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Neural network models comprising elements which have exclusively excitatoryor inhibitory synapses are capable of a wide range of dynamic behavior,including chaos. In this paper, a simple excitatory-inhibitory neural pair,which forms the building block of larger networks, is subjected to externalstimulation. The response shows transition between various types of dynamics,depending upon the magnitude of the stimulus. Coupling such pairs over a localneighborhood in a two-dimensional plane, the resultant network can achieve asatisfactory segmentation of an image into ``object'' and ``background''.Results for synthetic and and ``real-life'' images are given.Comment: 8 pages, latex, 5 figure

Dynamical response of an excitatory-inhibitory neural network to external stimulation: An application to image segmentation