Adaptive noise cancellation with fast tunable RBF network
Adaptive noise cancellation with fast tunable RBF network
- Author(s): Hao Chen ; Yu Gong ; Xia Hong
- DOI: 10.1049/ic.2012.0104
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- Author(s): Hao Chen ; Yu Gong ; Xia Hong Source: Sensor Signal Processing for Defence (SSPD 2012), 2012 page ()
- Conference: Sensor Signal Processing for Defence (SSPD 2012)
- DOI: 10.1049/ic.2012.0104
- ISBN: 978-1-84919-712-0
- Location: London, UK
- Conference date: 25-27 Sept. 2012
- Format: PDF
This paper describes a novel adaptive noise cancellation system with fast tunable radial basis function (RBF). The weight coefficients of the RBF network are adapted by the multi-innovation recursive least square (MRLS) algorithm. If the RBF network performs poorly despite of the weight adaptation, an insignificant node with little contribution to the overall performance is replaced with a new node without changing the model size. Otherwise, the RBF network structure remains unchanged and only the weight vector is adapted. The simulation results show that the proposed approach can well cancel the noise in both stationary and nonstationary ANC systems. (5 pages)
Inspec keywords: adaptive signal processing; interference suppression; least mean squares methods; recursive estimation; radial basis function networks
Subjects: Neural computing techniques; Interpolation and function approximation (numerical analysis); Signal processing and detection; Digital signal processing; Electromagnetic compatibility and interference; Interpolation and function approximation (numerical analysis)
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