Linear Systems I (Intro Lecture)
Linear Systems I (Intro Lecture)
This lecture provides an introduction to linear systems.
Topics covered in this lesson
- Dynamic features of the brain and their allied dynamical systems description
- Geometric and algorithmic/computational perspectives
- Motivation for linear dynamical systems in terms of approximations near equilibria
- Utility of this approximation is in terms of geometrical approaches (eigenvector decompositions)
- Treatment of time-dependent systems, including those driven by stochastic signals or noise
- Examples on how networks and the activity that they produce co-evolve over time
Prerequisites
Experience with Python Programming Language.
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