| | (0-0-3) (Lec-Lab-Credit Hours)
This course is an introduction to the basic ideas of pre-calculus and calculus for the people who need preparation or review before taking more advanced courses. The exact content depends upon the particular needs of those enrolled and the requirements of degree programs they are pursuing. Topics covered will be selected from the following: algebra, functions, and graphs; slopes and secant lines; derivatives; chain rule; optimization; curve sketching; integration; the exponential and natural logarithm; and probability density functions and integration by parts. This course may not be taken for credit towards a degree at Stevens.
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This course provides the necessary mathematical prerequisites for the computer science master’s program and also serves as a foundation for further study in mathematics. The topics covered include prepositional calculus: predicates and quantifiers; elementary number theory and methods of proof; mathematical induction; elementary set theory; combinatorics; functions and relations; countability; recursion and O-notation. Applications to computer science are stressed.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Topics include basic discrete probability, including urn models and random mappings; a brief introduction to information theory; elements of number theory including the prime number theorem, the Euler phi function, the Euclidean algorithm, the Chinese remainder theorem; and elements of abstract algebra and finite fields including basic fundamentals of groups, rings, polynomial rings, vector spaces, and finite fields. Carries credit toward the Applied Mathematics degree only when followed by CS 668.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Elementary mathematical techniques important to applied mathematics. Topics covered include review of functions and continuity; ordinary and partial derivatives; integration; ordinary and partial differential equations; infinite series and numerical techniques for solving differential equations; and multiple integration and surface integrals. Applications to problems of applied mathematics are given where feasible.
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| | (3-0-3) (Lec-Lab-Credit Hours)
This course is primarily for students interested in using numerical methods to solve problems in mathematics, science, engineering, and management. Computational projects will be a significant part of this course and it is expected that students already have experience programming in at least one high level language. Standard topics include numerical solutions of ordinary and partial differential equations, techniques in numerical linear algebra, the Fast Fourier Transform, optimization methods, and an introduction to parallel programming. Additional topics will depend on the interests of the instructor and students.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Review of limits, continuity, partial differentiation, Leibnitz’s rule; implicit functions and Jacobians; gradients, divergence, curl, line and surface integrals; theorems of Stokes, Gauss and Green; complex numbers, elementary functions, analytic functions, complex integration, power series, residue theorem, evaluation of real definite integrals; systems of linear equations, rank, eigenvalues and eigenvectors.
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| (3-0-3) (Lec-Lab-Credit Hours)
Review of first order and second order constant coefficient differential equations, nonhomogeneous equations; series solutions, Bessel and Legendre functions; boundary value problems, Fourier-Bessel series and separation of variables for partial differential equations; classification of partial differential equations; Laplace transform methods; calculus of variations; introduction to finite-difference methods.
Prerequisites:
MA 227 Multivariate Calculus
(3-0-3)(Lec-Lab-Credit Hours)
Review of matrix operations, Cramer’s rule, row reduction of matrices; inverse of a matrix, eigenvalues and eigenvectors; systems of linear algebraic equations; matrix methods for linear systems of differential equations, normal form, homogeneous constant coefficient systems, complex eigenvalues, nonhomogeneous systems, the matrix exponential; double and triple integrals; polar, cylindrical and spherical coordinates; surface and line integrals; integral theorems of Green, Gauss and Stokes. Engineering curriculum requirement.
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Difference equations; calculus of variations; integral equations; and applications to engineering and science.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Sample space, events, and probability; basic counting techniques and combinatorial probability; random variables, discrete and continuous; probability mass, probability density, and cumulative distribution functions; expectation and moments; some common distributions; jointly distributed random variables, conditional distributions and independence, bivariate normal, and transformations of variables; and Central Limit Theorem. Some additional topics may include an introduction to confidence intervals and hypothesis testing.
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| (0-0-3) (Lec-Lab-Credit Hours)
This course offers an introduction to exploratory data analysis and the use of basic statistical tools. Topics will include: data collection; descriptive statistics, and graphical and tabular treatment of quantitative, qualitative, and count data; detecting relations between variables; confidence intervals and hypothesis testing for one and two samples; simple and multiple linear regression; analysis of variance; design of experiments; and nonparametric methods. Selected topics, such as quality control and time series analysis, may also be included. Statistical software will be used throughout the course and statistical inference will be based on examples using real data. Students will participate in group projects of data analysis. They will be trained in the different phases of the professional statistician’s work, namely: data collection, description, analysis, testing, and presentation of the conclusions.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
Prerequisites:
MA 227 Multivariate Calculus
(3-0-3)(Lec-Lab-Credit Hours)
Review of matrix operations, Cramer’s rule, row reduction of matrices; inverse of a matrix, eigenvalues and eigenvectors; systems of linear algebraic equations; matrix methods for linear systems of differential equations, normal form, homogeneous constant coefficient systems, complex eigenvalues, nonhomogeneous systems, the matrix exponential; double and triple integrals; polar, cylindrical and spherical coordinates; surface and line integrals; integral theorems of Green, Gauss and Stokes. Engineering curriculum requirement.
