Exploring Eigenvectors and Eigenvalues Visually

Exploring Eigenvectors and Eigenvalues Visually

More- Subject:
- Geometry
- Mathematics and Statistics
- Material Type:
- Simulations
- Provider:
- GeoGebra
- Provider Set:
- GeoGebraTube

Conditions of Use:

Remix and Share

Exploring Eigenvectors and Eigenvalues Visually

Exploring Eigenvectors and Eigenvalues Visually

More- Subject:
- Geometry
- Mathematics and Statistics
- Material Type:
- Simulations
- Provider:
- GeoGebra
- Provider Set:
- GeoGebraTube

Conditions of Use:

Read the Fine Print

A First Course in Linear Algebra is an introductory textbook aimed at ... More

A First Course in Linear Algebra is an introductory textbook aimed at college-level sophomores and juniors. Typically students will have taken calculus, but it is not a prerequisite. The book begins with systems of linear equations, then covers matrix algebra, before taking up finite-dimensional vector spaces in full generality. The final chapter covers matrix representations of linear transformations, through diagonalization, change of basis and Jordan canonical form. Determinants and eigenvalues are covered along the way.

More- Subject:
- Mathematics
- Algebra
- Material Type:
- Textbooks
- Provider:
- University of Minnesota
- Provider Set:
- University of Minnesota - Open Academics Textbooks
- Author:
- Robert Beezer

Conditions of Use:

No Strings Attached

Este modulo nos da un pequeño repaso de la importancia de los ... More

Este modulo nos da un pequeño repaso de la importancia de los eigenvectores y eigenvalores en el análisis y entedimiento de los sistemas LTI.

More- Subject:
- Science and Technology
- Material Type:
- Readings
- Syllabi
- Provider:
- Rice University
- Provider Set:
- Connexions
- Author:
- Justin Romberg
- Michael Haag

Conditions of Use:

Remix and Share

Fundamental concepts of quantum mechanics: wave properties, uncertainty principles, Schrodinger equation, and ... More

Fundamental concepts of quantum mechanics: wave properties, uncertainty principles, Schrodinger equation, and operator and matrix methods. Basic applications to: one-dimensional potentials (harmonic oscillator), three-dimensional centrosymetric potentials (hydrogen atom), and angular momentum and spin. Approximation methods: WKB method, variational principle, and perturbation theory.

More- Subject:
- Chemistry
- Science and Technology
- Material Type:
- Assessments
- Full Course
- Homework and Assignments
- Lecture Notes
- Syllabi
- Provider:
- M.I.T.
- Provider Set:
- M.I.T. OpenCourseWare
- Author:
- Voorhis, Troy Van

Conditions of Use:

Remix and Share

This 14-minute video lesson shows how to determine the eigenvalues of a ... More

This 14-minute video lesson shows how to determine the eigenvalues of a 3x3 matrix.

More- Subject:
- Algebra
- Mathematics and Statistics
- Material Type:
- Video Lectures
- Provider:
- Khan Academy
- Provider Set:
- Khan Academy
- Author:
- Khan, Salman

Conditions of Use:

Remix and Share

This 6-minute video lesson gives an example of how to solve for ... More

This 6-minute video lesson gives an example of how to solve for the eigenvalues of a 2x2 matrix.

More- Subject:
- Algebra
- Mathematics and Statistics
- Material Type:
- Video Lectures
- Provider:
- Khan Academy
- Provider Set:
- Khan Academy
- Author:
- Khan, Salman

Conditions of Use:

Remix and Share

This video shows how to find the eigenvectors and eigenspaces of a ... More

This video shows how to find the eigenvectors and eigenspaces of a 2x2 matrix

More- Subject:
- Algebra
- Mathematics and Statistics
- Material Type:
- Video Lectures
- Provider:
- Khan Academy
- Provider Set:
- Khan Academy

Conditions of Use:

Read the Fine Print

Linear Algebra is both rich in theory and full of interesting applications; ... More

