The complexity of recurrent neural computations
Serge Shumsky · 2002
The paper considers the amount of information processed in recurrent neural networks with random interconnections. The complexity of computations is defined as the number of neurons switchings during the run. The variety of neurons in the network gives rise to distribution of computational complexity. The author calculates this complexity distribution, and finds the limits of complexity in the individual algorithms.