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| | (3-0-3) (Lec-Lab-Credit Hours)
A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, Riemann-Stieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis.
Prerequisites:
MA 547 Adva
nced Calculus I
(3-0-3)(Lec-Lab-Credit Hours)
Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Fields and vector spaces; subspaces and quotient spaces; basis and dimension; linear transformations and matrices; determinants; and the theory of a single linear transformation.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Special topics in mathematics not covered in regularly scheduled courses and suitable for both graduates and advanced undergraduates. May be taken more than once.
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| | (0-0-3) (Lec-Lab-Credit Hours)
A unified development of mathematical tools for treating a variety of problems in physics and engineering. Linear algebra, normed and inner product spaces, and spectral theory of operators; integral equations; boundary value problems for ordinary and partial differential equations; Green’s functions; calculus of variations; and other related topics as time permits. Problem solving is stressed.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Topics covered in the sequence MA 605-606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, dir
ect products, Jordan-Holder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Topics covered in the sequence MA 605-606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, Jordan-Holder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
Prerequisites:
MA 605 Foundations of Algebra I
(3-0-3)(Lec-Lab-Credit Hours)
Topics covered in the sequence MA 605-606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, Jordan-Holder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Foundations of probability, random variables and their distributions, discrete and continuous random variables, independence, expectation and conditioning, generating functions, multivariate distributions, convergence of random variables, and classical limit theorems. Prerequisite: MA 222 or MA 540 or equivalent
Prerequisites:
MA 222 Probability and Statistics
(3-0-3)(Lec-Lab-Credit Hours)
Introduces the essentials of probability theory and elementary statistics. Lectures and assignments greatly stress the manifold applications of probability and statistics to computer science, production management, quality control, and reliability. A statistical computer package is used throughout the course for teaching and for assignments. Contents include: descriptive statistics, pictorial and tabular methods, and measures of location and of variability; sample space and events, probability axioms, and counting techniques; conditional
probability and independence, and Bayes' formula; discrete random variables, distribution functions and moments, and binomial and Poisson distributions; continuous random variables, densities and moments, normal, gamma, and exponential and Weibull distributions unions; distribution of the sum and average of random samples; the Central Limit Theorem; confidence intervals for the mean and the variance; hypothesis testing and p-values, and applications for the mean; simple linear regression, and estimation of and inference about the parameters; and correlation and prediction in a regression model.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Point estimation, method of moments, maximum likelihood, and properties of point estimators; confidence intervals and hypothesis testing; sufficiency; Neyman-Pearson theorem, uniformly most powerful tests, and likelihood ratio tests; and Fisher information and the Cramer-Rao inequality. Additional topics may include nonparametric statistics, decision theory, and linear models.
Prerequisites:
MA 611 Probability
(3-0-3)(Lec-Lab-Credit Hours)
Foundations of probability, random variables and their distributions, discrete and continuous random variables, independence, expectation and conditioning, generating functions, multivariate distributions, convergence of random variables, and classical limit theorems. Prerequisite: MA 222 or MA 540 or equivalent
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| | (3-0-3) (Lec-Lab-Credit Hours)
The MA 615-616 sequence covers topics in numerical analysis and numerical methods including: errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimum-maximum error approximations; nonlinear equations; simultaneous linear equations; summing series, Fourier series, filter design, the frequency approach, design of numerical tools, and statistics of error analysis; eigenvalues and eigenvectors of matrices; and the orientation throughout is toward computers.
Corequisites:
MA 547 Advanced Calculus I
(3-0-3)(Lec-Lab-Credit Hours)
El
ementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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| | (3-0-3) (Lec-Lab-Credit Hours)
The MA 615-616 sequence covers topics in numerical analysis and numerical methods including: errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimum-maximum error approximations; nonlinear equations; simultaneous linear equations; summing series, Fourier series, filter design, the frequency approach, design of numerical tools, and statistics of error analysis; eigenvalues and eigenvectors of matrices; and the orientation throughout is toward computers.
