@article{siegelmann_computational_1995,
title = {On the {Computational} {Power} of {Neural} {Nets}},
volume = {50},
issn = {0022-0000},
url = {http://www.sciencedirect.com/science/article/pii/S0022000085710136},
doi = {10/dvwtc3},
abstract = {This paper deals with finite size networks which consist of interconnections of synchronously evolving processors. Each processor updates its state by applying a "sigmoidal" function to a linear combination of the previous states of all units. We prove that one may simulate all Turing machines by such nets. In particular, one can simulate any multi-stack Turing machine in real time, and there is a net made up of 886 processors which computes a universal partial-recursive function. Products (high order nets) are not required, contrary to what had been stated in the literature. Non-deterministic Turing machines can be simulated by non-deterministic rational nets, also in real time. The simulation result has many consequences regarding the decidability, or more generally the complexity, of questions about recursive nets.},
language = {en},
number = {1},
urldate = {2019-11-28},
journal = {Journal of Computer and System Sciences},
author = {Siegelmann, H. T. and Sontag, E. D.},
month = feb,
year = {1995},
note = {ZSCC: 0000002},
keywords = {Classical ML, Machine learning},
pages = {132--150}
}