Computationally efficient algorithm for high sampling-frequency operation of active noise control. (May 2015)

• Record Type: Journal Article
• Authors: Rout, Nirmal Kumar; Das, Debi Prasad; Panda, Ganapati
• Is Part Of: Mechanical systems and signal processing. Volume 56/57(2015)
• Page Start: 302
• Page End: 319
• Publication Date: 2015-05
• Subjects: Active noise control -- Partitioned block adaptive filter -- Computational complexity; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2014.10.009
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: In high sampling-frequency operation of active noise control (ANC) system the length of the secondary path estimate and the ANC filter are very long. This increases the computational complexity of the conventional filtered-x least mean square (FXLMS) algorithm. To reduce the computational complexity of long order ANC system using FXLMS algorithm, frequency domain block ANC algorithms have been proposed in past. These full block frequency domain ANC algorithms are associated with some disadvantages such as large block delay, quantization error due to computation of large size transforms and implementation difficulties in existing low-end DSP hardware. To overcome these shortcomings, the partitioned block ANC algorithm is newly proposed where the long length filters in ANC are divided into a number of equal partitions and suitably assembled to perform the FXLMS algorithm in the frequency domain. The complexity of this proposed frequency domain partitioned block FXLMS (FPBFXLMS) algorithm is quite reduced compared to the conventional FXLMS algorithm. It is further reduced by merging one fast Fourier transform (FFT)-inverse fast Fourier transform (IFFT) combination to derive the reduced structure FPBFXLMS (RFPBFXLMS) algorithm. Computational complexity analysis for different orders of filter and partition size are presented. Systematic computer simulations are carried out for both the proposed partitioned block ANC algorithms to show its accuracy compared to the time domain FXLMS algorithm. Highlights: High sampling frequency operation of ANC increases computational complexity. Full block ANC algorithm in frequency domain is computationally efficient. But, full block ANC algorithms find implementation difficulties. Partition block ANC algorithm overcomes the implementation issues. The proposed computationally efficient algorithm is suitable for battery operated ANC appliances.