Mathematics and Computer Science: Contemporary Developments Vol. 8

This book covers key areas of mathematics and computer science. The contributions by the authors include compression algorithms, filtered images, mean square error, signal-to-noise ratio, JPEG algorithm, compression quality, structural similarity index, Steiner decomposition number, corona product, remote sensing images, DAC improvements, Lossy compression, discrete atomic compression, investment portfolio selection, multivariate exponential weighted moving average, dynamic conditional correlation model, mean-variance models, sampling distribution, bootstrap confidence interval, Kvalseth’s standard deviation, asymptotic confidence interval, asymptotic standard error, subset selection, probability of correct selection, probability distribution function, one stage and two stage selection procedure, breast cancer, machine learning algorithms, k-means, and k-nearest neighbours, naïve bayes, prime numbers, natural numbers; function of Riemann. This book contains various materials suitable for students, researchers, and academicians in the fields of mathematics and computer science.