Keywords: Quasilinear PDEs (4)

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Linear Partial Differential Equations: Analysis and Numerics, Fall 2010

Linear Partial Differential Equations: Analysis and Numerics, Fall 2010

This course provides students with the basic analytical and computational tools of ... (more)

This course provides students with the basic analytical and computational tools of linear partial differential equations (PDEs) for practical applications in science engineering, including heat/diffusion, wave, and Poisson equations. Analytics emphasize the viewpoint of linear algebra and the analogy with finite matrix problems. Numerics focus on finite-difference and finite-element techniques to reduce PDEs to matrix problems. (less)

Subject:
Mathematics and Statistics
Material Type:
Assessments
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Johnson, Steven G.
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Linear Partial Differential Equations, Fall 2004

Linear Partial Differential Equations, Fall 2004

The classical partial differential equations of applied mathematics: diffusion, Laplace/Poisson, and wave ... (more)

The classical partial differential equations of applied mathematics: diffusion, Laplace/Poisson, and wave equations. Methods of solution, such as separation of variables, Fourier series and transforms, eigenvalue problems. Green's function methods are emphasized. 18.04 or 18.112 are useful, as well as previous acquaintance with the equations as they arise in scientific applications. (less)

Subject:
Mathematics and Statistics
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Hancock, Matthew
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Linear Partial Differential Equations, Fall 2005

Linear Partial Differential Equations, Fall 2005

The classical partial differential equations of applied mathematics: diffusion, Laplace/Poisson, and wave ... (more)

The classical partial differential equations of applied mathematics: diffusion, Laplace/Poisson, and wave equations. Methods of solution, such as separation of variables, Fourier series and transforms, eigenvalue problems. Green's function methods are emphasized. 18.04 or 18.112 are useful, as well as previous acquaintance with the equations as they arise in scientific applications. (less)

Subject:
Mathematics and Statistics
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Hancock, Matthew
Remix and Share
Linear Partial Differential Equations, Fall 2006

Linear Partial Differential Equations, Fall 2006

The classical partial differential equations of applied mathematics: diffusion, Laplace/Poisson, and wave ... (more)

The classical partial differential equations of applied mathematics: diffusion, Laplace/Poisson, and wave equations. Methods of solution, such as separation of variables, Fourier series and transforms, eigenvalue problems. Green's function methods are emphasized. 18.04 or 18.112 are useful, as well as previous acquaintance with the equations as they arise in scientific applications. (less)

Subject:
Mathematics and Statistics
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
Hancock, Matthew
Remix and Share
2002 llaF ,gnivloS melborP gnireenignE dna sretupmoC ot noitcudortnI

2002 llaF ,gnivloS melborP gnireenignE dna sretupmoC ot noitcudortnI

.desu si egaugnal gnimmargorp avaJ ehT .gninnalp dna ,tnemeganam ,ecneics ,gnireenigne ni ... (more)

.desu si egaugnal gnimmargorp avaJ ehT .gninnalp dna ,tnemeganam ,ecneics ,gnireenigne ni smelborp gnivlos rof seuqinhcet gnipoleved no si sisahpmE .scipot decnavda detceles dna scihparg retupmoc ,gnihcraes dna gnitros ,serutcurts atad ,sdohtem laciremun ,secafretni resu lacihparg ,stpecnoc gnimmargorp revoc smelborp gnimmargorp ylkeeW .esruoc eht fo sucof eht si tnempoleved dna ngised erawtfos detneiro-tcejbO .snoitacilppa cifitneics dna gnireenigne rof sdohtem lanoitatupmoc dna tnempoleved erawtfos latnemadnuf stneserp esruoc sihT (less)

Subject:
Science and Technology
Material Type:
Assessments
Full Course
Homework and Assignments
Lecture Notes
Syllabi
Collection:
MIT OpenCourseWare
Provider:
M.I.T.
Author:
George Kocur
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