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The NFA model can be extended to model the nonlinear dynamics of the
factors [20,65,63,64]
x(t) |
= |
f(s(t)) + n(t) |
(2.15) |
s(t) |
= |
g(s(t-1)) + m(t) , |
(2.16) |
where the
m(t) is called process noise or innovation
process. The mapping
g modelling the dynamics is handled
somewhat similarly as the mapping
f. Experiments
[65,63] have given good results in prediction of
artificial time series compared to traditional time series methods.
Tapani Raiko
2001-12-10