| 基于神经网络的三极管温度特性模型研究 |
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| 引用本文： | 许敏丰.基于神经网络的三极管温度特性模型研究[J].北京工商大学学报(自然科学版),2008,26(2):47-50. |
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| 作者姓名： | 许敏丰 |
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| 作者单位： | 北京工商大学,信息工程学院,北京,100037 |
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| 摘 要： | 温度对三极管的性能影响较大,使得电路中的静态工作点出现不稳定现象.采用神经网络技术分析实际环境温度对三极管放大特性的影响,并通过实测数据和利用线性均差法得到的数据建立三极管温度特性的神经网络模型.利用该模型可预测温度对放大倍数的影响,掌握电路系统的温度漂移,从而为优化系统性能提供设计依据.
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| 关 键 词： | BP神经网络 静态工作点 线性拟合 线性插值 |
INVESTIGATION ON CHARACTERISTICS OF TRIODE'S TEMPERATURE BASED ON NEURAL NETWORK |
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| XU Min-feng.INVESTIGATION ON CHARACTERISTICS OF TRIODE'S TEMPERATURE BASED ON NEURAL NETWORK[J].Journal of Beijing Technology and Business University:Natural Science Edition,2008,26(2):47-50. |
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| Authors: | XU Min-feng |
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| Abstract: | The temperature had great effect to the triode's performance and made the quiescent operation point in circuitry unstable.The text analyzed the effect to the triode's characteristics from environment's temperature.According to the experimental data,it established a neural network model and used it to predict the variation of the system's temperature.That can afford proofs to optimize the performance of the system. |
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| Keywords: | BP neural network quiescent operation point line fitting linear divided difference |
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