Gradient descent method with multiple adaptive step sizes for identifying loudspeaker nonlinearities

被引：0
|
作者：
Chen L. [1 ]
Pan K. [1 ]
Zhang Z. [1 ]
Feng X. [1 ]
Shen Y. [1 ,2 ]
机构：
[1] Key Laboratory of Modern Acoustics, Institute of Acoustics, Nanjing University, Nanjing
[2] Shenzhen Research Institute of Nanjing University, Shenzhen
来源：
AES: Journal of the Audio Engineering Society | 2021年 / 69卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Gradient methods;
D O I：
10.17743/JAES.2020.0071
中图分类号：
学科分类号：
摘要：
An improved gradient descent method with multiple variable step sizes for identifying nonlinear parameters of moving-coil loudspeakers is proposed. This method monitors parameters trends during identification and adaptively multiplies or attenuates corresponding step sizes, eliminating the need for manual adjustments. Simulations and experiments reveal that it is as accurate as the fixed step size method and more efficient and robust against initial linear parameter errors. © 2021 Audio Engineering Society. All rights reserved.
引用
收藏
页码：182 / 190
页数：8
相关论文
共 50 条
  • [1] Gradient Descent Method With Multiple Adaptive Step Sizes for Identifying Loudspeaker Nonlinearities
    Li Chen
    Pan, Keyu
    Zhang, Zhaoqi
    Feng, Xuelei
    Shen, Yong
    JOURNAL OF THE AUDIO ENGINEERING SOCIETY, 2021, 69 (03): : 182 - 190
  • [2] Distributed Weighted Gradient Descent Method With Adaptive Step Sizes for Energy Management of Microgrids
    Zheng, Xinze
    Li, Qiang
    Yuan, Juzhong
    Chen, Ziyu
    IEEE TRANSACTIONS ON SMART GRID, 2024, 15 (05) : 4436 - 4449
  • [3] Gradient Methods with Adaptive Step-Sizes
    Bin Zhou
    Li Gao
    Yu-Hong Dai
    Computational Optimization and Applications, 2006, 35 : 69 - 86
  • [4] Gradient methods with adaptive step-sizes
    Zhou, Bin
    Gao, Li
    Dai, Yu-Hong
    COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2006, 35 (01) : 69 - 86
  • [5] DESCENT DIRECTION STOCHASTIC APPROXIMATION ALGORITHM WITH ADAPTIVE STEP SIZES
    Luzanin, Zorana
    Stojkovska, Irena
    Kresoja, Milena
    JOURNAL OF COMPUTATIONAL MATHEMATICS, 2019, 37 (01) : 76 - 94
  • [6] Improving generalization performance of adaptive gradient method via bounded step sizes
    Wang, Yangchuan
    Ding, Lianhong
    Shi, Peng
    Li, Juntao
    Yuan, Ruiping
    NEUROCOMPUTING, 2025, 617
  • [7] Gradient-Descent Adaptive Filtering Using Gradient Adaptive Step-Size
    Talebi, Sayed Pouria
    Darvishi, Hossein
    Werner, Stefan
    Rossi, Pierluigi Salvo
    2022 IEEE 12TH SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP (SAM), 2022, : 321 - 325
  • [8] A normalized gradient descent algorithm for nonlinear adaptive filters using a gradient adaptive step size
    Mandic, DP
    Hanna, AI
    Razaz, M
    IEEE SIGNAL PROCESSING LETTERS, 2001, 8 (11) : 295 - 297
  • [9] Analysis of Gradient Descent With Varying Step Sizes Using Integral Quadratic Constraints
    Padmanabhan, Ram
    Seiler, Peter
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2025, 70 (01) : 587 - 594
  • [10] Switched-mode systems: gradient-descent algorithms with Armijo step sizes
    Wardi, Y.
    Egerstedt, M.
    Hale, M.
    DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS, 2015, 25 (04): : 571 - 599
12345