# HG changeset patch
# User peterf
# Date 1331963429 0
# Node ID 3fa185431bbcfa8817dfe84a860a4709edc40c06
# Parent  a8df4a4abe89e3e2813d473bc1e7ca81ccb3dd02
Ref

diff -r a8df4a4abe89 -r 3fa185431bbc draft.tex
--- a/draft.tex	Sat Mar 17 05:43:34 2012 +0000
+++ b/draft.tex	Sat Mar 17 05:50:29 2012 +0000
@@ -778,7 +778,18 @@
 
 	 We are currently working towards methods for the computation of predictive information
 	 rate in some restricted classes of Gaussian processes including finite-order
-	 autoregressive models and processes with power-law spectra (fractionally integrated Gaussian noise). %(fBm continuous vs fiGn discrete time)
+	 autoregressive models and processes with power-law spectra (fractionally integrated Gaussian noise).
+	 
+%	 %(fBm (continuous), fiGn discrete time) possible reference:
+%			@book{palma2007long,
+%		  title={Long-memory time series: theory and methods},
+%		  author={Palma, W.},
+%		  volume={662},
+%		  year={2007},
+%		  publisher={Wiley-Blackwell}
+%	}
+
+
 
 %	 mention non-gaussian processes extension Similarly, the predictive information
 %	 rate may be computed using a Gaussian linear formulation CITE. In this view,