Mathematics for AI and Machine Learning

Foundations for modern AI and machine learning

Kronecker Vectorization

Chapter 10 Mathematics for AI

Chapter 10: Matrix Block Partitioning — Vector Kronecker Product

High-resolution PNG
Kronecker Vectorization — high-resolution mind-map icon

From the book

Chapter 10: Matrix Block Partitioning. In the chapter mind map this icon labels Vector Kronecker Product: $\mathrm{vec}(\mathbf{a}\mathbf{b}^\top) = \mathbf{b} \otimes \mathbf{a}$. The discussion below is excerpted and lightly edited from § Vector Kronecker Product in Mathematics for AI and Machine Learning.

For vectors $\mathbf a \in \mathbb{R}^{m \times 1}$ and $\mathbf b \in \mathbb{R}^{n \times 1}$, the Kronecker product is:

This is equivalent to the outer product $\mathbf a \mathbf b^\top$ when reshaped appropriately.

What this drawing shows

What you see. Represents the identity connecting Kronecker products with vectorized matrix multiplication.

In the mind map. Chapter 10 — Vector Kronecker Product. See From the book above for definitions, figures, and worked examples.

Where to read next

Open Chapter 10 companion →

Read the full definitions, figures, and worked examples in Chapter 10: Matrix Block Partitioning — see the mind-map node Vector Kronecker Product.