Mathematics for AI and Machine Learning

Foundations for modern AI and machine learning

Zero-Order Hold

Chapter 20 Dynamics & diffusion

Chapter 20: ODE, SDE, and Continuous Limits of Algorithms — Zero-Order Hold (ZOH)

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Zero-Order Hold — animated GIF preview
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Zero-Order Hold — high-resolution mind-map icon

From the book

Chapter 20: ODE, SDE, and Continuous Limits of Algorithms. In the chapter mind map this icon labels Zero-Order Hold (ZOH). The discussion below is excerpted and lightly edited from § Zero-Order Hold (ZOH) in Mathematics for AI and Machine Learning.

Assuming the input $\mathbf{u}(t)$ is constant over each interval $[k\Delta, (k+1)\Delta)$, the exact discrete-time equivalent is:

  • Exact for piecewise-constant inputs
  • Preserves stability: if $\mathrm{Re}(\lambda_i) < 0$ for all eigenvalues of $A$, then $|\mu_i| < 1$ for all eigenvalues of $\bar{A}$
  • Requires computing matrix exponential (can be expensive)

What this drawing shows

What you see. Gray continuous signal dashed; green zero-order-hold stair steps build left to right, holding each sample until the next grid time.

In the mind map. Chapter 20 — Zero-Order Hold (ZOH). See From the book above for definitions, figures, and worked examples.

Where to read next

Open Chapter 20 companion →

Read the full definitions, figures, and worked examples in Chapter 20: ODE, SDE, and Continuous Limits of Algorithms — see the mind-map node Zero-Order Hold (ZOH).