VLSI implementation of neural networks : a switched capacitor approach

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Copyright: Jackson, Geoffrey Bruce
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Abstract
Recent research has indicated that Neural Networks may offer powerful and effective solutions to certain classes of problems which von Neumann machines do not handle effectively. These problems include the areas of visual and speech recognition. This thesis describes the basic principles behind neural networks and neural network implementation. The main aim of the thesis is to investigate the implementation of neural networks in silicon integrated technology. To this end the design of a CMOS VLSI test neural network is described and the problems of VLSI implementation discussed. The neural network design utilizes switched\capacitor techniques to implement the basic McCulloch-Pitts neuron. A test chip has been fabricated using this circuit technique and tested successfully. Comparisons between the switched capacitor technique and other neural network implementations are also discussed.
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Author(s)
Jackson, Geoffrey Bruce
Supervisor(s)
Rigby, G. A.
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Publication Year
1992
Resource Type
Thesis
Degree Type
Masters Thesis
UNSW Faculty
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download Jackson-010130942.pdf 6.3 MB Adobe Portable Document Format
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