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1 - 10 of 14 results for: CME

CME 102: Ordinary Differential Equations for Engineers (ENGR 155A)

Analytical and numerical methods for solving ordinary differential equations arising in engineering applications: Solution of initial and boundary value problems, series solutions, Laplace transforms, and nonlinear equations; numerical methods for solving ordinary differential equations, accuracy of numerical methods, linear stability theory, finite differences. Introduction to MATLAB programming as a basic tool kit for computations. Problems from various engineering fields. Prerequisite: CME 100/ ENGR 154 or MATH 51.
Terms: Aut, Win, Spr, Sum | Units: 5 | UG Reqs: GER:DB-Math, WAY-FR | Grading: Letter or Credit/No Credit

CME 106: Introduction to Probability and Statistics for Engineers (ENGR 155C)

Probability: random variables, independence, and conditional probability; discrete and continuous distributions, moments, distributions of several random variables. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, non-parametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields. Prerequisite: CME 100/ENGR154 or MATH 51.
Terms: Win, Sum | Units: 3-4 | UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit
Instructors: Khayms, V. (PI)

CME 108: Introduction to Scientific Computing (MATH 114)

Introduction to Scientific Computing Numerical computation for mathematical, computational, physical sciences and engineering: error analysis, floating-point arithmetic, nonlinear equations, numerical solution of systems of algebraic equations, banded matrices, least squares, unconstrained optimization, polynomial interpolation, numerical differentiation and integration, numerical solution of ordinary differential equations, truncation error, numerical stability for time dependent problems and stiffness. Implementation of numerical methods in MATLAB programming assignments. Prerequisites: MATH 51, 52, 53; prior programming experience (MATLAB or other language at level of CS 106A or higher).nGraduate students should take it for 3 units and undergraduate students should take it for 4 units.
Terms: Win, Sum | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

CME 263: Introduction to Linear Dynamical Systems (EE 263)

Applied linear algebra and linear dynamical systems with application to circuits, signal processing, communications, and control systems. Topics: least-squares approximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm, and singular value decomposition. Eigenvalues, left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input/multi-output systems, impulse and step matrices; convolution and transfer matrix descriptions. Control, reachability, and state transfer; observability and least-squares state estimation. Prerequisites: linear algebra and matrices as in MATH 103; differential equations and Laplace transforms as in EE 102A.
Terms: Aut, Sum | Units: 3 | Grading: Letter or Credit/No Credit

CME 291: Master's Research

Students require faculty sponsor. (Staff)
Terms: Aut, Win, Spr, Sum | Units: 1-6 | Repeatable for credit | Grading: Letter or Credit/No Credit

CME 364A: Convex Optimization I (CS 334A, EE 364A)

Terms: Win, Sum | Units: 3 | Grading: Letter or Credit/No Credit

CME 400: Ph.D. Research

Terms: Aut, Win, Spr, Sum | Units: 1-15 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: Alonso, J. (PI) ; Athey, S. (PI) ; Bambos, N. (PI) ; Beroza, G. (PI) ; Boahen, K. (PI) ; Boneh, D. (PI) ; Bosagh Zadeh, R. (PI) ; Boyd, S. (PI) ; Candes, E. (PI) ; Carlsson, G. (PI) ; Darve, E. (PI) ; Delp, S. (PI) ; Diaconis, P. (PI) ; Donoho, D. (PI) ; Dror, R. (PI) ; Farhat, C. (PI) ; Fedkiw, R. (PI) ; Fringer, O. (PI) ; Genesereth, M. (PI) ; Gerritsen, M. (PI) ; Giesecke, K. (PI) ; Glynn, P. (PI) ; Goel, A. (PI) ; Golub, G. (PI) ; Guibas, L. (PI) ; Hanrahan, P. (PI) ; Hastie, T. (PI) ; Holmes, S. (PI) ; Hong, H. (PI) ; Iaccarino, G. (PI) ; Jameson, A. (PI) ; Johari, R. (PI) ; Kamvar, S. (PI) ; Khatib, O. (PI) ; Khayms, V. (PI) ; Kitanidis, P. (PI) ; Kosovichev, A. (PI) ; Kumar, S. (PI) ; Lai, T. (PI) ; Langley, P. (PI) ; Lee, P. (PI) ; Lele, S. (PI) ; Leskovec, J. (PI) ; Levinson, D. (PI) ; Levitt, M. (PI) ; Lew, A. (PI) ; Linder, C. (PI) ; Liu, T. (PI) ; Moerner, W. (PI) ; Moin, P. (PI) ; Montanari, A. (PI) ; Motwani, R. (PI) ; Murray, W. (PI) ; Ng, A. (PI) ; Pande, V. (PI) ; Papanicolaou, G. (PI) ; Pitsch, H. (PI) ; Plevritis, S. (PI) ; Poulson, J. (PI) ; Rajagopal, R. (PI) ; Rajaratnam, B. (PI) ; Reed, E. (PI) ; Roughgarden, T. (PI) ; Saberi, A. (PI) ; Salisbury, J. (PI) ; Saunders, M. (PI) ; Shaqfeh, E. (PI) ; Taylor, C. (PI) ; Tchelepi, H. (PI) ; Tibshirani, R. (PI) ; Wein, L. (PI) ; Weissman, T. (PI) ; Wong, W. (PI) ; Xing, L. (PI) ; Ye, Y. (PI) ; Ying, L. (PI)

CME 244: Project Course in Mathematical and Computational Finance

For graduate students in the MCF track; students will work individually or in groups on research projects.
Terms: Aut, Win, Spr, Sum | Units: 1-6 | Grading: Letter (ABCD/NP)
Instructors: Jain, K. (PI)

CME 245: Topics in Mathematical and Computational Finance

Current topics for enrolled students in the MCF program; can be repeated up to three times.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: Jain, K. (PI)
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