** Gauss-Newton and Conjugate-Gradient optimization **

This code implements a Gauss-Newton 
optimization of objective functions that can
be iteratively approximated by quadratics.
This approach is particularly appropriate
for least-squares inversions of moderately
non-linear transforms.  You will also find
code for conjugate-gradient and line-search
optimizations.  

Get documentation of the algorithm here:
[[papers/inv/]] [[papers/inv.pdf]] [[papers/inv.ps.gz]] 

See the java documentation in the 
documentation subdirectory [[documentation]].

All files with ``main'' contain test code.
You can run all tests with ``Test.main().''

Here's some advice on how to formulate your problem:
  [[papers/regularization.pdf]] [[papers/regularization/]]