Abstract
A ‘mixed’-mode neural network is one in which the neuronal states are represented by voltages and the synaptic signals are conveyed by currents. This results in a lower complexity circuit since the synaptic resistances are not required. The present chapter discusses a mixed-mode variant of the voltage-mode linear equation solver presented in the previous chapter. The Differential Voltage Current Conveyor (DVCC) has been used as the analog building block to realize a voltage comparator with current outputs. Further, a digitally programmable version of the mixed-mode circuit is also presented and a mechanism to adjust the weights corresponding to the coefficients in the set of linear equations is also discussed. Effect of deviations from ideal device behaviour, like offsets in the DVCC and opamps, is also explored.
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Ansari, M.S. (2014). Mixed-Mode Neural Circuit for Solving Linear Equations. In: Non-Linear Feedback Neural Networks. Studies in Computational Intelligence, vol 508. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1563-9_4
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DOI: https://doi.org/10.1007/978-81-322-1563-9_4
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