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Junior Member (25+)
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Analog VLSI hardware for fuzzy systems
Our world has an analog nature and it is natural to process signals in an analog way. Analog signal processing can be much faster than digital ones and AD or DA conversion is not required. The main obstacle is to develop adequate circuits for nonlinear signal processing. In the presentation several new circuits are proposed. These circuits use nonlinear characteristics of MOS transistors for nonlinear signal processing. The fuzzy signal processing is used as an example. The proposed fuwier circuits are relatively simple while almost arbitrary shapes of membership functions can be obtained. The proposed current mode MAX and MIN operators exhibit accuracy superior to other circuits. The defudier circuit uses the concept of signal normalization and weighted sum. New normalization circuit, operating in the subthreshold conduction mode, exhibits almost ideal characteristics. The described new building blocks were used to design the entire analog fuzzy VLSI chip. mode, which means that the current not voltage carries the information.right? Numerous applications of industrial. electronics use intelligent control systems. For example many motor control systems require sophisticated computation. The intelligence is also involved in smart sensors that are able to measure flux and other electrical parameters just by analyzing currents and voltages on the supply terminals. Hardware implementation of intelligent systems use computers or microcomputers for the computation. The digital approach has many advantages. Primarily it is flexible and easy to be reprogrammed. At the same time those digital systems are rather complex and they require analog to digital conversion at the front of the system and digital to analog conversion at its end. Our world has an analog nature and it would be wise to perform all computation in analog fashion. Refer: IEEE paper Regards Roy S Mtech Electronic Research And Development Centre Of India Trivandrum ![]()
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