6533b7d4fe1ef96bd1262a49

RESEARCH PRODUCT

On the effect of analog noise in discrete-time analog computations

Pekka OrponenWolfgang Maass

subject

Computational modelFinite-state machineArtificial neural networkComputer scienceCognitive NeuroscienceComputationanalog noiseAnalog signal processingUpper and lower boundsArts and Humanities (miscellaneous)Discrete time and continuous timeNoise (video)Algorithmanalog computations

description

We introduce a model for analog computation with discrete time in the presence of analog noise that is flexible enough to cover the most important concrete cases, such as noisy analog neural nets and networks of spiking neurons. This model subsumes the classical model for digital computation in the presence of noise. We show that the presence of arbitrarily small amounts of analog noise reduces the power of analog computational models to that of finite automata, and we also prove a new type of upper bound for the VC-dimension of computational models with analog noise.

https://research.aalto.fi/en/publications/36bfbba3-9899-4d61-9af2-30b1accd7366