Linear Algebra is both rich in theory and full of interesting applications; in this course the student will try to balance both. This course includes a review of topics learned in Linear Algebra I. Upon successful completion of this course, the student will be able to: Solve systems of linear equations; Define the abstract notions of vector space and inner product space; State examples of vector spaces; Diagonalize a matrix; Formulate what a system of linear equations is in terms of matrices; Give an example of a space that has the Archimedian property; Use the Euclidean algorithm to find the greatest common divisor; Understand polar form and geometric interpretation of the complex numbers; Explain what the fundamental theorem of algebra states; Determine when two matrices are row equivalent; State the Fredholm alternative; Identify matrices that are in row reduced echelon form; Find a LU factorization for a given matrix; Find a PLU factorization for a given matrix; Find a QR factorization for a given matrix; Use the simplex algorithm; Compute eigenvalues and eigenvectors; State Shur's Theorem; Define normal matrices; Explain the composition and the inversion of permutations; Define and compute the determinant; Explain when eigenvalues exist for a given operator; Normal form of a nilpotent operator; Understand the idea of Jordan blocks, Jordan matrices, and the Jordan form of a matrix; Define quadratic forms; State the second derivative test; Define eigenvectors and eigenvalues; Define a vector space and state its properties; State the notions of linear span, linear independence, and the basis of a vector space; Understand the ideas of linear independence, spanning set, basis, and dimension; Define a linear transformation; State the properties of linear transformations; Define the characteristic polynomial of a matrix; Define a Markov matrix; State what it means to have the property of being a stochastic matrix; Define a normed vector space; Apply the Cauchy Schwarz inequality; State the Riesz representation theorem; State what it means for a nxn matrix to be diagonalizable; Define Hermitian operators; Define a Hilbert space; Prove the Cayley Hamilton theorem; Define the adjoint of an operator; Define normal operators; State the spectral theorem; Understand how to find the singular-value decomposition of an operator; Define the notion of length for abstract vectors in abstract vector spaces; Define orthogonal vectors; Define orthogonal and orthonormal subsets of R^n; Use the Gram-Schmidt process; Find the eigenvalues and the eigenvectors of a given matrix numerically; Provide an explicit description of the Power Method. (Mathematics 212)

MoreConditions of Use:

Remix and Share

This 8-minute video explains what eigenvectors and eigenvalues are and why they ... More

This 8-minute video explains what eigenvectors and eigenvalues are and why they are interesting.

More- Subject:
- Algebra
- Mathematics and Statistics
- Material Type:
- Video Lectures
- Provider:
- Khan Academy
- Provider Set:
- Khan Academy
- Author:
- Khan, Salman

Conditions of Use:

Remix and Share

This 9-minute video lesson shows the proof of the formula for determining ... More

This 9-minute video lesson shows the proof of the formula for determining Eigenvalues.

More- Subject:
- Algebra
- Mathematics and Statistics
- Material Type:
- Video Lectures
- Provider:
- Khan Academy
- Provider Set:
- Khan Academy
- Author:
- Khan, Salman

Conditions of Use:

No Strings Attached

This module examines the Laplace Transform, an analytical tool that produces exact ... More

This module examines the Laplace Transform, an analytical tool that produces exact solutions for small, closed-form, tractable systems. We use the Laplace transform to move toward a solution for the nerve fiber potentials modeled by the dynamic Strang Quartet in the earlier module of the same name.

More- Subject:
- Mathematics and Statistics
- Science and Technology
- Material Type:
- Readings
- Syllabi
- Provider:
- Rice University
- Provider Set:
- Connexions
- Author:
- Doug Daniels
- Steven Cox

Conditions of Use:

Read the Fine Print

Using Maple or Mathmatica, learner should be able to explore the properties ... More

Using Maple or Mathmatica, learner should be able to explore the properties of orthogonal vectors and matrices.

More- Subject:
- Science and Technology
- Material Type:
- Activities and Labs
- Instructional Material
- Provider:
- iLumina
- Provider Set:
- iLumina Digital Library
- Author:
- David Smith

Conditions of Use:

No Strings Attached

This module lays out the structure for the text of the CAAM ... More

This module lays out the structure for the text of the CAAM 335 course in matrix analysis.

More- Subject:
- Mathematics and Statistics
- Science and Technology
- Material Type:
- Readings
- Syllabi
- Provider:
- Rice University
- Provider Set:
- Connexions
- Author:
- Doug Daniels
- Steven Cox

Conditions of Use:

Remix and Share

Together, this course and 8.06 Quantum Physics III cover quantum physics with ... More

Together, this course and 8.06 Quantum Physics III cover quantum physics with applications drawn from modern physics. Topics covered in this course include the general formalism of quantum mechanics, harmonic oscillator, quantum mechanics in three-dimensions, angular momentum, spin, and addition of angular momentum.

