Matlab 2: Vectorisation and Functions

Related lectures (48)

Covers the 'find' function in Matlab for testing criteria on vectors or matrices.

Provides a Python crash course covering basic arithmetics, complex numbers, strings, lists, dictionaries, and more.

Covers programming functions in MATLAB, including handling scalars, vectors, matrices, and variable naming conventions.

Covers the application of numerical methods to solve differential equations using MATLAB.

Explores the application and formulation of the finite element method in solving various engineering problems.

Explores oriented angles in analytical geometry, discussing unit vectors, trigonometric functions, matrix representations, and rotations.

Covers the basics of compilation and C++ programming, including variables, functions, loops, and debugging.

Covers basic operations on arrays and functions in Matlab, including array creation, arithmetic operations, and function definitions.

Covers the basics of programming in Matlab, focusing on interactive usage, mathematical operations, vectors, matrices, strings, and 3D matrices.

Covers entropy, its definition, and its implications in thermodynamics.

Covers the joint equidistribution of CM points and explores convergence in multiple variables.

Covers exercises on genome-scale metabolic models, including FBA and TFA analysis, as well as modeling kinetics.

Covers advanced topics related to limits and sequences.

Covers mathematical concepts from number theory to probability and statistics.

Explores approximating functions with Taylor series, showcasing step-by-step calculations and practical applications.

Explores interpolation techniques, including inequalities, continuity proofs, and function interpolation in different spaces.

Introduces Mathematica basics, including graphics creation, list manipulation, and function definition.

Covers the concept of limits at infinity and discusses criteria and examples of functions approaching infinity.

Covers the properties of limits and functions of multiple variables.

Covers differentiability of functions in two variables and the conditions for a function to be differentiable.

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