A basic equation, describing the temporal evolution of fields in a chiral medium with Kerr non-linearity is used to study the effects resulting from the combined action of chirality and non-linearity on optical solitons. The spatial chirality effect is characterized through the Born–Fedorov...

Morphological transformations are efficient methods for shape analysis and representation. In this paper two morphological shape descriptors are described for object feature representation. Neural networks are then employed for object recognition and classification. Various coding schemes and...

This paper illustrates how internal model control of nonlinear processes can be achieved by recurrent neural networks, e.g. fully connected Hopfield networks. It is shown that using results developed by Kambhampati et al. (1995), that once a recurrent network model of a nonlinear system has been...

Control of the precalcination degree in the precalciner of cement plants is a problem of great importance due to its effect to the quality of the clinker, the consumed energy and the byproducts of the whole cement pyroprocess. Divergence of the desired precalcination degree of the raw mix may...

Investigations were conducted to explore the feasibility of a prototype charge simulation retina machine vision system to identify shape and size, when different three-dimensional objects were arbitrarily located in the vision field of the retina. The system consisted of a light source, light...

The multi-criteria predictive control of nonlinear dynamical systems based on Artificial Neural Networks (ANNs) and genetic algorithms (GAs) are considered. The (ANNs) are used to determine process models at each operating level; the control action is provided by minimizing a set of control...

The development of the Financial Crisis throughout 2008 and 2009 has made many investors and fund managers question whether growth-based investment approaches have had their day. Value-based approaches built on fundamental analysis have resurfaced again. Typically, these value-based models use...

The use of n-tuple or weightless neural networks as pattern recognition devices is well known (Aleksander and Stonham, 1979). They have some significant advantages over the more common and biologically plausible networks, such as multi-layer perceptrons; for example, n-tuple networks have been...

Brain imaging techniques have the potential of providing information about functional interactions within entire neural networks. Large quantities of data can be obtained from mapping studies, but computational techniques are needed to make sense of the complex network interactions that take...

Problems such as conduction of nerve impulses, behavior of the immune system or of effects of medication, and many others, when modelled by differential equations, are amenable to solution by a mathematical procedure called the decomposition method. This method is efficient and accurate; it makes...