Combined GPS L1C/A and L2C signal acquisition architectures leveraging differential combination

2014 ◽  
Vol 50 (4) ◽  
pp. 3212-3229 ◽  
Author(s):  
Tung Ta ◽  
Marco Pini ◽  
Letizia Presti
Keyword(s):  
Signal Acquisition ◽  
L2c Signal

Partial Differential Postcorrelation Processing for GPS L2C Signal Acquisition

2012 ◽  
Vol 48 (2) ◽  
pp. 1287-1305 ◽  
Author(s):  
Tung Hai Ta ◽  
Sana U. Qaisar ◽  
Andrew G. Dempster ◽  
Fabio Dovis
Keyword(s):  
Signal Acquisition ◽  
Partial Differential ◽  
L2c Signal

GPS L1, L2C Signal Acquisition Performance of GPS Software Receiver with respect to Pseudolite Pulsing Scheme

2012 ◽  
Vol 16 (1) ◽  
pp. 16-26
Author(s):  
Keum-Cheol Kwon ◽  
Cheol-Kwan Yand ◽  
Duk-Sun Shim ◽  
Tae-Sang Chung ◽  
Chand-Don Kee
Keyword(s):  
Signal Acquisition ◽  
Software Receiver ◽  
Acquisition Performance ◽  
L2c Signal

A New Robust GPS Satellite Signal Acquisition Using Lifting Wavelet

2005 ◽  
Vol 63 (5) ◽  
pp. 389-403 ◽  
Author(s):  
D. Djebouri ◽  
A. Djebbari ◽  
M. Djebbouri
Keyword(s):  
Signal Acquisition ◽  
Satellite Signal ◽  
Lifting Wavelet

HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION

2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach
Keyword(s):  
Neural Network ◽  
Signal Acquisition ◽  
Heart Murmur ◽  
Classification Techniques ◽  
Classification Schemes ◽  
Neural Network Classification ◽  
Nonlinear Classification ◽  
Processing Step ◽  
System Characterization ◽  
Hybrid Classification

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.

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