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Aiming at the shortcomings of the BP neural network, this paper presents a method for grain condition information fusion based on BP neural networks and D-S evidential theory. This method firstly employs many BP neural network outputs as the inputs of D-S evidence theory. After that, D-S evidence theory is used to fuse with results from all the neural networks, resulting in the grain quality evaluation...
Support vector machine has some advantages, such as simple structure and good generalization, which is one implementation in statistical learning theory. SVM offers a kind of effective way for the data fusion problem of little sample, non-linear and high dimension. In this paper, mobile agents are applied to data fusion system. The model and the study method of data fusion system are improved. An...
Object recognition in stereo sequences is a simulation of human visual systems on how to analyze and understand various scenes. A pair of stereo sequences is a type of complicated information with huge amount of raw data and features associated with different parameter spaces. Therefore the automatic object recognition in stereo sequences is a difficult and unsolved task challenging many researchers...
In the distributed multi-sensor data fusion system composed of radar and infrared sensor, the track correlation is one of the key techniques and is also sophisticated because the types of the sensors are different and both of them donpsilat possess the consistent measurement space. This paper presents a radar-infrared sensor track correlation algorithm using the grey correlation analysis of grey system...
Kalman filter is introduced into the neuro-fuzzy deducing system (NFDS) operation to attenuate disturbances in measurement data. Both of Lidar and infrared radar data sets will be engaged into data fusion, because there will exist defective data points within both of which owing to the respectively distinct running mechanism. Data confidence estimator of NFDS derived from contextual information (CI)...
It is recognized within data fusion domain that the main challenge in devising gradient order fusion algorithm is to provide a feasible architecture in fusion system, which will comprise concerned entities in diverse subject-specific fusion model, besides, the characteristics, fusion situations and interrelations among system components have been demonstrated the key factors in the decomposition in...
An elaborately designed software architecture is put forward based on fuzzy sets theory (FST), which is specialized in multiple sensor fusion and mechanism failure diagnosis. Besides, when confronted with multiple fault signals, fusion parameters can be dynamically adapted based on principles of fuzzy soft clustering so as to promote immune ability in artificially mechanical systems. The key point...
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