Neural Systems for Control358 pages | 1997 | PDF | 15,8 Mb
Through the years artificial neural networks (Prank Rosenblatt's perceptrons,Bernard Widrow's adalines, Albus' CMAC) have been invented with both biological ideas and control applications in mind, and the theories of the brain and nervous system have used ideas from control system theory (e.g. Norbert Wiener's cybernetics). This book attempts to show how the control system and neural network researchers of the present day are cooperating.
Since members of both communities like signal flow charts, I will use a few of these schematic diagrams to introduce some basic ideas. Figure 1 is a stereotypical control system. (The dashed lines with arrows indicate the flow of signals; E is a summing junction where the feedback is subtracted from the command to obtain an error signal.)
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