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Advanced Digital Signal Processing And Noise Reduction

TLDR
Thank you very much for reading advanced digital signal processing and noise reduction, maybe you have knowledge that, people have search hundreds of times for their chosen books, but end up in infectious downloads, instead they are facing with some infectious bugs inside their laptop.
Abstract
Thank you very much for reading advanced digital signal processing and noise reduction. Maybe you have knowledge that, people have search hundreds times for their chosen books like this advanced digital signal processing and noise reduction, but end up in infectious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their laptop.

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Citations
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Journal ArticleDOI

A review of predictive coding algorithms.

TL;DR: Five predictive coding algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive codes that have been proposed to model cortical function.
Posted Content

Revisiting Graph Neural Networks: All We Have is Low-Pass Filters

TL;DR: The results indicate that graph neural networks only perform low-pass filtering on feature vectors and do not have the non-linear manifold learning property, and some insights on GCN-based graph neural network design are proposed.
Journal ArticleDOI

Optimal Signal Quality Index for Photoplethysmogram Signals.

TL;DR: The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F1 scores of 86.0%, 87.2%, and 79.1%, respectively.
Journal ArticleDOI

Statistical analysis of Haralick texture features to discriminate lung abnormalities

TL;DR: The proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.
Journal ArticleDOI

LMS Adaptive Filters for Noise Cancellation: A Review

TL;DR: Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation.
References
More filters
Journal ArticleDOI

A review of predictive coding algorithms.

TL;DR: Five predictive coding algorithms are covered: linear predictive coding which has a long and influential history in the signal processing literature; the first neuroscience-related application of predictive coding to explaining the function of the retina; and three versions of predictive codes that have been proposed to model cortical function.
Posted Content

Revisiting Graph Neural Networks: All We Have is Low-Pass Filters

TL;DR: The results indicate that graph neural networks only perform low-pass filtering on feature vectors and do not have the non-linear manifold learning property, and some insights on GCN-based graph neural network design are proposed.
Journal ArticleDOI

Optimal Signal Quality Index for Photoplethysmogram Signals.

TL;DR: The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F1 scores of 86.0%, 87.2%, and 79.1%, respectively.
Journal ArticleDOI

Statistical analysis of Haralick texture features to discriminate lung abnormalities

TL;DR: The proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.
Journal ArticleDOI

LMS Adaptive Filters for Noise Cancellation: A Review

TL;DR: Algorithms such as LMS and RLS proves to be vital in the noise cancellation are reviewed including principle and recent modifications to increase the convergence rate and reduce the computational complexity for future implementation.