Conditions for robust stability of analog VLSI implementation of neural networks with uncertain circuit parasitics

An analog VLSI implementation of neural networks has been modeled in terms of active cell impedance connected to a resistive grid. The resistive grid can be characterized in terms of the nominal linear component and the parasitic component with uncertain parametric values. Necessary and sufficient conditions for the nominal and robust stability of these systems can then be derived.<
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