Sparsity-induced kernel adaptive filters have emerged as a promising candidate for a
nonlinear sparse system identification (SSI) problem. The existing zero-attracting kernel …

Low complexity and ease of implementation provided by zero-attraction-based least mean
square (LMS) algorithms have made them popular candidates for sparse system …

Supervisory Control and Data Acquisition (SCADA) systems are vulnerable to traditional
cyber-attacks, such as man-in-the-middle, denial of service, eavesdropping, and …

We have been witnessed a growing research activity to advance new strategies to detect
and exploit underlying sparsity in the parameters of physical models. In many cases, the …

In this paper, a quadral-duty digital pulse width modulation (QDPWM) technique-based low-
cost hardware architecture for brushless DC (BLDC) motor drive is proposed. The proposed …

Linear-in-the-parameters nonlinear controllers are widely used for active noise cancellation
(ANC) in the presence of nonlinearities in the system. However, the performance of such …

This paper proposes ReAdapt–a reconfigurable datapath architecture for scaling the energy-
quality trade-off of adaptive filtering at runtime. The ReAdapt can dynamically select four …

Heart disease is identified to be the major reason for death worldwide as recorded by World
Health Organization. The use of cardiac pacemakers was estimated to be around 1.14 …

A dual‐duty digital pulse‐width modulation (DDPWM) technique‐based cost‐effective
control hardware architecture for brushless DC (BLDC) motor drive is reported in this paper …

Sparsity-aware kernel adaptive filtering algorithms using maximum correntropy criterion
(MCC) and maximum Versoria criterion (MVC) have emerged as a promising candidate for …