INEQUALITIES IN ANALYSIS AND PROBABILITY

Targeted at graduate students and researchers, this book delves into classical inequalities within vector and functional spaces, emphasizing their applications in probability. It introduces innovative extensions of analytical inequalities, offering sharper bounds and generalizations applicable to random variables, martingales, and transformed Brownian motions. The detailed proofs of these new results enhance understanding and provide a comprehensive resource for those with a foundational knowledge of Probability and Integration Theory.