2012 - IEEE Fellow For contributions to computational intelligence, learning systems, and nonlinear modelling
His main research concerns Artificial intelligence, Artificial neural network, Wireless sensor network, Anomaly detection and Heart rate variability. Marimuthu Palaniswami has researched Artificial intelligence in several fields, including Computational complexity theory, Machine learning and Pattern recognition. His Artificial neural network study combines topics from a wide range of disciplines, such as Robustness, Control theory, Robust control and Adaptive control.
The various areas that Marimuthu Palaniswami examines in his Wireless sensor network study include Sensor node, Adaptation, Key and Base station. The concepts of his Key study are interwoven with issues in Smart environment, Reduction, Energy, Statistical parameter and Web of Things. His studies in Heart rate variability integrate themes in fields like Electrocardiography and Cardiology.
His primary areas of study are Artificial intelligence, Pattern recognition, Wireless sensor network, Support vector machine and Internal medicine. His Artificial intelligence research incorporates elements of Machine learning, Computer vision and Signal processing. His work in Pattern recognition addresses subjects such as Speech recognition, which are connected to disciplines such as Independent component analysis.
His Wireless sensor network research is included under the broader classification of Computer network. His biological study spans a wide range of topics, including Fetus and Cardiology. His work carried out in the field of Heart rate variability brings together such families of science as Entropy and Statistics.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Cluster analysis, Entropy and Signal processing. His research integrates issues of Machine learning, Photoplethysmogram, Computer vision and Heart rate in his study of Artificial intelligence. His Cluster analysis research includes themes of Visualization, Anomaly detection, Data mining and Random projection.
His research investigates the link between Anomaly detection and topics such as Real-time computing that cross with problems in Wireless sensor network. His Wireless sensor network study is focused on Computer network in general. His research in Entropy intersects with topics in Heart rate variability and Nonlinear system.
Marimuthu Palaniswami mostly deals with Artificial intelligence, Cluster analysis, Pattern recognition, Data mining and Random projection. In his study, Hardware architecture, Variety and Load forecasting is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence. His Cluster analysis research is multidisciplinary, relying on both Anomaly detection, Computation, Partition, Minimum spanning tree and Big data.
In his research on the topic of Anomaly detection, Wireless sensor network is strongly related with Real-time computing. His Pattern recognition study combines topics in areas such as Hilbert–Huang transform, Photoplethysmogram, Noise and Respiratory rate. His study in Data mining is interdisciplinary in nature, drawing from both Smart meter, Scalability, Tree and Trajectory.
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Internet of Things (IoT): A vision, architectural elements, and future directions
Jayavardhana Gubbi;Rajkumar Buyya;Slaven Marusic;Marimuthu Palaniswami.
Future Generation Computer Systems (2013)
An Information Framework for Creating a Smart City Through Internet of Things
Jiong Jin;Jayavardhana Gubbi;Slaven Marusic;Marimuthu Palaniswami.
IEEE Internet of Things Journal (2014)
Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability
M. Brennan;M. Palaniswami;P. Kamen.
IEEE Transactions on Biomedical Engineering (2001)
Support vector machines for automated gait classification
R.K. Begg;M. Palaniswami;B. Owen.
IEEE Transactions on Biomedical Engineering (2005)
Fuzzy c-Means Algorithms for Very Large Data
T. C. Havens;J. C. Bezdek;C. Leckie;L. O. Hall.
IEEE Transactions on Fuzzy Systems (2012)
Energy-efficient link-layer jamming attacks against wireless sensor network MAC protocols
Yee Wei Law;Marimuthu Palaniswami;Lodewijk Van Hoesel;Jeroen Doumen.
ACM Transactions on Sensor Networks (2009)
Support Vector Machines for Automated Recognition of Obstructive Sleep Apnea Syndrome From ECG Recordings
A.H. Khandoker;M. Palaniswami;C.K. Karmakar.
international conference of the ieee engineering in medicine and biology society (2009)
Distributed Anomaly Detection in Wireless Sensor Networks
Sutharshan Rajasegarar;Christopher Leckie;Marimuthu Palaniswami;James Bezdek.
international conference on conceptual structures (2006)
Intrusion Detection for Routing Attacks in Sensor Networks
Chong Eik Loo;Mun Yong Ng;Christopher Leckie;Marimuthu Palaniswami.
International Journal of Distributed Sensor Networks (2006)
Anomaly detection in wireless sensor networks
S. Rajasegarar;C. Leckie;M. Palaniswami.
IEEE Wireless Communications (2008)
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