More- Subject:
- Physics
- Science and Technology
- Material Type:
- Full Course
- Homework and Assignments
- Lecture Notes
- Syllabi
- Provider:
- M.I.T.
- Provider Set:
- M.I.T. OpenCourseWare
- Author:
- Barton Zwiebach

Conditions of Use:

Remix and Share

Topics include uncertainty relation, observables, eigenstates, eigenvalues, probabilities of the results of ... More

Topics include uncertainty relation, observables, eigenstates, eigenvalues, probabilities of the results of measurement, Transformation Theory, equations of motion, and constants of motion. Symmetry in Quantum Mechanics, Representations of Symmetry Groups. Variational and Perturbation Approximations. Systems of Identical Particles and Applications. Time-Dependent Perturbation Theory. Scattering Theory - Phase Shifts, Born Approximation. The Quantum Theory of Radiation. Second Quantization and Many-Body Theory. Relativistic Quantum Mechanics of One Electron. 8.321 is the first semester of a two-semester subject on quantum theory, stressing principles. Topics covered include: Hilbert spaces, observables, uncertainty relations, eigenvalue problems and methods for solution thereof, time-evolution in the Schrodinger, Heisenberg, and interaction pictures, connections between classical and quantum mechanics, path integrals, quantum mechanics in EM fields, angular momentum, time-independent perturbation theory, density operators, and quantum measurement.

More- Subject:
- Statistics and Probability
- Physics
- Science and Technology
- Material Type:
- Full Course
- Homework and Assignments
- Lecture Notes
- Syllabi
- Provider:
- M.I.T.
- Provider Set:
- M.I.T. OpenCourseWare
- Author:
- Taylor, Washington

Conditions of Use:

Remix and Share

A two-semester subject on quantum theory, stressing principles: uncertainty relation, observables, eigenstates, ... More

A two-semester subject on quantum theory, stressing principles: uncertainty relation, observables, eigenstates, eigenvalues, probabilities of the results of measurement, transformation theory, equations of motion, and constants of motion. Symmetry in quantum mechanics, representations of symmetry groups. Variational and perturbation approximations. Systems of identical particles and applications. Time-dependent perturbation theory. Scattering theory: phase shifts, Born approximation. The quantum theory of radiation. Second quantization and many-body theory. Relativistic quantum mechanics of one electron. This is the second semester of a two-semester subject on quantum theory, stressing principles. Topics covered include: time-dependent perturbation theory and applications to radiation, quantization of EM radiation field, adiabatic theorem and Berry's phase, symmetries in QM, many-particle systems, scattering theory, relativistic quantum mechanics, and Dirac equation.

More- Subject:
- Statistics and Probability
- Physics
- Science and Technology
- Material Type:
- Full Course
- Homework and Assignments
- Lecture Notes
- Syllabi
- Provider:
- M.I.T.
- Provider Set:
- M.I.T. OpenCourseWare
- Author:
- Taylor, Washington

Conditions of Use:

Read the Fine Print

Using Maple, Mathmatica, or MatLab, the learner will investigate the trajectories in ... More

Using Maple, Mathmatica, or MatLab, the learner will investigate the trajectories in the phase plane of 2x2 homogeneous linear systems of first-order differential equations of the form X' = AX.

More- Subject:
- Science and Technology
- Material Type:
- Activities and Labs
- Instructional Material
- Reference
- Provider:
- iLumina
- Provider Set:
- iLumina Digital Library
- Author:
- David Smith

Conditions of Use:

Read the Fine Print

Using Maple, Mathmatica, or MatLab, learner should be able to investigate the ... More

Using Maple, Mathmatica, or MatLab, learner should be able to investigate the trajectories in the phase plane of 2x2 homogeneous linear systems of first-order differential equations of the form X = AX.

More- Subject:
- Science and Technology
- Material Type:
- Activities and Labs
- Instructional Material
- Provider:
- iLumina
- Provider Set:
- iLumina Digital Library
- Author:
- David Smith