In this paper, a novel augmented complex-valued least-mean kurtosis (ACLMK) algorithm is
proposed for processing complex-valued signals. The negated kurtosis of the complex …

In this paper, a novel augmented complex-valued normalized subband adaptive filter
(ACNSAF) algorithm is proposed for processing the noncircular complex-valued signals …

In this work, a new class of stochastic gradient algorithm is developed based on q-calculus.
Unlike the existing q-LMS algorithm, the proposed approach fully utilizes the concept of q …

In this paper, we propose an adaptive framework for the variable power of the fractional least
mean square (FLMS) algorithm. The proposed algorithm named as robust variable power …

Augmented adaptive filters provide superior performance over their conventional
counterparts when dealing with noncircular complex signals. However, the performance of …

In this paper, kurtosis-based complex-valued real-time recurrent learning (KCRTRL) and
kurtosis-based augmented CRTRL (KACRTRL) algorithms are proposed for training fully …

In this paper, we study the problem of distributed bias-compensated recursive least-squares
(BCRLS) estimation over multi-agent networks, where the agents collaborate to estimate a …

In this study, the authors propose a novel component‐wise variable step‐size (CVSS)
diffusion distributed algorithm for estimating a specific parameter over sensor networks. The …

Spectrum sensing is a significant issue in cognitive radio networks which enables estimation
of the frequency spectrum and hence provides frequency reuse. In the large‐scale cognitive …

This paper introduces a novel adaptive convex combination (ACC) of the complex-valued
least mean kurtosis (CLMK) and augmented CLMK (ACLMK) algorithms by inspiring their …