Browsing by Subject "backpropagation"
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Publisher and Date:(IEEE-INST Electrical Electronics Engineers Inc, 2001)Analog techniques are desirable for hardware implementation of neural networks due to their numerous advantages such as small size low power and high speed. However these advantages are often offset by the difficulty in the training of analog neural network circuitry. In particular training of the circuitry by software based on hardware models is impaired by statistical variations in the integrated circuit production process resulting in performance degradation. In this paper a new paradigm of ...