Control Bootcamp
Rapid overview of optimal control concepts, covering controllability, observability, LQR, and Kalman filter. Applies main approaches to simple Matlab examples for practical understanding.
MIT - A 2020 Vision of Linear Algebra, Spring 2020
Professor Strang presents a fresh approach to linear algebra, focusing on matrices. This concise series covers key concepts like column space, orthogonality, eigenvalues, and solving linear systems.
Linear Algebra
In this course, you will learn systems of linear equations, Matrices, Elementary row operations, Row-reduced echelon matrices. Vector spaces, Subspaces, Bases and dimension, Ordered bases and coordinates.
Quantum Mechanics and Applications
Explore quantum mechanics fundamentals, including wave-particle duality, Schrödinger equation, and applications in atomic physics. Develop problem-solving skills for quantum systems.
Dynamics of Ocean Structures
Explore ocean structure dynamics, from types and environmental forces to vibration analysis and stochastic dynamics. Learn about platforms, fluid-structure interaction, and response control methods.
Basic Linear Algebra
Linear Algebra is a basic course for students intended to go for Engineering studies and higher studies in Mathematics. We will cover the basic tools needed in these branches.
Linear Algebra
Comprehensive exploration of linear algebra concepts, from basic operations to advanced topics like eigenvalues, with practical applications and problem-solving techniques.
Applied Linear Algebra
Explore vector spaces, linear maps, eigenvalues, and applications in systems, algorithms, and optimization. Gain practical skills in linear algebra for various fields.
Facial Recognition: Eigenvectors and Covariance Matrices - Lecture 14
Explore facial recognition technology, from simple approaches to advanced techniques using eigenvectors and covariance matrices. Learn about challenges and solutions in this field.
Two-sided Lieb-Thirring Bounds for Semi-bounded Schrödinger Operators
Explore upper and lower bounds for eigenvalues of semi-bounded Schrödinger operators, focusing on atomic Hamiltonians with Kato potentials and the landscape function in all spatial dimensions.
Monotonicity of Entropy in Families of Interval Maps - Lecture 2
Explore the transfer operator, holomorphic motions, and entropy monotonicity in interval maps. Gain insights into applications in rational dynamics and quadratic families.
Matrices
Explore advanced matrix concepts including Kronecker product, spectral decomposition, singular value decomposition, and projection matrices, with applications in statistics and linear algebra.
Linear Algebra
Comprehensive exploration of linear algebra concepts, from basic matrix operations to complex numbers, with practical examples and geometric applications.
A Second Course in Differential Equations
Explore advanced topics in ordinary differential equations, including linear systems, eigenvalues, numerical methods, and Python implementations for solving complex ODEs.
Linear Algebra - Vol 2
Explore advanced linear algebra concepts including transformation matrices, determinants, cofactors, eigenvalues, and eigenvectors through comprehensive lessons and practical examples.
Grade 11 Maths - Matrices
Explore matrices, determinants, and their applications in solving systems of equations, including Cramer's rule, for Ethiopian Grade 11 mathematics.
Linear Algebra
Comprehensive exploration of linear algebra concepts, from matrices and vector spaces to eigenvalues and transformations, with practical applications and in-depth explanations.
Linear Algebra for Quantum Mechanics
Explore essential linear algebra concepts for quantum mechanics, including linear transformations, eigenvectors, and Hermitian operators, enhancing your understanding of mathematical formalism in quantum physics.
Drawing Phase Portraits for Nonlinear Systems
Learn to analyze nonlinear systems by drawing phase portraits, identifying fixed points, linearizing, and inferring global dynamics. Gain practical skills in stability analysis using eigenvalues and eigenvectors.
Systems of ODEs - Saddle Points and Instability
Explore unstable saddle points in 2D linear ODEs, their applications in energy-efficient transport, and analysis using eigenvalues, eigenvectors, and phase portraits.
Eigenvalues and Eigenvectors
Explore eigenvalues and eigenvectors, key concepts in linear algebra. Learn to compute them for any matrix, understand their significance in transformations, and apply them to solve complex linear systems.