0000000000026310

AUTHOR

Teemu Antti-poika

showing 2 related works from this author

On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets

2000

We investigate the computational properties of finite binary- and analog-state discrete-time symmetric Hopfield nets. For binary networks, we obtain a simulation of convergent asymmetric networks by symmetric networks with only a linear increase in network size and computation time. Then we analyze the convergence time of Hopfield nets in terms of the length of their bit representations. Here we construct an analog symmetric network whose convergence time exceeds the convergence time of any binary Hopfield net with the same representation length. Further, we prove that the MIN ENERGY problem for analog Hopfield nets is NP-hard and provide a polynomial time approximation algorithm for this p…

Computational complexity theoryCognitive NeuroscienceComputationBinary numberHopfield networkTuring machinesymbols.namesakeRecurrent neural networkArts and Humanities (miscellaneous)Convergence (routing)symbolsTime complexityAlgorithmMathematicsNeural Computation
researchProduct

Some Afterthoughts on Hopfield Networks

1999

In the present paper we investigate four relatively independent issues, which complete our knowledge regarding the computational aspects of popular Hopfield nets. In Section 2 of the paper, the computational equivalence of convergent asymmetric and Hopfield nets is shown with respect to network size. In Section 3, the convergence time of Hopfield nets is analyzed in terms of bit representations. In Section 4, a polynomial time approximate algorithm for the minimum energy problem is shown. In Section 5, the Turing universality of analog Hopfield nets is studied. peerReviewed

TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESQuantitative Biology::Neurons and CognitionComputer scienceParallel algorithmHopfield netsApproximation algorithmSection (fiber bundle)Hopfield networknetworksHopfieldAlgorithmTime complexityEquivalence (measure theory)Energy (signal processing)
researchProduct