Prerequisites:
MA 615 Numerical Analysis I
(3-0-3)(Lec-Lab-Credit Hours)
The MA 615-616 sequence covers topics in numerical analysis and numerical methods including: errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimum-maximum error approximations; nonlinear equations; simultaneous linear equations; summing series, Fourier series, filter design, the frequency approach, design of numerical tools, and statistics of error analysis; eigenvalues and eigenvectors of matrices; and the orientation throughout is toward computers.
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This course covers basic ideas in sampling theory and uses only elementary mathematics. Topics include multistage sampling, stratified sampling, systematic sampling, self-weighting samples, and optimum allocation.
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| (3-0-3) (Lec-Lab-Credit Hours)
Random walks and Markov chains; Brownian motions and Markov processes; and applications, stationary (wide sense) processes, infinite divisibility, and spectral decomposition. By permission of instructor.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Absolute geometry as founded on axioms of incidence, order, congruence, and continuity; models of absolute geometry and problems of consistency; independence and categoricity of an axiom system; Euclidean and non-Euclidean geometry; brief description of the Erlangen program; and classical differential geometry of surfaces.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Fundamental laws of counting, permutations, combinations, recurrence relations, Mšbius inversion, probleme des menages, probleme des recontres, partitions, trees, generating functions, Ramsey theory, transversal theory, and matroid theory.
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| | (3-0-3) (Lec-Lab-Credit Hours)
The objective of this course is to introduce the students to the basic results of convex analysis and optimization. The properties of nonlinear non-smooth optimization models will be analyzed. Topics include: separation and representation of convex sets, properties of convex functions, subgradients, optimality conditions, saddle points, constraint qualifications, Fenchel and Lagrange duality, and sensitivity analysis. Examples of optimization models from probability, statistics, and approximation theory will be discussed, as well as some basic models from management, finance, telecommunications, and other fields.
Prerequisites:
MA 547 Advanced Calculus I
(3-0-3)(Lec-Lab-Credit Hours)
Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and t
heorems of Gauss, Green, and Stokes.
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| | (3-0-3) (Lec-Lab-Credit Hours)
The objective of this course is to introduce the students to the most popular numerical methods for solving nonlinear and non-smooth optimization problems. The techniques will be based on the properties of nonlinear non-smooth optimization models and optimality conditions. Linear optimization techniques will be treated as a special case. Some emphasis will be put on using optimization software. Examples using AMPL and CPLEX will be demonstrated in class. Topics include line search, non-derivative methods, basic decent methods, conjugate gradient methods, subgradient methods, Newton methods, projection methods, penalty, barrier, interior point methods, Lagrangian methods, bundle methods, trust-region method, numerical treatment of non-convex models, and decomposition methods.
Prerequisites:
MA 629 Convex Analysis and Optimization
(3-0-3)(Lec-Lab-Credit Hours)
The objective of this course is to introduce the students to the basic results of convex analysis and optimization. The properties of nonlinear non-smooth optimization models will be analyzed. Topics include: separation and representation of convex sets, properties of convex functions, subgradients, optimality conditions, saddle points, constraint qualifications, Fenchel and Lagrange duality, and sensitivity analysis. Examples of optimization models from probability, statistics, and approximation theory will be discussed, as well as some basic models from management, finance, telecommunications, and other fields.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Strategic games and Nash equilibrium, strictly competitive (zero-sum) games and max-minimization, sStrategic games with imperfect information (Bayesian games), extensive games with perfect information (bargaining and repeated games), extensive games with imperfect information and signaling games, coalitional games (the core, stable sets, and bargaining sets), and auctions.
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Modern theory of the delta function and other generalized functions: Fourier and Laplace transforms and applications to ordinary and partial differential equations.
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| | | (0-0-3) (Lec-Lab-Credit Hours)
Queuing theory, transportation problem, traffic theory, inventory control, search theory, and methods of optimization.
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| | (3-0-3) (Lec-Lab-Credit Hours)
The real number system. Introduction to metric spaces and their applications. Lebesque measure and integral from a classical and/or modern approach.
Prerequisites:
MA 548
(3-0-3)(Lec-Lab-Credit Hours)
A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, Riemann-Stieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis.
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| | (3-0-3) (Lec-Lab-Credit Hours)
L-p spaces and applications to Fourier series and Lebesque-Stieltjes integral.
Prerequisites:
MA 635
(3-0-3)(Lec-Lab-Credit Hours)
The real number system. Introduction to metric spaces and their applications. Lebesque measure and integral from a classical and/or
modern approach.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Prepositional calculus; syntax and semantics of first order theories; completeness theorem; elementary model theory: axiomatic development of Zermelo-Fraenkel or Bernays-Gödel set theory; and ordinals, cardinals, the axiom of choice, and several equivalent axioms.
