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- G. A. Kohring
- Advances in Complex Systems
- 2009

Two large, open source software systems are analyzed from the vantage point of complex adaptive systems theory. For both systems, the full dependency graphs are constructed and their properties are shown to be consistent with the assumption of stochastic growth. In particular, the afferent links are distributed according to Zipf's law for both systems.… (More)

1 Summary of the review This is a cool book about a cool problem in the cool field of computational complexity, or so the cool author would have us believe. Unfortunately, apart from a glibly prose, little attempt has been made to reach those not in the know, thereby leaving the uncool, non-expert out in the cold. In short, if you are a computer scientist… (More)

- G A Kohring
- 2007

Artiicial neurons with arbitrarily complex internal structure are introduced. The neurons can be described in terms of a set of internal variables, a set activation functions which describe the time evolution of these variables and a set of characteristic functions which control how the neurons interact with one another. The information capacity of… (More)

- Heinz-Gerd Hegering, Axel Lehmann, +26 authors Joerg Stachowiak
- GI Jahrestagung
- 2008

- R Knecht, G A Kohring
- 2007

The parallelization of distinct element models is discussed with particular attention being paid to the problem of load balancing. One method for solving the load balancing problem through the use of a local, dynamic procedure is given and an implementation on the Cray-T3D and the Intel Paragon is described. The theoretical issues surrounding the load… (More)

- G A Kohring
- 2007

Symmetric Boolean functions form an important subclass of all Boolean functions, with the parity (or XOR) function being perhaps the best know example. In this paper we prove that it is possible to construct a three layer wavelet neural network capable of learning any symmetric Boolean function using a simple perceptron type learning algorithm. For the… (More)

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