Research Analysis of Signals using Machine Learning Techniques
Navpreet Kaur1, Inderdeep Kaur Aulakh2
1Er. Navpreet Kaur, Assistant Professor in the Department of Computer Science, University Institute of Engineering, Chandigarh University, Punjab, India.
2Dr. Inderdeep Kaur Aulakh, Associate Professor in the Department of Information Technology, University Institute of Engineering and Technology, Panjab University, Chandigarh, India.
Manuscript received on 12 August 2019. | Revised Manuscript received on 18 August 2019. | Manuscript published on 30 September 2019. | PP: 8503-8508 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5556098319/2019©BEIESP | DOI: 10.35940/ijrte.C5556.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Enhancements in installed microchips, low-control simple and computerized hardware, and radio correspondences have empowered the improvement of little and low-estimated sensor hubs or nodes (SNs) that made remote sensor systems, WSNs one of the promising advances amid the previous decade. Over the most recent couple of years wireless sensor systems (WSNs) have drawn the consideration of the exploration network, driven by an abundance of hypothetical and viable difficulties. This dynamic research in WSNs investigated different new applications empowered by bigger scale systems of sensor hubs fit for detecting data from nature, process the detected information and transmits it to the remote area. 
Keywords: WSN, SN, DT, SVM
Scope of the Article: Machine Learning