The Control Group was established in 1947 by R.H.Macmillan and was later expanded by J.F. Coales after 1952. Research by the Control Group was first carried out in the areas of mechanical control systems, and later in nonlinear and optimal control with A.T.Fuller, and applications to industrial processes. After 1974 multivariable frequency response methods became a prominent research theme with the appointment of A.G.J. MacFarlane. From the mid 1980s onwards the group was recognized for work in H-infinity control with Prof Keith Glover
Today, the guiding principle of all
research in the laboratory is that a well-designed engineering system
must be based on a sound mathematical model. In this regard, neural
networks represent just one of a wide range of applicable
techniques. Others include stochastic processes such as hidden Markov
models, Bayesian inference, invariant transformations in 3D geometry,
computational geometry, Wiener and Kalman filtering, classification
and regression trees, and genetic algorithms.
A full list of research projects is given
elsewhere , but the principle areas of interest
are as follows:
* Neural networks, pattern recognition and machine learning, including multi-layer perceptrons, radial basis functions, and recurrent networks.
* Signal processing, non-stationary time-series analysis, speech coding and compression.
* Speech recognition using both neural networks and hidden Markov Models. This includes large vocabulary recognition, recognition in noise, speaker adaptation and word spotting.
* Language processing including N-grams, stochastic context-free grammars, grammatical inference, dictionary construction.
* Statistical machine translation
* Image processing and object recognition, including 3-D reconstruction from 2-D images, image segmentation, and face recognition.
* Visual navigation of mobile robots and task level and sensor-based robot control within an unstructured environment.
* Aspects of robot assembly including path planning, hand-eye coordination and quality inspection using computer vision, man-machine interfaces using visual gestures.
* Aspects of medical imaging, including the acquisition, visualisation, registration and segmentation of 3D ultrasound images for medical diagnosis.
* Risk analysis in various aspects of health care.
In addition to supporting a large post-graduate research activity, the
Machine Intelligence Laboratory is also responsible for a
Masters course in Advanced Computer Science
and undergraduate teaching in the areas of computing and pattern
processing. The Masters course is a one year course run jointly with
the Computer Laboratory. It has an annual enrolment of around 20
students and its aim is to teach both the theory and practice of
speech and language processing systems. Topics covered include speech
analysis, recognition and synthesis; syntax and parsing; semantics and
discourse analysis; and perception and psycholinguistics. The course
consists of two terms of taught lectures and practicals followed by a
three month thesis project. It operates with the support of
EPSRC and
it has close links with UK industry via an industrial advisory board.
At the undergraduate level, the laboratory is involved in the teaching
of information engineering and computing generally. It is responsible
for a 3rd year paper covering computing, artificial intelligence and
pattern recognition, and it runs specialist modules in the 4th year on
medical imaging, 3d computer graphics, statistical pattern processing,
speech processing, computer vision and robotics.
-- Main.rff22 - 29 Jan 2013
research in the laboratory is that a well-designed engineering system
must be based on a sound mathematical model. In this regard, neural
networks represent just one of a wide range of applicable
techniques. Others include stochastic processes such as hidden Markov
models, Bayesian inference, invariant transformations in 3D geometry,
computational geometry, Wiener and Kalman filtering, classification
and regression trees, and genetic algorithms.
A full list of research projects is given
elsewhere , but the principle areas of interest
are as follows:
* Neural networks, pattern recognition and machine learning, including multi-layer perceptrons, radial basis functions, and recurrent networks.
* Signal processing, non-stationary time-series analysis, speech coding and compression.
* Speech recognition using both neural networks and hidden Markov Models. This includes large vocabulary recognition, recognition in noise, speaker adaptation and word spotting.
* Language processing including N-grams, stochastic context-free grammars, grammatical inference, dictionary construction.
* Statistical machine translation
* Image processing and object recognition, including 3-D reconstruction from 2-D images, image segmentation, and face recognition.
* Visual navigation of mobile robots and task level and sensor-based robot control within an unstructured environment.
* Aspects of robot assembly including path planning, hand-eye coordination and quality inspection using computer vision, man-machine interfaces using visual gestures.
* Aspects of medical imaging, including the acquisition, visualisation, registration and segmentation of 3D ultrasound images for medical diagnosis.
* Risk analysis in various aspects of health care.
In addition to supporting a large post-graduate research activity, the
Machine Intelligence Laboratory is also responsible for a
Masters course in Advanced Computer Science
and undergraduate teaching in the areas of computing and pattern
processing. The Masters course is a one year course run jointly with
the Computer Laboratory. It has an annual enrolment of around 20
students and its aim is to teach both the theory and practice of
speech and language processing systems. Topics covered include speech
analysis, recognition and synthesis; syntax and parsing; semantics and
discourse analysis; and perception and psycholinguistics. The course
consists of two terms of taught lectures and practicals followed by a
three month thesis project. It operates with the support of
EPSRC and
it has close links with UK industry via an industrial advisory board.
At the undergraduate level, the laboratory is involved in the teaching
of information engineering and computing generally. It is responsible
for a 3rd year paper covering computing, artificial intelligence and
pattern recognition, and it runs specialist modules in the 4th year on
medical imaging, 3d computer graphics, statistical pattern processing,
speech processing, computer vision and robotics.
-- Main.rff22 - 29 Jan 2013