Computational Methods for Data Analysis

This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are then used for the processing of real-life data using Matlab.

Auteur

Yeliz Karaca, University of Massachusetts, Worcester MA, USA; Carlo Cattani, University of Tuscia, Viterbo, Italy.