratio (SNR), peak reconstruction error (PRE) and mean square error (MSE) have been evaluated. Our simulation results show that 19% improvement in SNR, 91% decrease in peak reconstruction error, and 99% reduction in mean square error can be achieved using proposed algorithm over the conventional PSO technique.
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