Resources for ENC students, staff, and faculty.
Bayesian Reasoning and Machine Learning
Call Number: Q325.5 .B347 2012
Publication Date: 2012-02-02
This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.
Advances in Discrete Dynamics
Call Number: QA845 .A3183 2012
Publication Date: 2013-01-01
Discrete dynamical systems, the main topic of this book, have had a fast development due to the development of computer science. Programming an iteration with the form xn+1 = f(xn), where f is a real function is made easy with modern computers. So, with the modern computer, it is relatively easy and fast to obtain simulations related with the dynamics of their models. Finding analytical proofs for computer simulations of models are natural and exciting problems for mathematicians and, like in a feedback process, new powerful analytical results motivate the use of discrete models. This book examines the theory of dynamical systems.
The Linear Sampling Method in Inverse Electromagnetic Scattering
Call Number: QC20.7 .S3 C35 2011
Publication Date: 2011-01-01
This book describes the linear sampling method for a variety of electromagnetic scattering problems. It presents uniqueness theorems and the derivation of various inequalities on the material properties of the scattering object from a knowledge of the far field pattern of the scattered wave. Also covered are: the approximation properties of Herglotz wave functions; the behavior of solutions to the interior transmission problem, a novel interior boundary value problem; and numerical examples of the inversion scheme.
Chaotic Signal Processing
Call Number: TK5102.9 .C47145 2014
Publication Date: 2014
This book presents up-to-date research results on chaotic signal processing, including the application of nonlinear dynamics to radar target recognition, an exactly solvable chaos approach for communications, a chaotic approach for reconfigurable computing, system identification using chaos, design of high resolution LADAR system based on chaos, and the use of chaos on comprehensive sensing.
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This multi-disciplinary database provides full text for thousands of journals, including full text for many peer-reviewd titles and PDF backfiles to 1886. Some useful subjects in this database include business, marketing management and economics.
This electronic publication offers access to a carefully maintained and easily searchable database of reviews, abstracts and bibliographic information for much of the mathematical sciences literature. Over 100,000 new items are added each year, most of them classified according to the Mathematics Subject Classification. MathSciNet® contains over 2.8 million items and over 1.6 million direct links to original articles. Bibliographic data from retrodigitized articles dates back to the early 1800s. Reference lists are collected and matched internally from approximately 500 journals, and citation data for journals, authors, articles and reviews is provided.
- Science Citation Index
The Science Citation Index (part of Web of Science) provides access to current and retrospective bibliographic information, author abstracts, and cited references found in approximately 5,900 of the world's leading scholarly science and technical journals covering more than 150 disciplines. AFIT access to partial-full text only.
Did you know that we also link our full-text databases through Google Scholar? If you search from any campus computer or authenticate through VPN, Google Scholar will direct you to sources from the D'Azzo Research Library.
- American Mathematical Society (AMS)
The American Mathematical Society (AMS) is an association of professional mathematicians dedicated to the interests of mathematical research and scholarship, and serves the national and international community through its publications, meetings, advocacy and other programs.
- Mathematical Association of America (MAA)
The Mathematical Association of America is the largest professional society that focuses on mathematics accessible at the undergraduate level. MAA is the leading professional association in collegiate mathematics, the preeminent publisher of expository mathematics, the primary source of professional development programs for faculty, and the number one provider of resources for teaching and learning.
- Society for Industrial and Applied Mathematics (SIAM)
SIAM exists to ensure the strongest interactions between mathematics and other scientific and technological communities through membership activities, publication of journals and books, and conferences.
- American Statistical Association (ASA)
The worlds largest community of statistians, ASA promotes excellence in the development, application, and dissemination of statistical science through meetings, publications, membership services, education, accreditation, and advocacy.
- International Association Statistical Computing (IASC)
A division of the International Statitistician Institute (ISI), the IASC focuses on computational statistics, statistical software, exploratory data analysis, data mining, pattern recognition, statistical graphics and data visualisation, statistical data bases, and related fields.
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AMPL is a comprehensive and powerful algebraic modeling language for linear and nonlinear optimization problems, in discrete or continuous variables.
CPLEX's mathematical optimization technology enables better decision-making for efficient resource utilization.
MATLAB is a programming environment for algorithm development, data analysis, visualization, and numerical computation. Using MATLAB, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran.
Mathematica is renowned as the world's ultimate application for computations.