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Control problems offer an industrially important application and a
guide to understanding control systems for those working in Neural
Networks. Neural Systems for Control represents the most up-to-date
developments in the rapidly growing aplication area of neural
networks and focuses on research in natural and artifical neural
systems directly applicable to control or making use of modern
control theory. The book covers such important new developments in
control systems such as intelligent sensors in semiconductor wafer
manufacturing; the relation between muscles and cerebral neurons in
speech recognition; online compensation of reconfigurable control
for spacecraft aircraft and other systems; applications to rolling
mills, robotics and process control; the usage of past output data
to identify nonlinear systems by neural networks; neural
approximate optimal control; model-free nonlinear control; and
neural control based on a regulation of physiological
investigation/blood pressure control. All researchers and students
dealing with control systems will find the fascinating Neural
Systems for Control of immense interest and assistance.
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