Intelligent Information Systems

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Intelligent Information Systems

• Prof. M. Muraszkiewicz
• Institute of Information and Book Studies
• Warsaw University
• mietek_at_n-s.pl

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Neural Nets Module 10
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Table of Contents

• Background
• Historical Note
• Definition
• Properties and Applications

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Background
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Two Tracks in AI
Analytical, symbolic Invented by
researchers (inspired by logics and math J.
von Neumann). Naturalistic Based on
solutions worked out by mother nature through
evolution (inspired by psychology, neurology,
biology, evolution K. Darwin, ...).
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About the Human Brain
If the human brain were so simple that we could
understand it, we would be so simple that we
couldnt. Emmerson M. Pough
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Parameters

• volume 1400 cm3,
• weight 1,5 kG,
• surface 2000 cm2 (the surface of a sphere of
  the same volume is 600 cm2),
• 1010 neurons,
• 1012 glia cells,
• number of connections - 1015 average length
  from 0,01 mm to 1m.
• Neurons receive and send impulses whose frequency
  is
• 1 - 100 Hz, duration 1 - 2 ms, voltage 100 mV
  and speed of propagation 1 - 100 m/s.
• Speed of brain 1018 operations/s (parallel
  processing).
• Informational capacity of senses channels
• -- vision - 100 Mb/s,
• -- touch - 1 Mb/s,
• -- audition - 15 Kb/s,
• -- smell - 1 Kb/s,
• -- taste - 100 b/s. (source R. Tadeusiewicz,
  Sieci neuronowe).

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Historical Note
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Difficult History

• W. McCulloch, W. Pitts first mathematical model
  of a neuron (1943),
• D. Hebb the rule that determines the change in
  the weight connection,
• F. Rosenblatts Perceptron (1957), a two-layer
  network, for recognizing alphanumerical
  characters,
• B. Widrow, M. Hoff ADALINE
• M. Minsky (1969) proved limits of simple neural
  nets which weakened research in the 70ies,
• J. Hopfields Net with a feedback (1982),
• Works by J. Andersona (1988) neural nets
  comeback".

Warren McCulloch 1898-1969
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Definition
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Intuitive Definition
A neural network is a set of simple processors
(neurons) connected in a certain way. A neuron
can have many inputs (synapses) with which
weights can be associated. The value of weights
can be changed during the operation of a network
to produce the desired data flow within it what
makes the network and adaptive device. Topology
of the network and the values of weights
determine the program executed on the network.
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Definition from Wikipedia
An artificial neural network (ANN), often just
called a "neural network" (NN), is an
interconnected group of artificial neurons that
uses a mathematical model or computational model
for information processing based on a
connectionist approach to computation
http//en.wikipedia.org/wiki/Artificial_neural_n
etwork
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Types of Nets
The neurons learn in an iterative way. By
adding an error detector and a feature to change
weights simple nets become to new models such as
ADALINE (ADAptive LINear Element).
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Properties and Applications
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Main Properties

• Advantages
• adaptiveness and self-organization
• parallel processing,
• learning (supervised and unsupervised)
• fault tolerance
• Disadvantages
• non-explicability
• slow

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Type of Applications

• prediction
• optimization
• classification
• pattern and sequence recognition
• data analysis and association,
• filtering
• ...

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Examples of Applications

• Speech analysis
• Planning of learning progress
• Analysis of production problems
• Trade activities optimization
• Spectral analysis
• Optimization of wastes utilization
• Selection of row materials
• Forensic support
• Staff recruitment support
• Industrial processes control
• ...

• Diagnostics of electronic devices
• Psychiatric research
• Stock exchange predictions
• Sales predictions
• Search for oil fields
• Interpretation of biological research
• Prices prediction
• Analysis of medical data
• Planning of machines maintenance

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Readings

• Haykin S., Neural Networks A Comprehensive
  Foundation (3rd Edition), Prentice Hall, 2007.
• Lawrence, J., Introduction to Neural Networks,
  California Scientific Software Press, 1994.
• Royas R., Neural Networks A Systematic
  Introduction, Springer, 1996.
• http//en.wikipedia.org/wiki/Neural_networks
• http//en.wikipedia.org/wiki/Artificial_neural_net
  work

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