• Danvir Mandal
• Shyam S. Pattnaik

In this paper, existing machine learning techniques for signal processing are reviewed and presented. The machine learning techniques used in processing of signals for detection of stress, detection of network intrusion, design of antenna, QRS detection and quantification and recognition of gestures are discussed and presented. The use of the machine learning in signal processing has reinforced its need in futuristic smart machines or robots for domestic and industrial purposes which validates their importance in current scenario.

machine learning, signal processing, smart machines

"Machine Learning Approaches for Signal Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 10, page no.438-440, October 2018, Available :http://www.jetir.org/papers/JETIRDQ06063.pdf

"Machine Learning Approaches for Signal Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 10, page no. pp438-440, October 2018, Available at : http://www.jetir.org/papers/JETIRDQ06063.pdf