Analog VLSI hardware for fuzzy systems

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