Adaptation learning is a data-driven technique that adjusts its behavior based on the experience gained during data analysis. It plays an integral role in providing engineering solutions based on specific needs. Researchers have used the second-order statistics criterion for decades to conceptualize the optimality criteria using Shannon's and Rényi’s information-theoretic measures. Some gaps have been identified in this research work, and useful findings have been established using generalized information-theoretic measures, namely Tsallis entropy of order $\alpha$ and Kapur entropy of order $\alpha$ and type $\beta$, via the Parzen--Rosenblatt window. This work explores the problem of co... More >