**Reconstructability Analysis **

**with**

** Fourier Transforms**

#### Martin Zwick

* *

**Abstract**

Fourier
methods used in 2- and 3-dimensional image reconstruction can be used also in
reconstructability analysis (RA). These
methods maximize a variance-type measure instead of information-theoretic
uncertainty, but the two measures are roughly colinear and the Fourier approach
yields results close to those of standard RA.
The Fourier method, however, does not require iterative calculations for
models with loops. Moreover the error in
Fourier RA models can be assessed without actually generating the full probability
distributions of the models; calculations scale with the size of the data
rather than the state space. State-based
modeling using the Fourier approach is also readily implemented. Fourier methods may thus enhance the power of
RA for data analysis and data mining.

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