Signal processing unit for classifying objects on the basis of s

Image analysis – Histogram processing – For setting a threshold

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382 15, 382 36, 395 21, G06R 962

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active

052475840

ABSTRACT:
In a signal processing arrangement for classifying objects on the basis of signals from a plurality of different sensors each of the signals from the sensors is applied to a pair of neural networks. One neural network of each pair processes predetermined characteristics of the object and the other neural network processes movement or special data of the object such that these networks provide detection, identification and movement information specific for the sensors. Feature vectors formed from this information specific for the sensors are applied to a neural network for determining the associations of the identification and movement information. The information obtained by this network is applied together with the feature vectors to a network for identifying and classifying the object. The information from the association and identification networks, respectively, are supplied together with the information specific for the sensors to an expert system which, by using further knowledge about data and facts of the potential objects, makes final decisions and conclusions for identification.

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Paper entitled "CMAC: An Associative Neural Network Alternative to Backpropagation", by W. Thomas Miller, III, et al., Proceedings of the IEEE, Oct., 1990.

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