Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the see...Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.展开更多
This paper presents a new method to estimate the time of important earthquakes in Hormozgan region with magnitude greater than 5.5 based on the Radial Basis Function （RBF） Neural Network （NN） models. Input vector ...This paper presents a new method to estimate the time of important earthquakes in Hormozgan region with magnitude greater than 5.5 based on the Radial Basis Function （RBF） Neural Network （NN） models. Input vector to the network is composed of different seisrnicity rates between main events that are calculated in convenient and reliable way to create optimized training methods. It helps network with a limited number of training data to estimation. It is common for earthquakes modeling by data-driven methods in this case. In addition, the proposed method is combined with Rosenberg cluster method to remove aftershocks events from the history of catalog for NN to better process the data. The results show that created RBF model successfully estimates the interevent times between large and sequence earthquakes that can be used as a tool to predict earthquake, so that comparison with other NN structure, for example Multi- Layer Perceptron （MLP） NN, reveals the superiority of the proposed method. Because of superiority proposed method has higher accuracy, lower costs and simpler network structure.展开更多
文摘Seeking in a field of view(FOV) is influenced by the existence of jammers,noise,shine background or flying perturbations.All these factors may push the target out of the FOV and cause missing the target.In all the seekers the FOV is not fully exploited which means the target can be missed before becoming out of the FOV,this results of the nonlinearity of the reticle structure.In this paper,a novel method of the target position detection a crossed four slits or crossed array trackers(CAT) seeker will be designed,simulated and evaluated.The idea of this method depends on dividing the FOV into main regions up to a certain parameter,which is the pulses number;then,each main region will be divided into sub-regions up to a second parameter which will be the pulses distribution a spin period.The errors sources will be discussed and evaluated.Other new idea will be applied which is exploiting some area of the FOV where a part of the position data is missed in the information signal by pushing the target to the region where the information signal carries the total position data.
文摘This paper presents a new method to estimate the time of important earthquakes in Hormozgan region with magnitude greater than 5.5 based on the Radial Basis Function （RBF） Neural Network （NN） models. Input vector to the network is composed of different seisrnicity rates between main events that are calculated in convenient and reliable way to create optimized training methods. It helps network with a limited number of training data to estimation. It is common for earthquakes modeling by data-driven methods in this case. In addition, the proposed method is combined with Rosenberg cluster method to remove aftershocks events from the history of catalog for NN to better process the data. The results show that created RBF model successfully estimates the interevent times between large and sequence earthquakes that can be used as a tool to predict earthquake, so that comparison with other NN structure, for example Multi- Layer Perceptron （MLP） NN, reveals the superiority of the proposed method. Because of superiority proposed method has higher accuracy, lower costs and simpler network structure.
