Title :
Analog quantum neuron for functions approximation
Author :
Ezhov, A.A. ; Khromov, A.G. ; Berman, G.P.
Author_Institution :
Troitsk Inst. of Innovation & Fusion Res., Moscow, Russia
Abstract :
We describe a system which is able to perform universal stochastic approximations of continuous multivariable functions in both neuron-like and quantum manner. The implementation of this model in the form of multi-barrier multiple-silt system has been earlier proposed. For the simplified waveguide variant of this model it is proved, that the system can approximate any continuous function of many variables. This theorem is also applied to the 2-input quantum neural model analogical to the schemes developed for quantum control
Keywords :
function approximation; mathematics computing; neural nets; quantum computing; analog quantum neuron; functions approximation; multivariable continuous functions; quantum computation; quantum neural model; Analog computers; Artificial neural networks; Computer architecture; Function approximation; Hardware; Information processing; Neurons; Quantum computing; Quantum mechanics; Stochastic systems;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939600
