Search results for " Artificial Neural networks"

showing 1 items of 11 documents

The computational power of continuous time neural networks

1997

We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.

TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESQuantitative Biology::Neurons and CognitionComputational complexity theoryArtificial neural networkComputer sciencebusiness.industryComputer Science::Neural and Evolutionary ComputationNSPACEComputational resourcePower (physics)Turing machinesymbols.namesakeCellular neural networksymbolsArtificial intelligenceTypes of artificial neural networksbusiness
researchProduct