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| | (0-0-3) (Lec-Lab-Credit Hours)
First order number theory; primitive and general recursive functions; arithmetization; Gödel’s incompleteness theorems; Tarski’s theorems; and syntax and semantics of second order theories.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Scope and applications of time series analysis: process control, financial data analysis and forecasting, and signal processing. Exploratory data analysis: graphical analysis, trend and seasonality detection and removal, and moving-average filtering. Review of basic statistical concepts related to the characterization of stationary processes. ARMA models and prediction of stationary processes. Estimation of ARMA models and model building and forecasting with ARMA models. Spectral analysis: periodogram testing for seasonality and periodicities and the maximum entropy and maximum-likelihood estimators. Asymptotic convergence. Selected topics, such as multivariate time series, nonlinear models, Kalman filtering, econometric forecasting, and long-memory processes. Selected applications, such as the unit-root problem in economics, forecasting and testing for market efficiency in financial time series, process control, and quality control.
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| (3-0-3) (Lec-Lab-Credit Hours)
Theory and application of ordinary differential equations (ODEs) with an emphasis on ODEs as continuous dynamical systems on a finite-dimensional phase space. Standard topics include existence and uniqueness theorems, general theory for linear equations, the exponential of linear map, stability of equilibrium points, hyperbolicity and structural stability, Lyapunov’s method, invariant manifolds, Floquet theory for periodic orbits, and Poincare-Bendixon theorem.
Corequisites:
MA 547 Advanced Calculus I
(3-0-3)(Lec-Lab-Credit Hours)
Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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Prerequisites:
MA 232
(3-0-3)(Lec-Lab-Credit Hours)
This course introduces basic concepts of linear algebra from a geometric point of view. Topics include the method of Gaussian elimination to solve systems of linear equations; linear spaces and dimension; independent and dependent vectors; norms, inner product, and bases in vector spaces; determinants, eigenvalues and eigenvectors of matrices; symmetric, unitary, and normal matrices; matrix representations of linear transformations and orthogonal projections; the fundamental theorems of linear algebra; and the least-squares method and LU-decomposition.
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| | (3-0-3) (Lec-Lab-Credit Hours)
This course discusses the classical theory and applications of partial differential equations and introduces the student to the modern theory. Classification of second order equations; well-posedness; existence and uniqueness for the Cauchy problem; Riemann function; Dirichlet and Neumann problems; Green’s functions; perturbation theory; elliptic operators; variational formulation for the Laplace equation; weak solutions; and Sobolev spaces.
Corequisites:
MA 547 Advanced Calculus I
(3-0-3)(Lec-Lab-Credit Hours)
Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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| | (3-0-3) (Lec-Lab-Credit Hours)
Metric spaces and topological spaces, bases and sub-bases, connectivity, local (path) connectivity, separation axioms, compactness and local compactness, concepts of convergence, Tychonoff’s theorem, Urysohn’s lemma, Tietze extension theorem, and selected topics as time permits.
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| | (0-0-3) (Lec-Lab-Credit Hours)
This course is an introduction to methods and theory in numerical solutions of partial differential equations. The finite difference and pseudo-spectral methods will be used as examples to solve partial differential equations, including parabolic, hyperbolic, and elliptic equations in one or higher dimensional space. The theory on consistency, convergence, and Von Neumann stability analysis of numerical schemes will be emphasized for a basic understanding about how to control numerical errors and to achieve higher order accuracy for numerical solutions. Students will also be assigned projects to obtain the first-hand experience in numerical computations.
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| | (0-0-3) (Lec-Lab-Credit Hours)
The main purpose of this course is to present the foundations of the optimal control theory, some applications, and their solutions. The students will be introduced to the core concepts and results of control and system theory. The foundational and basic results will be derived for discrete and continuous time scales, and state variables. Topics to be covered: proportional-derivative control; state-space and spectrum assignment; outputs and dynamic feedback; reachability; controllability; feedback and stability; Lyapunov theory; linearization principle of observability; dynamic programming algorithm; multipliers for unconstrained and constrained controls; and Pontryagin maximum principle.
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| | (0-0-3) (Lec-Lab-Credit Hours)
The main purpose of this course is to present the foundations of the stochastic control theory, the corresponding numerical methods, and some applications. The focus will be on the idea of dynamic programming which will be developed starting from deterministic models, through finite-horizon stochastic problems, to infinite-horizon stochastic problems of various types. Applications to queuing systems, network design, and routing; supply-chain management and others will be discussed in detail. Topics to be covered: basic concepts of control theory for stochastic dynamic systems; controlled Markov chains; dynamic programming for finite horizon problems; infinite horizon discounted problems; numerical methods for infinite horizon problems; linear stochastic dynamic systems in discrete time; tracking and Kalman filtering; linear quadratic models; controlled Markov processes in continuous time; and elements of stochastic control theory in continuous time and state space.
