Several enhancements to gr-trellis and gnuradio-examples/python/channel-coding:

-Added fsm constructor for generating FSM directly from the
generator matrix of binary convolutional codes.
-Added functionality to fsm class to compute the best way to
go from any state to any other state (useful for termination)
-Added soft-in-soft-out (SISO) block for turbo processing
-Added turbo decoding examples



git-svn-id: http://gnuradio.org/svn/gnuradio/trunk@3322 221aa14e-8319-0410-a670-987f0aec2ac5

1 files changed, 2 insertions, 2 deletions

diff --git a/gr-trellis/src/lib/trellis_metrics_X.i.t b/gr-trellis/src/lib/trellis_metrics_X.i.t
index 2fc3ba8ff..1687d8fb4 100644
--- a/gr-trellis/src/lib/trellis_metrics_X.i.t
+++ b/gr-trellis/src/lib/trellis_metrics_X.i.t
@@ -24,12 +24,12 @@
 
 GR_SWIG_BLOCK_MAGIC(trellis,@BASE_NAME@);
 
-@SPTR_NAME@ trellis_make_@BASE_NAME@ (const int O, const int D, const std::vector<@I_TYPE@> &TABLE, trellis_metric_type_t TYPE);
+@SPTR_NAME@ trellis_make_@BASE_NAME@ (int O, int D, const std::vector<@I_TYPE@> &TABLE, trellis_metric_type_t TYPE);
 
 class @NAME@ : public gr_block
 {
 private:
-  @NAME@ (const int O, const int D, const std::vector<@I_TYPE@> &TABLE, trellis_metric_type_t TYPE);
+  @NAME@ (int O, int D, const std::vector<@I_TYPE@> &TABLE, trellis_metric_type_t TYPE);
 
 public:
   int O () const { return d_O; }