Information Fusion Algorithm And Application Based On Neural Network

Information Fusion technology is used for how to utilize multi-source information to overcome the inaccuracy while thoroughly describing objects concerned for correct judgment. This technology has been widely applied to pattern recognition, target tracing and automation fields.Neural network is a new type of theory of intelligent information processing, in which a lot of units named neurons make up a nonlinear dynamics system that simulates and abstracts human brain's imagery thinking and association memory in order to achieve some information processing ability such as learning, identify and memory like human brain. Neural network has been developed for several ten years and shown enormous potential and application in many fields such as information technology.This paper aims to study the information used in the calculation of the smart integration of the field, the establishment of intelligent information fusion algorithm, and applied nuclear detector peaks drift, namely, the use of intelligence information fusion of spectrometer peaks with temperature and voltage drift, such as the integration of models and algorithms.First of all, the theoretical foundation, current research situation and developing direction of the information fusion and neural computing are introduced in this paper. At the same time, the application problem and relevant algorithm in information fusion of neural computing are discussed.To put the information fusion can be used for the theory of modular neural networks and fuzzy NN of models and algorithms.Analyze the relationship between neural network and pattern recognition and prove the neural network fusion theory qualitatively. With the different peaks against interference in the issue of drift, Modular neural network will be used for the peak drift spectrometer data fusion, By the fusion of the network model and its learning.Finally, the test data of peak drift is calculated and simulated based on the mathematics models. The result proved that the mathematic models have high precision and the fusion technology of information can beused in fusion of peak drift successfully.