Performance Verification of a Fuzzy Wavelet Neural Network in the First Order Partial Derivative Approximation of Nonlinear Functions
Approximation of the first order partial derivative of a function modeled from a set of discrete data is the requirement of several applications. However, using a direct method for calculating the partial derivative from a set of discrete points is preferred rather differentiating the function which...
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| Veröffentlicht in: | Neural processing letters 2016-02, Vol.43 (1), p.219-230 |
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| container_title | Neural processing letters |
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| creator | Nejad, Hadi Chahkandi Farshad, Mohsen Khayat, Omid Rahatabad, Fereidoun Nowshiravan |
| description | Approximation of the first order partial derivative of a function modeled from a set of discrete data is the requirement of several applications. However, using a direct method for calculating the partial derivative from a set of discrete points is preferred rather differentiating the function which is obtained by modeling the discrete dataset. In this paper, the first order partial derivative of a fuzzy wavelet neural network structure is calculated to act as a direct differentiator. The structure of the network is described and its parameters are tuned by an adaptive gradient-based back propagation learning algorithm. It is shown that the proposed model outperforms the adaptive neuro-fuzzy inference-based and feed forward neural network-based differentiators in approximating the first order partial derivatives of multi-variable nonlinear functions. |
| doi_str_mv | 10.1007/s11063-015-9414-9 |
| format | Article |
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| ispartof | Neural processing letters, 2016-02, Vol.43 (1), p.219-230 |
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| subjects | Algorithms Approximation Artificial Intelligence Artificial neural networks Back propagation Back propagation networks Bias Complex Systems Computational Intelligence Computer Science Derivatives Differentiators Fuzzy logic Machine learning Mathematical functions Neural networks Partial differential equations Time series |
| title | Performance Verification of a Fuzzy Wavelet Neural Network in the First Order Partial Derivative Approximation of Nonlinear Functions |
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