Functional Link Neural Network Based Adaptive Filter
In this code, we will identify a nonlinear system using the traditional trigonometric functional link neural network based adaptive filter (TFLAF). These type of filters are also known as linear-in-the-parameters nonlinear adaptive filters. In TFLAF, the input vector/buffer is expanded as a function of sine and cosine functions. In this example, we have used this filter in a nonlinear system identification scenario, where the nonlinearity is introduced by the loudspeaker. For more details, please refer to the following paper from our lab.
V. Patel, V. Gandhi, S. Heda, and N. V. George, “Design of Adaptive Exponential Functional Link Network-Based Nonlinear Filters,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 63, no. 9, pp. 1434–1442, 2016.
In this code, example 1 (Case I of page 5) of the above paper with exact values of parameters is implemented.
The code is nicely scripted. Hope this helps!!!!!
Cite As
Dwaipayan Ray (2024). Functional Link Neural Network Based Adaptive Filter (https://www.mathworks.com/matlabcentral/fileexchange/69555-functional-link-neural-network-based-adaptive-filter), MATLAB Central File Exchange. Retrieved .
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- Mathematics and Optimization > Optimization Toolbox > Systems of Nonlinear Equations > Newton-Raphson Method >
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