time

[Thomas Petsche]

Masahide.Nomura wrote:
>In fact, both feedforward nets and Poggio's technique can be used to
>realize multidimensional mappings. The difference lies in the robustness.
>While a feedforward net mapping can be badly degraded by the loss of a
>neuron, the mapping is only locally degraded with Poggio's technique.

But this is not a property of a feedforward network (or RBF's for that
matter).  For FF nets, the lack of predictable and dependable fault
tolerance is a property of `vanilla' back prop.  For backprop with
weight decay, we can accurately predict that the network will be
completely INtolerant to any faults.  OTOH, it is quite possible to
obtain a fault tolerant feedforward network by (1) designing a fault
tolerant generic network which can then be trained [1] or (2) modifying
backprop to encourage fault tolerant representations [as yet 
unpublished work by other researchers].

[1] @article{petsche-dickinson-1990,
	   author = {T. Petsche and B.W. Dickinson},
	   journal = {IEEE Transactions on Neural Networks},
	   month = jun,
	   number = {2},
	   pages = {154--166},
	   title = {Trellis Codes, Receptive Fields, and Fault-Tolerant,
		 Self-Repairing Neural Networks},
	   volume = {1},
	   year = {1990},
	   note={Errata for eqn 1 available from first author.}
	}