A modal logical language and its Kripke semantics and Aumann semantics are introduced. A complete for mal deduction system is established to describe reasoning about knowledge in multi-agent systems involving different languages, and an institution of lo
Compactness in Pavelka's fuzzy logic for some compact lattices of truth values is shown, and the concept of gradual compactness is introduced to establish some corresponding results in a more general setting.
We analyze the influence of some usual linguistic modifiers, such as scalar product, normalization, Bouchon-Meunier modifiers, perturbation, and (weakening and reinforcement) power, in the process of approximate reasoning and clarify the difference betwe
Blumenstein, M & Verma, B 1998, 'Neural based segmentation and recognition technique for handwritten words', IEEE International Conference on Neural Networks - Conference Proceedings, pp. 1738-1742.
Artificial Neural Networks (ANNs) have been successfully applied to Optical Character Recognition (OCR) yielding excellent results. In this paper a technique is presented that segments difficult printed and cursive handwriting, and then classifies the segmented characters. A conventional algorithm is used for the initial segmentation of the words, while an ANN is used to verify whether an accurate segmentation point has been found. After all segmentation points have been detected another NN is used to identify the characters which remain following the segmentation process. The C programming language, the SP2 supercomputer and a SUN workstation were used for the experiments. The technique has been tested on real-world handwriting scanned from various staff at Griffith University, Gold Coast. Some preliminary experimental results are presented in this paper.