On Computations with Pulses
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 quite high if the pulses arriving at a computational unit have an approximately linearly rising or linearly decreasing initial segment. This property is satisfied by common models for biological neurons. On the other hand, several implementations of pulse stream VLSI employ pulses that are approximately piecewise constant (i.e., step functions). In this article we investigate the relevance of the shape of pulses in formal models for computation with pulses. The results show that the computational power drops significantly if one replaces pulses with linearly rising or decreasing initial segments by piecewise constant pulses. We provide an exact characterization of the latter model in terms of a weak version of a random access machine (RAM). We also compare the language recognition capability of a recurrent version of this model with that of deterministic finite automata and Turing machines.