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Electronic Colloquium on Computational Complexity

Under the auspices of the Computational Complexity Foundation (CCF)

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Reports tagged with analog computation:
TR00-002 | 23rd December 1999
Michael Schmitt

Lower Bounds on the Complexity of Approximating Continuous Functions by Sigmoidal Neural Networks

We calculate lower bounds on the size of sigmoidal neural networks
that approximate continuous functions. In particular, we show that
for the approximation of polynomials the network size has to grow
as $\Omega((\log k)^{1/4})$ where $k$ is the degree of the polynomials.
This bound is ... more >>>

TR00-086 | 26th September 2000
Michael Schmitt

On the Complexity of Computing and Learning with Multiplicative Neural Networks

In a great variety of neuron models neural inputs are
combined using the summing operation. We introduce the concept of
multiplicative neural networks which contain units that multiply
their inputs instead of summing them and, thus, allow inputs to
interact nonlinearly. The class of multiplicative networks
comprises such widely known ... more >>>

TR06-137 | 13th November 2006
Prashant Joshi, Eduardo D. Sontag

Computational aspects of feedback in neural circuits

It had previously been shown that generic cortical microcircuit
models can perform complex real-time computations on continuous
input streams, provided that these computations can be carried out
with a rapidly fading memory. We investigate in this article the
computational capability of such circuits in the ... more >>>

ISSN 1433-8092 | Imprint