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| | (0-0-3) (Lec-Lab-Credit Hours)
This course introduces students to modeling and numerical techniques for optimization under uncertainty and risk. Topics include: generalized concavity of measures, optimization problems with probabilistic constraints (convexity, differentiability, optimality, and duality), numerical methods for solving problems with probabilistic constraints, two-stage and multi-stage models (structure, optimality, duality), decomposition methods for two-stage and multi-stage models, risk averse optimization models,
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| | (3-0-3) (Lec-Lab-Credit Hours)
Complex numbers; elementary functions; Möbius transformations; analytic functions; power series; integration; Cauchy-Goursat theorems; Cauchy integral formula; Taylor and Laurent series; singularities; residue theory; and meromorphic and entire functions.
Prerequisites:
MA 548
(3-0-3)(Lec-Lab-Credit Hours)
A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, Riemann-Stieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and
functional analysis.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Theory and methods in continuous and discrete dynamical systems. Topics may vary, but will typically include local bifurcation theory for vector fields and maps, center manifold reductions, normal forms, periodic orbits and Poincaré maps, averaging methods, Melnikov methods, chaotic dynamics, the Smale horseshoe map, and symbolic dynamics.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Study of the classical transforms, the Laplace, Fourier, Hilbert, and other transforms; inversion and application to solution of differential, difference, and integral equations; and Abelian and Tauberian theorems, including Wiener’s theory.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Geometry of Hilbert space; spectral theory of self-adjoint and normal operators; applications to differential operators; multiplicity theory; and families of operators, Stone’s theorem, and introduction to rings of operators.
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| | (0-0-3) (Lec-Lab-Credit Hours)
The course will introduce the students to the fundamental mathematical models of risk and approaches to decision-making under uncertainty and risk-aversion. The mathematical models will range from classical models as Expected Utility Theory, Prospect Theory, Dual Utility Theory, to state-of-the-art work on stochastic dominance, the theory of coherent risk measures, and gener
al deviation measures. The course also surveys recent developments in particular applied areas as portfolio optimization, asset pricing, nuclear safety, reliability, etc.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Linear topological spaces, local convexity, and spaces of distribution; Banach spaces; three fundamental theorems and applications to classical analysis; operators, operational calculus, compact operators, and applications to integral equations; Klein-Milman theorems; and fixed point theorems with applications to nonlinear problems.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Notion of simplicial complex, absolute, and relative homology groups of a space; exact sequences; cohomology; axioms for homology theory; introduction to homological algebra; and homotopy and the fundamental group.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Existence and uniqueness of solutions; dependence on parameters; periodic solutions; nonlinear autonomous systems; Poincare-Bendixon theory; continuous transformation groups; linear systems; Floquet theory; linear systems in complex domain; regular and irregular singularities; asymptotic expansions; Stokes’ phenomenon; and boundary value problems.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Characteristics and classification of equations; Cauchy-Kowalewski theorem; linear and quasilinear systems; elliptic equations and potential theory; Green’s functio
ns; mean value theorems; a priori estimates; functions space methods; hyperbolic equations; Riemann’s solution of the Cauchy problem; discontinuities and shocks; Huyghen’s principle; method of spherical means; and parabolic equations.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Algebraic number fields; rings of algebraic integers and integral basis of field discriminant; unique factorication for ideals; splitting and ramifications of primes; Kummer’s theorem with applications to quadratic and roots of unity fields; padic numbers; Hensel’s lemMA ; geometry of numbers; units in an algebraic extension; finiteness of class numbers of a field; and computation of class numbers in special cases.
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| | (0-0-3) (Lec-Lab-Credit Hours)
One to six credits. Limit of six credits for the degree of Master of Science.
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| | (0-0-3) (Lec-Lab-Credit Hours)
One to six credits. Limit of six credits for the degree of Doctor of Philosophy.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Special topics in mathematics not covered in regularly scheduled courses and suitable for both graduates and advanced undergraduates. May be taken more than once.
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| | (0-0-3) (Lec-Lab-Credit Hours)
For the degree of Master of Science. Five to ten credits with departmental approval.
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| | (0-0-3) (Lec-Lab-Credit Hours)
Original research carried out under the guidance of a member of the faculty which may serve as the basis for the dissertation required for the degree of Doctor of Philosophy. Hours and credits to be arranged.
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