Oxford BioSignals apply their advanced neural
network technology in application areas where expert
knowledge exists as to diagnostic processes but where
very few rules can be explicitly defined. The technology
is particularly suitable for domains where large quantities
of data exist and where it can be difficult or tedious
to monitor and classify multiple complex signals simultaneously.
- Learning from Experience - Neural
networks are particularly suited to problems where
a precise solution is difficult to specify but where
a large amount of example data is available which can
be used to learn the relationship between input and
output.
- Generalising from examples -
With careful design it is possible to train a neural
network so that it will give the correct response
to input data which has not been encountered previously
- the ability to generalise.
- Efficiency - Although the training
process is computationally intensive the requirements
of a fully trained network are much less and can
be run efficiently on low performance devices.
- Non linearity - Neural networks
are non-linear systems giving them an advantage
when dealing with complex, real-world problems.
Understand
more about our technology.
Oxford BioSignals' are designed
to automate the monitoring process for complex multiple
signal systems. These solutions are developed to reduce
habituation and complexity in tedious monitoring tasks
and to provide users with insights into the performance
of their equipment. Read more about the application
of our technology in Aero Engines and Industrial
Processes.
discover
how our technology is applied in engineering
applications.
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Aero Engine
