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Journal ArticleDOI

Quality Aware Compression of Multilead Electrocardiogram Signal using 2-mode Tucker Decomposition and Steganography

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TLDR
A quality controlled compression of multilead electrocardiogram (MECG) is proposed, based on tensor analysis, and implemented upon 3D beat tensor of MECG, and has provided superior result as compared to recently published works on M ECG data compression.
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This article is published in Biomedical Signal Processing and Control.The article was published on 2021-02-01. It has received 9 citations till now. The article focuses on the topics: Tucker decomposition & Data compression.

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Citations
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Journal ArticleDOI

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour

TL;DR: The Modified Sunflower Optimization (MSFO) algorithm is hybrid along with LBM which optimally selects the parameters that maximize the performance of tumour growth model.
Journal ArticleDOI

Deep neural network based missing data prediction of electrocardiogram signal using multiagent reinforcement learning

TL;DR: Bidirectional long short-term memory recurrent neural network based prediction of missing segment of ECG signal is accomplished, governed by reinforcement learning (RL) using multiagent, applicable to any single channel ECG signals.
Journal ArticleDOI

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour

TL;DR: In this paper , the Modified Sunflower Optimization (MSFO) algorithm is hybrid along with Lattice Boltzmann Method (LBM) which optimally selects the parameters that maximize the performance of tumour growth model.
Journal ArticleDOI

Monte Carlo Filter-Based Motion Artifact Removal From Electrocardiogram Signal for Real-Time Telecardiology System

TL;DR: In this article, the Monte Carlo filter (MCF)-based MA removal from single-channel ECG signal is proposed, assisting in real-time telecardiology systems, and the proposed algorithm was tested on the IEEE Signal Processing Cup Challenge 2015 ECG database and MIT-BIH arrythmia records, with an improvement of signal-to-noise ratio between 10 and 15 dB.
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Quality Guaranteed ECG Signal Compression Using Tunable-Q Wavelet Transform and Möbius Transform-Based AFD

TL;DR: In this paper, a combination of tunable-Q wavelet transform (TQWT) and adaptive Fourier decomposition (AFD) was used for ECG signal compression.
References
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Journal ArticleDOI

Tensor Decompositions for Signal Processing Applications From Two-way to Multiway Component Analysis

TL;DR: In this article, a comprehensive introduction to tensor decompositions is provided from a signal processing perspective, starting from the algebraic foundations, via basic Canonical Polyadic and Tucker decomposition, through to advanced cause-effect and multi-view data analysis schemes.
Journal ArticleDOI

A Self-Learning Particle Swarm Optimizer for Global Optimization Problems

TL;DR: A novel algorithm, called self-learning particle swarm optimizer (SLPSO), for global optimization problems, which can enable a particle to choose the optimal strategy according to its own local fitness landscape.
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Ventricular Fibrillation and Tachycardia Classification Using a Machine Learning Approach

TL;DR: A VF/VT classification algorithm using a machine learning method, a support vector machine, is proposed, and the results surpass those of current reported methods.
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A Review on Deep Learning Methods for ECG Arrhythmia Classification

TL;DR: A comprehensive review study on the recent DL methods applied to the ECG signal for the classification purposes, which showed high accuracy in correct classification of Atrial Fibrillation, Supraventricular ECTopic Beats, and Ventricular Ectopic Beats using the GRU, CNN, and LSTM, respectively.
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ECG data compression using truncated singular value decomposition

TL;DR: The results showed that truncated SVD method can provide an efficient coding with high-compression ratios and demonstrated the method as an effective technique for ECG data storage or signals transmission.
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