The partitional clustering concept started with K-means algorithm which was published in
1957. Since then many classical partitional clustering algorithms have been reported based …

Wireless sensor networks (WSNs) are becoming increasingly important, providing pervasive
real-time applications that have been used to enhance smart environments in various fields …

The substantial increase in the usage of wireless sensor networks (WSNs) encourages to
develop data clustering in event monitoring applications. Many centralized algorithms with …

Traditional K-Means based distributed clustering used in wireless sensor networks has
limitation of getting stuck into local minima, thus many times results in giving inaccurate …

Direction of Arrival (DOA) estimation by Maximum Likelihood (ML) method has been popular
among researchers due to its effective performance. However, its practical applications are …

In this paper, event related potential (ERP) generated due to hand movement is detected
through the adaptive noise canceller (ANC) from the electroencephalogram (EEG) signals …

In wireless sensor networks (WSNs), distributed algorithms are used to estimate desired
parameters for minimizing the communication overheads and make the network energy …

Multi-objective clustering algorithms have superiority over its single objective counterparts
as they include additional knowledge on properties of data in the form of objectives to …

In this paper, we propose a distributed gradient algorithm for received signal strength based
target localization using only quantized data. The Maximum Likelihood of the Quantized …

Passive localization and classification algorithms for mixed near-field and far-field sources
have mainly been investigated for antenna arrays with regular or symmetrical geometry …