Lectures related to Trace (linear algebra)

Covers the basics of linear algebra, including matrix operations and singular value decomposition.

Explores projections in R³, matrix properties, and trace concepts with practical examples.

Linear Algebra Basics: Matrix Representations and Transformations

Explores linear algebra basics, emphasizing matrix representations of transformations and the importance of choosing appropriate bases.

Linear Matrix Inequalities: Control Networks

Explores Linear Matrix Inequalities in networked control systems and analyzes control networks' basics and performance.

Matrix Trace Properties

Explains matrix trace properties and finding independent vectors in trace space.

Linear Algebra: Matrices and Operations

Covers the definition of 3x3 matrices, determinants, matrix operations, and invertibility.

Eigenvalues and Similar Matrices

Explores eigenvalues, matrix trace, and similarity, highlighting their significance in matrix properties.

Eigenstate Thermalization Hypothesis

Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.

End of the M-step derivation

Covers the derivation of the M-step for mu_k and Sigma_k, focusing on key quantities and matrices.

Linear Algebra in 3D: Determinants and Inverses

Explores determinants in 3D space and their role in linear algebra.

Linear Algebra: Matrix Representation of Linear Applications

Explores matrix representation of linear applications, emphasizing eigenvalues and bases.

Linear Systems in 2D: Stability

Explores stability in linear 2D systems, covering fixed points, vector fields, and phase portraits.

Smart Sensing Labels and RFID Systems

Covers the development of smart sensing labels and RFID systems for perishable goods traceability.

Cayley-Hamilton Theorem

Covers the Cayley-Hamilton theorem, demonstrating matrix self-satisfaction and validity of introduced processes.

Linear Algebra: Matrices and Linear Applications

Covers matrices, linear applications, vector spaces, and bijective functions.

Linear Matrix Inequalities: Stability and Optimization

Explores stability analysis for linear time-varying and switched systems using Lyapunov theory and Linear Matrix Inequalities.

Lie Algebra: Representations

Explores Lie algebra representations, emphasizing SU(2) and traceless matrices, explained by Alfredo Glioti.

Density Operator: Matrix to the System State

Explores density operator matrix transformation in quantum physics and the implications of measuring the system, leading to state collapse.

Reduced Density Matrices: System+Environment

Covers the concept of density matrices and the system-environment interaction.

Linear Transformations: Matrices and Kernels

Covers linear transformations, matrices, kernels, and properties of invertible matrices.