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If the
connectivity has directed cycles, the network can
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do much more
than just computing a fixed sequence of
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non-linear
transforms:
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It
can oscillate. Good for motor control?
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It
can settle to point attractors.
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Good
for classification
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It
can behave chaotically
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But
that is usually a bad idea for information processing.
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It
can remember things for a long time.
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The
network has internal state. It can decide to ignore the
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input
for a while if it wants to.
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It
can model sequential data in a natural way.
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No
need to use delay taps to spatialize time.
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