| 基函数可递归的泛函神经元网络学习算法 |
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| 引用本文： | 肖倩,周永权,陈振.基函数可递归的泛函神经元网络学习算法[J].计算机科学,2013,40(1):203-207. |
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| 作者姓名： | 肖倩 周永权 陈振 |
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| 作者单位： | (广西大学计算机与电子信息学院 南宁530004) (广西民族大学信息科学与工程学院 南宁530006) |
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| 基金项目： | 国家自然科学基金(61165015);广西自然科学基金(2012GXNSFDA053028);广西高等学校重大科研项目(201201ZD008)资助 |
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| 摘 要： | 将泛函神经元结构做了一个变形,给出了一种基函数可递归的泛函神经元网络学习算法,该算法借助于矩阵伪逆递归求解方法,完成对泛函神经元网络基函数的自适应调整,最终实现泛函网络结构和参数共同的最优求解。数值仿真实验结果表明,该算法具有自适应性、鲁棒性和较高的收敛精度,将在实时在线辨识中有着广泛的应用。
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| 关 键 词： | 泛函神经元 基函数 矩阵伪逆 学习算法 |
Functional Network Learning Algorithm with Recursively Base Functions |
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| XIAO Qian,ZHOU Yong-quan,CHEN Zhen.Functional Network Learning Algorithm with Recursively Base Functions[J].Computer Science,2013,40(1):203-207. |
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| Authors: | XIAO Qian ZHOU Yong-quan CHEN Zhen |
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| Affiliation: | (School of Computer and Electronics Information,Guangxi University,Nanning 530004,China) (College of Information Science and Engineering,Guangxi University for Nationalities,Nanning 530006,China) |
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| Abstract: | By transforming the functional neuron,we proposed a functional network learning algorithm with recursively base functions. The algorithm uses a recursive method for solving matrix's pseudo-inverse to achieve adaptive adjustment of base functions in functional neural network, finally realizes the functional network structure and parameters of the optimal solution together. The experimental results show that the learning algorithm has adaptive, robustness and high accuracy of convergence, and will have broad application in real-time online identification. |
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| Keywords: | Functional neuron Base functions Matrix's pseudo inverse Learning algorithm |
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