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Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation (Studies in Computational Intelligence)
Problem-Based Learning: A Didactic Strategy in the Teaching of System Simulation (Studies in Computational Intelligence)
This book describes and outlines the theoretical foundations of system simulation in teaching, and as a practical contribution to teaching-and-learning models. It presents various methodologies used in teaching, the goal being to solve real-life problems by creating simulation models and probability distributions that allow correlations to be...
Quantifying and Controlling Catastrophic Risks
Quantifying and Controlling Catastrophic Risks
The perception, assessment and management of risk are increasingly important core principles for determining the development of both policy and strategic responses to civil and environmental catastrophes. Whereas these principles were once confined to some areas of activity i.e. financial and insurance, they are now widely used in civil and...
Multidimensional Signal, Image, and Video Processing and Coding, Second Edition
Multidimensional Signal, Image, and Video Processing and Coding, Second Edition

This is a textbook for a first- or second-year graduate course for electrical and computer engineering (ECE) students in the area of digital image and video processing and coding. The course might be called Digital Image and Video Processing (DIVP) or some such, and has its heritage in the signal processing and communications areas of...

Statistics for Six Sigma Green Belts with Minitab and JMP
Statistics for Six Sigma Green Belts with Minitab and JMP

The only book on the market that provides a simple nonmathematical presentation of the statistics needed by Six Sigma Green Belts. Every concept is explained in plain English with a minimum of mathematical symbols. Includes real-world examples, step by step instructions and sample output for Minitab and JMP software as...

Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed...
Head First Data Analysis: A learner's guide to big numbers, statistics, and good decisions
Head First Data Analysis: A learner's guide to big numbers, statistics, and good decisions
Today, interpreting data is a critical decision-making factor for businesses and organizations. If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions,...
Performance Analysis of Transaction Processing Systems
Performance Analysis of Transaction Processing Systems
This book provides the tools necessary for predicting and improving the performance of real-time computing systems, with special attention given to the rapidly growing field of on-line traDsaCtion-processing (OLTP) systems. It is aimed at two audiences:

1. The system analyst who thorougbly understands the concepts of modem operating
...
Brownian Motion Calculus
Brownian Motion Calculus

Brownian Motion Calculus presents the basics of Stochastic Calculus with a focus on the valuation of financial derivatives. It is intended as an accessible introduction to the technical literature. The sequence of chapters starts with a description of Brownian motion, the random process which serves as the basic driver...

Mathematical Methods: For Students of Physics and Related Fields (Lecture Notes in Physics)
Mathematical Methods: For Students of Physics and Related Fields (Lecture Notes in Physics)
Intended to follow the usual introductory physics courses, this book has the unique feature of addressing the mathematical needs of sophomores and juniors in physics, engineering and other related fields. Many original, lucid, and relevant examples from the physical sciences, problems at the ends of chapters, and boxes to emphasize important...
Essentials of Mathematical Methods in Science and Engineering
Essentials of Mathematical Methods in Science and Engineering

A complete introduction to the multidisciplinary applications of mathematical methods

In order to work with varying levels of engineering and physics research, it is important to have a firm understanding of key mathematical concepts such as advanced calculus, differential equations, complex analysis, and introductory mathematical...

The Foundations of Statistics
The Foundations of Statistics
With the 1954 publication of his Foundations of Statistics, in which he proposed a basis that takes into account not only strictly objective and repetitive events, but also vagueness and interpersonal differences, Leonard J. Savage opened the greatest controversy in modern statistical thought. His theory of the...
Probability and Random Processes, Second Edition: With Applications to Signal Processing and Communications
Probability and Random Processes, Second Edition: With Applications to Signal Processing and Communications

Miller and Childers have focused on creating a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It is aimed at graduate students as well as practicing engineers, and includes unique chapters on...

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