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Courses Programs - Thayer School of Engineering - Dartmouth ...

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graduate courses<br />

90<br />

Graduate Course Descriptions<br />

ENGS 91 Numerical Methods in Computation<br />

(Identical to MATH 26 and COSC 26)<br />

Offered: 10F, 11F: 12<br />

A study and analysis <strong>of</strong> important numerical and computational methods for solving<br />

engineering and scientific problems. The course will include methods for solving linear<br />

and nonlinear equations, doing polynomial interpolation, evaluating integrals,<br />

solving ordinary differential equations, and determining eigenvalues and eigenvectors<br />

<strong>of</strong> matrices. The student will be required to write and run computer programs.<br />

Prerequisite: COSC 5 or ENGS 20; ENGS 22 or MATH 23, or equivalent<br />

Instructor: Shepherd<br />

ENGS 92 Fourier Transforms and Complex Variables<br />

(Identical to PHYS 70)<br />

Offered: 10F, 11F: 2<br />

Survey <strong>of</strong> a number <strong>of</strong> mathematical methods <strong>of</strong> importance in engineering and<br />

physics with particular emphasis on the Fourier transform as a tool for modeling and<br />

analysis. Orthogonal function expansions, Fourier series, discrete and continuous<br />

Fourier transforms, generalized functions and sampling theory, complex functions<br />

and complex integration, Laplace, Z, and Hilbert transforms. Computational Fourier<br />

analysis, applications to linear systems, waves, and signal processing.<br />

Prerequisites: MATH 33 or ENGS 22, and ENGS 23 or equivalent<br />

Instructor: Testorf<br />

ENGS 93 (formerly 103) Statistical Methods in <strong>Engineering</strong><br />

Offered: 11W, 12W: 11 11S, 12S: 12<br />

The application <strong>of</strong> statistical techniques and concepts to maximize the amount<br />

and quality <strong>of</strong> information resulting from experiments. After a brief introductory<br />

summary <strong>of</strong> fundamental concepts in probability and statistics, topics considered will<br />

include probability distributions, sampling distributions, estimation and confidence<br />

intervals for parameters <strong>of</strong> statistical distributions, hypothesis testing, design and<br />

analysis <strong>of</strong> variance for single and multiple-factor experiments, regression analysis,<br />

estimation and confidence intervals for parameters <strong>of</strong> non-statistical models, and<br />

statistical quality control.<br />

Prerequisite: MATH 13 or equivalent<br />

Instructors: Borsuk (winter), Lasky (spring)<br />

ENGS 100 Methods in Applied Mathematics I<br />

(Identical to PHYS 100)<br />

Offered: 10F, 11F: 11<br />

Concepts and methods used in the treatment <strong>of</strong> linear equations with emphasis on<br />

matrix operations, differential equations, and eigenvalue problems will be developed<br />

following a brief review <strong>of</strong> analytic function theory. Topics include the Fourier<br />

integral, finite and infinite dimensional vector spaces, boundary value problems,<br />

eigenfunction expansions, Green’s functions, transform techniques for partial<br />

differential equations, and series solution <strong>of</strong> ordinary differential equations.<br />

Properties and uses <strong>of</strong> orthogonal polynomials and special functions such as the<br />

hypergeometric, Bessel, Legendre, and gamma functions are included. Applications<br />

in engineering and physics are emphasized.<br />

Prerequisite: Either ENGS 92 or MATH 33 or MATH 43 with permission <strong>of</strong> instructor,<br />

or equivalent<br />

Instructor: Caldwell

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