Analog VLSI and neural systems
Analog VLSI and neural systems
Low-power analog fuzzy rule implementation based on a linear MOS transistor network
MICRONEURO '96 Proceedings of the 5th International Conference on Microelectronics for Neural Networks and Fuzzy Systems
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Networks of resistors have been identified as interesting devices for analog computation. Since the analytical model of a network of constant resistors is a set of linear equations, such a circuit can be used to solve a large number of linear equations concurrently. Whenever such a resistive embodiment of a computational problem can be found, the resulting circuit is usually very simple, fast and dense compared to CPU-based hardware. Particular problems solved by such networks include simulation of electromagnetic fields, linear image filtering, regularization for image processing, and D/A conversion. Networks of resistors are especially attractive for CMOS integrated circuits, since it has been shown that a circuit obtained by replacing every resistor by a single MOS transistor has exactly the same branch currents as its resistive counterpart.