Operations Research/Computer Science Interfaces Series Mathematics of Neural Networks

The conference organisers were John Mason (Huddersfield) and Steve Ellacott (Brighton), supported by a programme committee consisting of Nigel Allinson (UMIST), Norman Biggs (London School of Economics), Chris Bishop (Aston), David Lowe (Aston), Patrick Parks (Oxford), John Taylor (King's College, Lon­ don) and Kevin Warwick (Reading). This text examines the mathematics, probability, statistics, and computational theory underlying neural networks and their applications. In addition to the theoretical work, the book covers a considerable range of neural network topics such as learning and training, neural network classifiers, memory-based networks, self-organizing maps and unsupervised learning, Hopfeld networks, radial basis function networks, and general network modelling and theory. Added to the book's mathematical and neural network topics are applications in chemistry, speech recognition, automatic control, nonlinear programming, medicine, image processing, finance, time series, and dynamics. As a result, the book surveys a wide range of recent research on the theoretical foundations of creating neural network models in a variety of application areas.