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<P><EM>Introduction to Chemical Engineering Analysis Using Mathematica, Second Edition</EM> reviews the processes and designs used to manufacture, use, and dispose of chemical products using Mathematica, one of the most powerful mathematical software...
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<EM>Advanced Mathematics for Engineering Students: The Essential Toolbox</EM> provides a concise treatment for applied mathematics. Derived from two semester advanced mathematics courses at the author’s university, the book delivers the mathematical ...
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<EM>Python Programming and Numerical Methods: A Guide for Engineers and Scientists</EM> introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational proble...
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<P><EM>Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, </EM>uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedure...
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<P><EM>Calculus for Engineering Students: Fundamentals, Real Problems, and Computers</EM> insists that mathematics cannot be separated from chemistry, mechanics, electricity, electronics, automation, and other disciplines. It emphasizes interdiscipli...
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<P><EM>Liengme’s Guide to Excel 2016 for Scientists and Engineers</EM> is a completely updated guide for students, scientists, and engineers who want to use Microsoft Excel 2016 to its full potential, whether you’re using a PC or a Mac. Electronic sp...
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<P><EM>Introduction to Algorithms for Data Mining and Machine Learning </EM>introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematic...
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<P><EM>Statistics for Biomedical Engineers and Scientists: How to Analyze and Visualize Data</EM> provides an intuitive understanding of the concepts of basic statistics, with a focus on solving biomedical problems. Readers will learn how to understa...
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<P><EM>Model Engineering for Simulation</EM> provides a systematic introduction to the implementation of generic, normalized and quantifiable modeling and simulation using DEVS formalism. It describes key technologies relating to model lifecycle mana...
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<P>The fourth edition of <I>Numerical Methods Using MATLAB</I>® provides a clear and rigorous introduction to a wide range of numerical methods that have practical applications. The authors’ approach is to integrate MATLAB® with numerical analysis in...
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<P><EM>Algebraic and Combinatorial Computational Biology</EM> introduces students and researchers to a panorama of powerful and current methods for mathematical problemsolving in modern computational biology. Presented in a modular format, each topi...
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<P><EM>MATLAB: A Practical Introduction to Programming and Problem Solving</EM>, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and builtin functions to easily exploit MATLAB's extensive capabili...
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<P><EM>Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition,</EM> continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and wor...
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<P><EM>Finite Element Analysis Applications: A Systematic and Practical Approach</EM> strikes a solid balance between more traditional FEA textbooks that focus primarily on theory, and the software specific guidebooks that help teach students and pro...
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<P><EM>Machine Learning: A ConstraintBased Approach</EM> provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines...
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<P><EM>The Finite Element Method in Engineering, Sixth Edition,</EM> provides a thorough grounding in the mathematical principles behind the Finite Element Analysis technique—an analytical engineering tool originated in the 1960's by the aerospace an...
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<P><EM>Mathematics for Neuroscientists, Second Edition, </EM>presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons...
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<P><EM>An Introduction to the Mathematics of Finance: A Deterministic Approach, Second edition,</EM> offers a highly illustrated introduction to mathematical finance, with a special emphasis on interest rates. This revision of the McCutcheonScott&nb...
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<P><EM>Numerical Methods for Partial Differential Equations: Finite Difference and Finite Volume Methods</EM> focuses on two popular deterministic methods for solving partial differential equations (PDEs), namely finite difference and finite volume m...
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<P><EM>Fundamentals of Technical Mathematics</EM> introduces key, applied mathematics for engineering technologists and technicians. Through a simple, engaging approach, the book reviews basic mathematics, including whole numbers, fractions, mixed nu...
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<P><EM>Risk Neutral Pricing and Financial Mathematics: A Primer</EM> provides a foundation to financial mathematics for those whose undergraduate quantitative preparation does not extend beyond calculus, statistics, and linear math. It covers a broad...
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<P>This selfcontained module for independent study covers the subjects most often needed by nonmathematics graduates, such as fundamental calculus, linear algebra, probability, and basic numerical methods. The easilyunderstandable text of <EM>Intr...
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<P>Written by experts in both mathematics and biology, <EM>Algebraic and Discrete Mathematical Methods for Modern Biology</EM> offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the b...
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<P>Completely updated guide for students, scientists and engineers who want to use Microsoft Excel 2013 to its full potential. Electronic spreadsheet analysis has become part of the everyday work of researchers in all areas of engineering and science...
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<P>Bioinspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. <I>BioInspired Computation in Telecommunications </I>reviews the latest developments in bioinspired computation from both...
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<P><EM>Principles of Financial Engineering, Third Edition,</EM> is a highly acclaimed text on the fastpaced and complex subject of financial engineering. This updated edition describes the "engineering" elements of financial engineering instead of t...
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<P><EM>Mathematics for Physical Science and Engineering</EM> is a complete text in mathematics for physical science that includes the use of symbolic computation to illustrate the mathematical concepts and enable the solution of a broader range of pr...
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Assuming no prior background in linear algebra or real analysis, <EM>An Introduction to MATLAB</EM>®<EM> Programming and Numerical Methods for Engineers</EM> enables you to develop good computational problem solving techniques through the use of nume...
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<P><EM>An Introduction to the Mathematics of Financial Derivatives </EM>is a popular, intuitive text that eases the transition between basic summaries of financial engineering to more advanced treatments using stochastic calculus. Requiring only a ba...
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<P><EM>Introduction to Probability, Second Edition</EM>, discusses probability theory in a mathematically rigorous, yet accessible way. This onesemester basic probability textbook explains important concepts of probability while providing useful exe...
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<P>The new edition of <EM>Mathematical Modeling</EM>, the survey text of choice for mathematical modeling courses, adds ample instructor support and online delivery for solutions manuals and software ancillaries. </P>
<P>From genetic engineering to h...
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<P>Hirsch, Devaney, and Smale’s classic <EM>Differential Equations, Dynamical Systems, and an Introduction to Chaos</EM> has been used by professors as the primary text for undergraduate and graduate level courses covering differential equations...
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<P><EM>Computability Theory: An Introduction to Recursion Theory </EM>provides a concise, comprehensive, and authoritative introduction to contemporary computability theory, techniques, and results. The basic concepts and techniques of computability ...
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<P>This book considers classical and current theory and practice, of supervised, unsupervised and semisupervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the f...
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<P>Essential for all biology and biomathematics courses, this textbook provides students with a fresh perspective of quantitative techniques in biology in a field where virtually any advance in the life sciences requires a sophisticated mathematical ...
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<P>The purpose, level, and style of this new edition conform to the tenets set forth in the original preface. The authors continue with their tack of developing simultaneously theory and applications, intertwined so that they refurbish and elucidate ...
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