ELL800: Difference between revisions
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== ELL800 : Numerical Linear Algebra and Optimization in Engineering == | == ELL800 : Numerical Linear Algebra and Optimization in Engineering == | ||
Basics of Linear Algebra; Matrix decomposition - LU, LDU, QR and Cholesky factorization; Householder reflection, Givens rotation; Numerical implications of SVD; Numerical Solution for Linear Systems; Algorithm Stability; Problem Conditioning; Pivoting and scaling; Least Square Solutions; Numerical Matrix eigenvalue methods; Sparse Systems; Iterative methods for large systems; Krylov, Arnoldi, Lanczos methods; Numerical Optimization techniques - Conjugate gradient method, Linear and quadratic programming, Spectral and Pseudo-spectral methods. ELp800 Control Systems Laboratory 1 Credit (0-0-2) Basics of Sensors and Actuators, Study of AC and DC Motors, Linear Systems, Analog and Digital Motors, Synchros, Temperature Control. | Basics of Linear Algebra; Matrix decomposition - LU, LDU, QR and Cholesky factorization; Householder reflection, Givens rotation; Numerical implications of SVD; Numerical Solution for Linear Systems; Algorithm Stability; Problem Conditioning; Pivoting and scaling; Least Square Solutions; Numerical Matrix eigenvalue methods; Sparse Systems; Iterative methods for large systems; Krylov, Arnoldi, Lanczos methods; Numerical Optimization techniques - Conjugate gradient method, Linear and quadratic programming, Spectral and Pseudo-spectral methods. [[ELp800]] Control Systems Laboratory 1 Credit (0-0-2) Basics of Sensors and Actuators, Study of AC and DC Motors, Linear Systems, Analog and Digital Motors, Synchros, Temperature Control. | ||
Latest revision as of 16:32, 14 April 2026
| ELL800 | |
|---|---|
| Numerical Linear Algebra and Optimization in Engineering | |
| Credits | 3 |
| Structure | 3-0-0 |
| Pre-requisites | |
| Overlaps | |
ELL800 : Numerical Linear Algebra and Optimization in Engineering
Basics of Linear Algebra; Matrix decomposition - LU, LDU, QR and Cholesky factorization; Householder reflection, Givens rotation; Numerical implications of SVD; Numerical Solution for Linear Systems; Algorithm Stability; Problem Conditioning; Pivoting and scaling; Least Square Solutions; Numerical Matrix eigenvalue methods; Sparse Systems; Iterative methods for large systems; Krylov, Arnoldi, Lanczos methods; Numerical Optimization techniques - Conjugate gradient method, Linear and quadratic programming, Spectral and Pseudo-spectral methods. ELp800 Control Systems Laboratory 1 Credit (0-0-2) Basics of Sensors and Actuators, Study of AC and DC Motors, Linear Systems, Analog and Digital Motors, Synchros, Temperature Control.