Information Theory, Inference, and Learning ... - MAELabs UCSD

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About Chapter 31
Some of the neural network models that we will encounter are related to Ising
models, which are idealized magnetic systems. It is not essential to understand
the statistical physics of Ising models to understand these neural networks, but
I hope you’ll find them helpful.
Ising models are also related to several other topics in this book. We will
use exact tree-based computation methods like those introduced in Chapter
25 to evaluate properties of interest in Ising models. Ising models offer crude
models for binary images. And Ising models relate to two-dimensional constrained
channels (cf. Chapter 17): a two-dimensional bar-code in which a
black dot may not be completely surrounded by black dots, and a white dot
may not be completely surrounded by white dots, is similar to an antiferromagnetic
Ising model at low temperature. Evaluating the entropy of this Ising
model is equivalent to evaluating the capacity of the constrained channel for
conveying bits.
If you would like to jog your memory on statistical physics and thermodynamics,
you might find Appendix B helpful. I also recommend the book by
Reif (1965).
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