The inverse synthetic aperture radar (ISAR) imaging technique is widely used in remote sensing and target detection areas, and the back projection (bp) algorithm is a fundamental method to obtain the target's imag...
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On the basis of fuzzy optimization model,the concept of equivalent error function is introduced to establish a new back propagation(bp) algorithm of Hessian matrix to promote the *** Newton's iteration method is a...
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On the basis of fuzzy optimization model,the concept of equivalent error function is introduced to establish a new back propagation(bp) algorithm of Hessian matrix to promote the *** Newton's iteration method is applied to promote the training efficiency and accelerate the *** method is used in the decision-making analysis for economic,water resources and environmental planning of the Dalian City.
Ultra-wideband (UWB) multiple input multiple output (MIMO) radar has been widely used in detection systems due to its advantages, such as low cost and high data acquisition capability. The detection system is applied ...
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Ultra-wideband (UWB) multiple input multiple output (MIMO) radar has been widely used in detection systems due to its advantages, such as low cost and high data acquisition capability. The detection system is applied in various ground-penetrating applications, including mine detection and earthquake rescue. In this paper, a novel UWB MIMO radar system based on step-frequency continuous wave is designed for underground target detection. To improve the penetration depth and high-range resolution, a new miniature Vivaldi antenna with a bandwidth of 1-3 GHz is designed and integrated into the ground-penetrating imaging system. Furthermore, a multiscale weighted time-domain back projection (bp) algorithm is proposed to suppress artifacts and reduce the computational complexity of the bp algorithm. The designed system is tested by detecting stationary targets. The experimental results agree well with the simulation. The reconstructed images show that the designed MIMO radar system can successfully image underground targets.
On the basis of fuzzy optimization model, the concept of equivalent error function is introduced to establish a new back propagation (bp) algorithm of Hessian matrix to promote the calculation. The New...
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On the basis of fuzzy optimization model, the concept of equivalent error function is introduced to establish a new back propagation (bp) algorithm of Hessian matrix to promote the calculation. The Newton's iteration method is applied to promote the training efficiency and accelerate the convergence. This method is used in the decision-making analysis for economic, water resources and environmental planning of the Dalian City.
Decoupling research on flexible tactile sensors play a very important role in the intelligent robot skin and tactile-sensing fields. In this paper, an efficient machine learning method based on the improved back-propa...
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Decoupling research on flexible tactile sensors play a very important role in the intelligent robot skin and tactile-sensing fields. In this paper, an efficient machine learning method based on the improved back-propagation (bp) algorithm is proposed to decouple the mapping relationship between the resistances of force-sensitive conductive pillars and three-dimensional forces for the 6 x 6 novel flexible tactile sensor array. Tactile-sensing principles and numerical experiments are analyzed. The tactile sensor array model accomplishes the decomposition of the force components by its delicate structure, and avoids direct interference among the electrodes of the sensor array. The force components loaded on the tactile sensor are decoupled with a very high precision from the resistance signal by the improved bp algorithm. The decoupling results show that the k-cross validation (k-CV) algorithm is a highly effective method to improve the decoupling precision of force components for the novel tactile sensor. The large dataset with the k-CV method obtains a better decoupling accuracy of the force components than the small dataset. All of the decoupling results are fairly good, and they indicate that the improved bp model with a strong non-linear approaching ability has an efficient and valid performance in decoupling force components for the tactile sensor.
In this paper,Chaos are imported into bp algorithm:The synaptic strengths are assigned with chaotic values at the beginning,and with conventional bp algorithm to train the neural *** is shown that the ability of getti...
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In this paper,Chaos are imported into bp algorithm:The synaptic strengths are assigned with chaotic values at the beginning,and with conventional bp algorithm to train the neural *** is shown that the ability of getting rid of local minimum with the new method is better than that of conventional bp method.
This paper predicts the temperature of optical transmitter and receiver through the bp algorithm based on MATLAB simulation *** inner temperature is affected by ambient temperature,heating power,air pressure,wrapping ...
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This paper predicts the temperature of optical transmitter and receiver through the bp algorithm based on MATLAB simulation *** inner temperature is affected by ambient temperature,heating power,air pressure,wrapping mode,whose stabilization needs corresponding adjustment of these *** the bp network structure with 4-8-5-1 is adopted,the Tansig function is applied in the implication layer,at the same time,the Purelin function is applied in the output *** last,the finite samples are trained and tested through the *** with the PID algorithm,the simulation result shows that there is a higher precision and faster convergence in the bp *** the meantime,the generalization ability of the bp network gives inner temperature when there are 4 inputs,which reflects the basic feature of the whole system.
Standing at the perspective of the project management, this thesis, from the relation between schedule, quality and cost, analyzes how the project cost was influenced by the schedule risk and quality risk, assesses th...
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Standing at the perspective of the project management, this thesis, from the relation between schedule, quality and cost, analyzes how the project cost was influenced by the schedule risk and quality risk, assesses the total cost risk of the project with artificial neural network bp algorithm, and determines the most sensitive factors of the project cost risk, which could provide reference for the project managers to control the project cost risk.
Taking machinery manufacturing enterprises as an example, this research proposes a financial risk assessment model based on bp neural network algorithm. On the basis of integrating the development characteristics, fin...
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Taking machinery manufacturing enterprises as an example, this research proposes a financial risk assessment model based on bp neural network algorithm. On the basis of integrating the development characteristics, financial risk types and causes of machinery manufacturing enterprises, the bp neural network algorithm model is used to improve financial risk assessment Model. The research shows that, from the perspective of latent variable path parameters, the coefficient of debt repayment variable index with the highest impact coefficient on financial risk is 0.92, and the coefficient of profit variable is 0.91. Therefore, financial risk early warning and assessment should pay special attention to these two indicators, while the obvious variable has a coefficient of 0.92. The path coefficients of the observed indicators are all over 0.7, which indicates that the company's product sales and net asset income directly affect the company's financial risk assessment, and will also have a direct impact on the company's healthy development.
In this paper potential seismic sources in coastal region of South China are identified by integration of genetic algorithm (GA) and back propagation (bp algorithm). GA is used for finding the best parameter combinati...
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In this paper potential seismic sources in coastal region of South China are identified by integration of genetic algorithm (GA) and back propagation (bp algorithm). GA is used for finding the best parameter combination rapidly in an infinite solution space for artificial neural networks (ANN). The results show that the distribution of potential seismic sources with different upper magnitude demarcated by this classifier is mostly satisfied the intrinsic relationship between seismic environment and earthquake occurrence, with less effect from subjective judgment of human being.
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