DSP Implementation of Combined FIR-Functional Link Neural Network for Active Noise Control
This paper presents theoretical and experimental study of active noise control (ANC) system based on the combination of finite-impulse response filter and functional-link neural network (CFFLNN). The combined structure is used in an effort not only to compensate for the nonlinear phenomena that often appear in the real-world ANC applications, but also to improve the attenuation performance. In this paper, we propose the development of adaptive learning algorithm, both for an identification of ANC secondary-path and for the active noise control process. Implementation of the active noise control process and proposed algorithm on digital signal processors DSP TMS320C6713 DSK is performed for real-time experiments in ANC system. Experimental results of CFFLNN-based ANC applied to the duct noise system show that the attenuation performance can be improved by introducing the FIR subsection, and that FLNN subsection can effectively compensate the nonlinearity in the ANC system.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.thentic information.