### Nonlinear noise reduction

`project -m# -q# -r# -k# [-i# -o` outfile`-l# -x# -c# -V# -h]` file

> `-m` embedding dimension
> `-q` dimension of manifold
> `-r` radius of neighbourhoods
> `-k` minimal number of neighbours
> `-i` number of iterations (1)
> `-l` number of values to be read (all)
> `-x` number of values to be skipped (0)
> `-c` column to be read (1 or file,#)
> `-o` output file name, just `-o` means file`_c`, file`_cc` (etc.)
> `-V` verbosity level (0 = only fatal errors)
> `-h` show this message

> verbosity level (add what you want):

> 1 = input/output
> 2 = state of neighbour search

Performs nonlinear projective noise reduction. Output file (the cleaned sequence) is file`_c[ccc]` (one letter `c` per iteration). As a second column, the difference between original and cleaned sequence is printed.

Note: This routine is largely redundant with ghkss.

This routine is based on

> P. Grassberger, R. Hegger, H. Kantz, C. Schaffrath, and T. Schreiber,
> On noise reduction methods for chaotic data,
> Chaos 3, 127 (1993);
> Reprinted in: E. Ott, T. Sauer, and J. A. Yorke, eds.,
> Coping With Chaos, Wiley, New York (1994)

### Usage example

Try also just running: `gnuplot project.gnu` in the `examples` directory.

    > henon -l10000 > data
    > addnoise -v0.02 data
    > project -m7 -q2 -r0.05 -k20 -i3 data_noisy

    gnuplot> plot '< cat data_noisy | delay'
    gnuplot> plot '< cat data_noisy_ccc | delay'

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