Process Models & Parameter Identification

Related lectures (29)

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Explores the concept of rank in 3x3 matrix representations and how it determines the structure of matrices.

Covers stress equilibrium, strain, and constitutive equations in 2D and 3D.

Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.

Explores the Laplacian matrix and consensus in networked control systems.

Covers the linear optimization problem of the transhipment model.

Covers the transhipment problem, optimal solutions, and total unimodularity in matrices.

Covers the fundamentals of linear equations, matrices, and systems of linear equations, including matrix operations and solutions.

Explores the infinite solutions of a specific matrix equation for any choice of a constant.

Explores methods for solving linear systems and building solutions step by step.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.