| Citation: | WANG Shuai, XIANG Jianjun, PENG Fang, et al. Application of a new steepest descent algorithm in adaptive noise cancellation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(7): 1462-1469. doi: 10.13700/j.bh.1001-5965.2020.0218(in Chinese)
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Adaptive noise cancellation has important applications in many fields. In order to carry out adaptive noise cancellation, a new steepest descent algorithm is proposed. The main principle of the algorithm is to reduce the dimension of multivariate quadratic function to make it become a univariate quadratic function, and then apply the properties of parabola to iteratively solve the extremum of each dimension. Compared with the traditional adaptive algorithm, the new steepest descent algorithm shows the advantages of fast convergence, good filtering effect, adjustable filtering effect, resisting bad SNR and sharp change SNR, no need to choose iteration step, and suitable for computer and programmable hardware implementation.
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