Publication Type:

Conference Paper

Source:

Proceeding of the IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014, Dr. N. G. P. Institute of Technology, Coimbatore (2014)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910625150&partnerID=40&md5=8e6b657398eb2fd84865a72031c31ea6

Abstract:

This paper gives an insight about how to create classifier plug-ins (signal processing blocks) using hard-code input for GNU Radio Companion (GRC). GNU Radio Companion is an open source Visual programming language for any real time signal processing applications. At present there is no classifier block available inside this GRC tool. Here we are introducing a low cost classifier which utilizes the basic machine learning algorithms:linear regression and logistic regression. The creation of classifier plug-ins in an open source software enables easy manipulation of real time classification problems during the transmission and reception of signals in Software Defined Radios. So this workdescribes the development of signal processing block that can be done by changing the Python code and C++ codes of the 'gr-modtool' package. It is highly cost effective and with great potential since GNU Radio software is open source and free. © 2014 IEEE.

Notes:

cited By 0; Conference of 2014 IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014 ; Conference Date: 6 March 2014 Through 8 March 2014; Conference Code:108513

Cite this Research Publication

R. Anil, Danymol, R., Gawande, H., and Gandhiraj, R., “Machine learning plug-ins for GNU Radio Companion”, in Proceeding of the IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014, Dr. N. G. P. Institute of Technology, Coimbatore, 2014.