Berthold Ruf

Recently one has started to investigate the

computational power of spiking neurons (also called ``integrate and

fire neurons''). These are neuron models that are substantially

more realistic from the biological point of view than the

ones which are traditionally employed in artificial neural nets.

It has turned out that the ...
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The computational power of formal models for

networks of spiking neurons is compared with

that of other neural network models based on

McCulloch Pitts neurons (i.e. threshold gates)

respectively sigmoidal gates. In particular it

is shown that networks of spiking neurons are

...
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Michael Schmitt

Spiking neurons are models for the computational units in

biological neural systems where information is considered to be encoded

mainly in the temporal pattern of their activity. In a network of

spiking neurons a new set of parameters becomes relevant which has no

counterpart in traditional ...
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We explore the computational power of formal models for computation

with pulses. Such models are motivated by realistic models for

biological neurons, and by related new types of VLSI (``pulse stream

VLSI'').

In preceding work it was shown that the computational power of formal

models for computation with pulses is ...
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Michael Schmitt

We study networks of spiking neurons that use the timing of pulses

to encode information. Nonlinear interactions model the spatial

groupings of synapses on the dendrites and describe the computations

performed at local branches. We analyze the question of how many

examples these networks must ...
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