GPS Synchronization Architecture for Dynamic Signal Acquisition

2008 ◽  
Author(s):  
Jack Arnold ◽  
Kurt Veggeberg
Keyword(s):  
Signal Acquisition ◽  
Dynamic Signal ◽  
Gps Synchronization

An Engine Dynamic Signal Testing System Based on Virtual Instrument Technology

2009 ◽  
Vol 16-19 ◽  
pp. 193-198 ◽  
Author(s):  
Ying Ji Liu ◽  
Feng Tian Cai ◽  
Wei Zhou ◽  
Xue Li Zhang ◽  
Tian Xia Zhang
Keyword(s):  
Virtual Instrument ◽  
High Speed ◽  
Computer Software ◽  
Digital Signal ◽  
Test System ◽  
Structure Design ◽  
Signal Acquisition ◽  
Instrument Technology ◽  
Dynamic Signal ◽  
Engine Dynamic

Aimed at the requirements of engine experimental research，a test system of engine dynamic signal was developed based on virtual instrument technology. The integral structure design of the system was given, the hardware is composed of sensors, signal conditioning module, high-speed data acquisition card and portable computer; the host computer software was developed with DASYLab, a virtual instrumentation tool. Its essential is to make good use of computer to achieve and extend functions of traditional instruments, by comprehensively using technologies of computer, digital signal processing, standard bus and software engineering method, functions of continuous multi channel sampling and multi type signal acquisition, and processing analysis were realized. The field test shows the system works reliably, development and application of this system can provide detailed experiment data and a new way in the field of engine power detection.

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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