0000000000026308

AUTHOR

Jiří ŠíMa

0000-0001-8248-9425

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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
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