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About Hull 2411 Document
This document summarizes a thesis submitted for the degree of Doctor of Philosophy at the University of Hull. The thesis proposes a quantum recurrent neural network (QRNN) approach for stochastic filtering. The QRNN filter is based on solving the Schrödinger wave equation to model the time-varying probability density function of observed signals. Key objectives of the research include solving the wave equation numerically, designing the network architecture, and investigating how waves propagate through the network. The QRNN approach provides an intelligent filtering framework analogous to real neural dynamics. The thesis evaluates the QRNN filter's performance on simulated signals and applications to real-world chaotic and blood sugar time series data.
Detailed Information
| Author: | ['Azad Uddin Ahmed'] |
|---|---|
| Publication Year: | 2010 |
| Pages: | 148 |
| Language: | English |
| Format: | |
| Price: | FREE |
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