This textbook is ideal for an undergraduate introduction to probability, with a calculus prerequisite. It is based on a course that the author has taught many times at Berkeley. The text's overall style is informal, but all results are stated precisely, and most are proved. Understanding is developed through intuitive explanations and...

This text makes extensive use of graphing calculators, and worked examples often included an alternative solution using the graphing calculator. However, pencil-and-paper worked examples introduce the concepts so that students will understand the mathematics that the technology uses. This approach also ensure that students who do not have...

The Monte Carlo method is a numerical method of solving mathematical problems through random sampling. As a universal numerical technique, the method became possible only with the advent of computers, and its application continues to expand with each new computer generation. A Primer for the Monte Carlo Method demonstrates how practical...

Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function.

This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers....

As optical character recognition (OCR) begins to find applications ranging from store checkout scanners to money-changing machines and postal system automation, it has become one of the most dynamic areas in information science today. Yet few volumes explore this data-oriented process without relying heavily on mathematical background...

"Fixed-Point Algorithms for Inverse Problems in Science and Engineering" presents some of the most recent work from top-notch researchers studying projection and other first-order fixed-point algorithms in several areas of mathematics and the applied sciences. The material presented provides a survey of the state-of-the-art...