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For an $n$-dimensional system, the lecture states there are $n$ Lyapunov exponents $\lambda_i$, matching the number of state-space dimensions.

Conditions: Stated for an $n$-dimensional dynamical system.; The clip does not discuss degeneracies or zero exponents separately.

For an $n$-dimensional system, the lecture states there are $n$ Lyapunov exponents $\lambda_i$, matching the number of state-space dimensions.

Conditions: Stated for an $n$-dimensional dynamical system.; The clip does not discuss degeneracies or zero exponents separately.

For general trajectories not confined exactly to a single stable or unstable manifold, the lecture argues that the largest positive Lyapunov exponent controls the long-time behavior. This is summarized on the slide as $\lambda_1$ dominating as $t\to\infty$.

Conditions: Trajectory experiences a mix of stable and unstable effects.; Looking at the long-time limit.

For general trajectories not confined exactly to a single stable or unstable manifold, the lecture argues that the largest positive Lyapunov exponent controls the long-time behavior. This is summarized on the slide as $\lambda_1$ dominating as $t\to\infty$.

Conditions: Trajectory experiences a mix of stable and unstable effects.; Looking at the long-time limit.