Process Models & Parameter Identification

Related lectures (29)

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Explores graphs and matrices, including adjacency, degree, and Laplace matrices, Matrix-tree theorem, and spanning trees.

Covers the matrix representations of linear applications and the equivalence between matrices.

Explores the Matrix Tree Theorem and its application in calculating spanning trees in graphs.

Explores the Ford Fulkerson algorithm, Max-Flow Min-Cut theorem, Incidence matrix, and network optimization complexity.

Explores process unit modeling, balance equations, degrees of freedom, and flowsheet solving.

Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.

Explores properties of matrices, irreducibility, and graph connectivity in networked control systems.

Introduces key concepts in linear algebra, including matrices, operations, and numerical invariants.

Covers systems of equations, matrices, solving examples, and consequences of invertible matrices.