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Title: Quantum Neural Network Training Algorithm
Authors: Kumar, Mukesh
Supervisor: Singh, V. P.
Keywords: Quantum Neural Network, Artificial Neural Network, Quantum Theory,MatLab
Issue Date: 3-Aug-2009
Abstract: Abstract Quantum neural networks(QNN) refers to the class of neural network models, artificial or biological, which rely on principles inspired in some way from quantum mechanics. Many quantum neural networks have been proposed in the literature, but very few of these proposals have attempted to provide an in-depth method of training them. Most either do not mention how the network will be trained. This assumes that training a quantum neural network will be straightforward and analogous to classical methods. Several different network structures have been proposed. Several of these networks also employ methods, which are speculative or difficult to do in quantum systems. These significant differences between classical networks and quantum neural networks, as well as the problems associated with quantum computation itself, require to more deeply at the issue of training quantum neural networks. The training of quantum neural network by different algorithm/method in the Matlab enviourment has been proposed and validated the some with data of viechle classification problem.
Appears in Collections:Masters Theses@CSED

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