The development of a theory that characterize the behavior of real-world Random Signals and Processes using standard Probability Theory.

This textbook is intended for introductory statistics courses being taken by students at two– and four–year colleges who are majoring in fields other than math or engineering.The book focuses on applications of statistical knowledge rather than the theory behind it.

The rationale of teaching Basic mathematics is that it plays the role of filling up gaps that the student teacher could be having from secondary school mathematics.

A study in the application of algebraic algorithms from incomplete projection data in the reconstruction of images.

A newest approach to string theory, although the older approaches are continuously developing new twists and improvements.

A brief insight on applications of recurrent neural networks to general optimization problems in diverse fields such as mechanical, electrical and industrial engineering, operational research, management sciences, computer sciences, system analysis, economics, medical sciences, manufacturing, social and public planning and image processing.

The application of Greedy Type Bases to a vector space with a metric that allows the computation of vector length and distance between vectors that a Cauchy sequence of vectors always converges to a well defined limit in the space.

This course is a short series of lectures on Introductory Statistics. Topics covered are listed in the Table of Contents. The notes were prepared by Ewa Paszek and Marek Kimmel. The development of this course has been supported by NSF 0203396 grant.

A study in the exploration of multivariate survival data and its competing risk for classification.

Fundamentals of Mathematics is a work text that covers the traditional topics studied in a modern prealgebra course, as well as topics of estimation, elementary analytic geometry, and introductory algebra.