Globally Optimal Algorithms for Transform Selection in Multiple-Transform Signal Compression

2016 ◽  
Author(s):  
Lucas Nissenbaum ◽  
Jae S. Lim
Keyword(s):  
Optimal Algorithms ◽  
Signal Compression

THE MODEL OF PULSE RADIATOR WITH OUTPUT SIGNAL COMPRESSION IN HELICALLY COILED DIELECTRIC WAVEGUIDE

2019 ◽  
Vol 78 (17) ◽  
pp. 1509-1520
Author(s):  
V. L. Pazynin ◽  
M. V. Maiboroda ◽  
A. A. Shmat'ko
Keyword(s):  
Output Signal ◽  
Dielectric Waveguide ◽  
Signal Compression

DOWNHOLE SIGNAL COMPRESSION AND SURFACE RECONSTRUCTION BASED ON DICTIONARY MACHINE LEARNING

2020 ◽  
Author(s):  
Jian Li ◽  
◽  
Bin Dai ◽  
Christopher M. Jones ◽  
Etienne M. Samson ◽  
...  
Keyword(s):  
Machine Learning ◽  
Surface Reconstruction ◽  
Signal Compression

scholarly journals The Effects of Compression on the Detection of Atrial Fibrillation in ECG Signals

2021 ◽  
Vol 11 (13) ◽  
pp. 5908
Author(s):  
Raquel Cervigón ◽  
Brian McGinley ◽  
Darren Craven ◽  
Martin Glavin ◽  
Edward Jones
Keyword(s):  
Atrial Fibrillation ◽  
Characteristic Curve ◽  
Set Partitioning ◽  
Constrained Systems ◽  
Battery Life ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Signal Compression ◽  
Ecg Signals ◽  
Cardiac Devices

Although Atrial Fibrillation (AF) is the most frequent cause of cardioembolic stroke, the arrhythmia remains underdiagnosed, as it is often asymptomatic or intermittent. Automated detection of AF in ECG signals is important for patients with implantable cardiac devices, pacemakers or Holter systems. Such resource-constrained systems often operate by transmitting signals to a central server where diagnostic decisions are made. In this context, ECG signal compression is being increasingly investigated and employed to increase battery life, and hence the storage and transmission efficiency of these devices. At the same time, the diagnostic accuracy of AF detection must be preserved. This paper investigates the effects of ECG signal compression on an entropy-based AF detection algorithm that monitors R-R interval regularity. The compression and AF detection algorithms were applied to signals from the MIT-BIH AF database. The accuracy of AF detection on reconstructed signals is evaluated under varying degrees of compression using the state-of-the-art Set Partitioning In Hierarchical Trees (SPIHT) compression algorithm. Results demonstrate that compression ratios (CR) of up to 90 can be obtained while maintaining a detection accuracy, expressed in terms of the area under the receiver operating characteristic curve, of at least 0.9. This highlights the potential for significant energy savings on devices that transmit/store ECG signals for AF detection applications, while preserving the diagnostic integrity of the signals, and hence the detection performance.

scholarly journals Optimal Algorithms for Multiwinner Elections and the Chamberlin-Courant Rule

2021 ◽  
Author(s):  
Kamesh Munagala ◽  
Zeyu Shen ◽  
Kangning Wang
Keyword(s):  
Optimal Algorithms

scholarly journals DCAECSCS: Divide and Conquer Algorithm Based Electro Cardiac Signal Compression Scheme

2021 ◽  
Vol 1084 (1) ◽  
pp. 012008
Author(s):  
Srinivas Bachu ◽  
Thelapolu Shalini ◽  
Naluguru Udaya Kumar
Keyword(s):  
Divide And Conquer ◽  
Signal Compression ◽  
Compression Scheme ◽  
Divide And Conquer Algorithm

Recurrent neural network predictors for EEG signal compression

2002 ◽  
Author(s):  
F. Bartolini ◽  
V. Cappellini ◽  
S. Nerozzi ◽  
A. Mecocci
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Eeg Signal ◽  
Signal Compression
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