Self-organising maps Structure Self-organising map, SOM, (Kohonen feature map, according to its inventor) 1 has two layers: the input layer and the competitive layer. The competitive layer consists usually of a pre-defined two-dimensional rectangular or hexagonal grid of nodes or neurons. These two layers are fully interconnected: all input neurons are connected to all competitive
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- Introduction to forest-based bioeconomy
- Wood products
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Self-organising maps
After reading this article you will..
- understand the basic principle of Self-Organising Maps and their learning.
Content
Process control and automation
- Introduction to process control and automation
- Development of process automation
- Fibre process automation
- Chemical recovery as a control object
- Advances in paper machine automation
- Paper machine as a dynamical system
- Tasks in paper machine control and management
- Control of stock flow concentration and quality
- Machine direction control
- Cross-directional control – The static optimisation
- Cross-directional control – Dynamics
- Cross-directional control – further aspects
- Controlling functional paper properties
- Managing grade chances in the paper machine
- Managing disturbances caused by broke and recovered solids
- Millwide systems
- Modelling and control methods
Authors & references
Authors:
Professor Emeritus Kauko Leiviskä, University of Oulu
References:
- Kohonen, T. 1987. Self-Organization and Associative Memory. 2nd edition, Springer, Berlin, 1987.
- Dayhoff, J. E. 1990. Neural network architectures. Van Nostrand Reinhold, New York. p. 259.
Videos
Exercises
This page has been updated 25.11.2020
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