Biomedical Engineering Reference
In-Depth Information
40
40
35
35
T
f
= 20
T
f
= 20
T
f
=40
30
30
T
f
=40
25
25
20
T
f
=100
20
T
f
=100
15
15
10
10
T
f
= 500
T
f
= 500
5
5
o
o
o
0
0
0
0.5
1
1.5
2
0
0.5
1
1.5
2
a
a
Figure 1.2
Optimal variance
I
l
∗
)
(
against
a for
T
f
=
20
,
40
,
100
,
500. Right is the same as
left, but
T
f
=
20 is shifted towards left with 0.3 units,
T
f
=
40 with 0.2 units, and
T
f
=
100 with 0.1 units.
Acknowledgments:
JF was partially supported by grants from EPSRC (GR/ R54569),
(GR/ S30443), (GR/ S20574) and (GR/ S63830) (U.K.), a grant of the Royal Society
and an exchange grant between U.K. and China of the Royal Society.
References
[1]
Abeles, M. (1990).
Corticonics
, Cambridge Univ. Press: Cambridge, UK.
[2]
Albeverio, S., Feng, J. F., and Qian, M. (1995). Role of noise in neural net-
works.
Phys.Rev.E.
52
: 6593-6606.
[3]
Albright, T.D., Jessell, T.M., Kandel, E.R., and Posner, M.I. (2000). Neural
science: a century of progress and the mysteries that remain.
Cell
100
: s1-s55.
[4]
Applebaum, D. (1996).
Probability and Information
. Cambridge University
Press: Cambridge, UK.
[5]
Arnold, L. (1998).
Random dynamical systems.
Springer-Verlag, Berlin.
[6]
Azouzl, R., and Gray, C.M. (2003). Adaptive coincidence detection and dy-
namic gain control in visual cortical neurons
in vivo
.
Neuron
, in press.
[7]
van Beers, R. J., Baraduc, P., and Wolpert, D.M.(2002). Role of uncertainty in
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