Lecture

Small Scale Stability: Solutions and Stability Analysis

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Covers small scale stability conditions and asymptotic behavior around fixed points.

Covers small scale stability at equilibrium points in dynamical systems for engineers.

Discusses stability analysis of equilibrium points in dynamical systems.

Explores fixed point stability, Lyapunov functions, Lotka-Volterra models, and nonlinear dynamics in complex systems.

Explores bistability in the cell cycle, emphasizing positive feedback mechanisms and abrupt response transformations.

Explores stability properties and fixed points in discrete time solutions.

Explores one-dimensional maps, periodic solutions, and bifurcations in dynamical systems.

Covers the introduction to Quantum Chaos, classical chaos, sensitivity to initial conditions, ergodicity, and Lyapunov exponents.

Explores bistability in genetic networks, analyzing fixed points and stability, phase portraits, and experimental implementation.

Covers the stability of discrete time periodic solutions and their properties.

Explores fixed points and their stability in dynamic systems, emphasizing linear stability analysis.

Covers the formalism and bases of dynamic systems, including differential equations and non-linear systems.

Covers dynamic systems, trajectories, growth models, stability of fixed points, and linearization of models.

Explores phase portraits in 2D systems and the dynamics of predator-prey models.

Covers the Phase Plane Analysis of 2-dimensional neuron models, focusing on nullclines and fixed points.

Explores the Kuramoto model for synchronization in phase oscillators and discusses stability criteria and critical coupling values.

Explores periodic orbits in Hamiltonian systems and their stability under various conditions.

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

Covers the basics of information theory, entropy, and fixed points in graph colorings and the Ising model.

Covers the stability analysis of fixed points in two-dimensional neuron models.