Difference: ControlOverview (1 vs. 9)

Historically, Cambridge has links with the early development of control theory through James Clerk Maxwell and Edward John Routh. Maxwell's 1868 paper "On Governors" is often considered to be the start of control theory in the modern sense, while Routh's Adams prize essay of 1877 derived his well-known stability criterion. Routh and Maxwell were, famously, senior and second wrangler in the Cambridge Mathematical Tripos of 1854 and were declared first equal in the Smith's prize examination. Routh remained in Cambridge as a private tutor (coach) for the mathematical tripos, while Maxwell held chairs at Aberdeen and King's College London before returning to Cambridge as first Cavendish Professor in 1871.

Historically, Cambridge has links with the early development of control theory through James Clerk Maxwell and Edward John Routh. Maxwell's 1868 paper "On Governors" is often considered to be the start of control theory in the modern sense, while Routh's Adams prize essay of 1877 derived his well-known stability criterion. Routh and Maxwell were, famously, senior and second wrangler in the Cambridge Mathematical Tripos of 1854 and were declared first equal in the Smith's prize examination. Routh remained in Cambridge as a private tutor (coach) for the mathematical tripos, while Maxwell held chairs at Aberdeen and King's College London before returning to Cambridge as first Cavendish Professor in 1871.

Historically, Cambridge has links with the early development of control theory through James Clerk Maxwell and Edward John Routh. Maxwell's 1868 paper "On Governors" is often considered to be the start of control theory in the modern sense, while Routh's Adams prize essay of 1877 derived his well-known stability criterion. Routh and Maxwell were, famously, senior and second wrangler in the Cambridge Mathematical Tripos of 1854 and were declared first equal in the Smith's prize examination. Routh remained in Cambridge as a private tutor (coach) for the mathematical tripos, while Maxwell held chairs at Aberdeen and King's College London before returning to Cambridge as first Cavendish Professor in 1871.

Further reading:

• A.T. Fuller, Obituary, International Journal of Control, vol. 73, no. 6, 457-463, 2000
  
• Routh, Edward John (1831-1907), Oxford Dictionary of National Biography
  
• Maxwell, James Clerk (1831-1879), Oxford Dictionary of National Biography
  

Historically, Cambridge has links with the early development of control theory through James Clerk Maxwell and Edward John Routh. Maxwell's 1868 paper "On Governors" is often considered to be the start of control theory in the modern sense, while Routh's Adams prize essay of 1877 derived his well-known stability criterion. Routh and Maxwell were, famously, senior and second wrangler in the Cambridge Mathematical Tripos of 1854 and were declared first equal in the Smith's prize examination. Routh remained in Cambridge as a private tutor (coach) for the mathematical tripos, while Maxwell held chairs at Aberdeen and King's College London before returning to Cambridge as first Cavendish Professor in 1871.

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.