The Kalman filter variants extended Kalman filter (EKF) and error-state Kalman filter (ESKF)
are widely used in underwater multi-sensor fusion applications for localization and …

The Least Mean Square (LMS) algorithm inherits slow convergence due to its dependency
on the eigenvalue spread of the input correlation matrix. In this work, we resolve this problem …

In this research, we propose a novel algorithm for learning of the recurrent neural networks
called as the fractional back-propagation through time (FBPTT). Considering the potential of …

The ability of the underwater vehicle to determine its precise position is vital to completing a
mission successfully. Multi-sensor fusion methods for underwater vehicle positioning are …

In this letter, we propose techniques for joint transmit and receive beamforming in downlink
multi-user MIMO systems under Rayleigh fading channels using knowledge of the second-…

The least-mean-fourth (LMF) algorithm is known for its fast convergence and lower steady
state error, especially in sub-Gaussian noise environments. Recent work on normalised …

Recursive least-squares (RLS) algorithms are widely used in many applications, such as
real-time signal processing, control and communications. In some applications, regularization …

This paper characterizes the performance metrics of MU-MIMO systems under Rayleigh
fading channels in the presence of both cochannel interference and additive noise with …

Effective sharing of the communication channel among many users, or multiple access (MA)
techniques, can play a vital role in meeting the diverse demands of low latency, high …

Salt-tolerant grasses of warm sub-tropical ecosystems differ in their distribution patterns with
respect to salinity and moisture regimes. Experiments were conducted on CO 2 fixation and …