基于非线性最优压缩感知和电子信息技术的迭代硬阈值算法在自动控制领域的应用

IF 2.4 Q2 ENGINEERING, MECHANICAL Nonlinear Engineering - Modeling and Application Pub Date : 2023-01-01 DOI:10.1515/nleng-2022-0305
Kun-han jiang, M. Bradha
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引用次数: 0

摘要

摘要为了提高迭代硬阈值的精度,提出了一种改进的迭代硬阈值(IHT)方法。该方法的具体内容包括基于压缩感知(非线性优化)的IHT算法原理、加权最小二乘改进、基于加权最小二乘改进的IHT算法模型的建立以及传统算法和改进算法在一维信号重构上的实验研究。结果表明,当采样率分别为0.2、0.5和0.8时,改进的IRLSIHT算法分别耗时8.37、29.63和30.86 s,信噪比分别为20.11、27.47和31.82 dB。与传统的IHT算法相比,耗时较长,这是不足之处,但信噪比最大,改进后的算法提高了精度。实践证明,将本文提出的方法与自动控制相结合,可以显著节省时间,提高工业产量。
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The application of iterative hard threshold algorithm based on nonlinear optimal compression sensing and electronic information technology in the field of automatic control
Abstract To improve the accuracy effect of the iterative hard threshold, an improved iterative hard threshold (IHT) method is proposed. The specific contents of this method include the principle of an IHT algorithm based on compression sensing (nonlinear optimization), weighted least squares improvement, the establishment of an IHT algorithm model based on weighted least squares improvement, and the experimental research of traditional algorithms and improved algorithms on one-dimensional signal reconstruction. The results show that the improved IRLSIHT algorithm takes 8.37, 29.63, and 30.86 s when the sampling rate is 0.2, 0.5, and 0.8, respectively, and the signal-to-noise ratio is 20.11, 27.47, and 31.82 dB, respectively. Compared with the traditional IHT algorithm, it takes a long time, which is a deficiency, but the signal-to-noise ratio is the largest, and the improved algorithm improves the accuracy. It has been proven that combining the method proposed in this article with automatic control can significantly save time and increase industrial output.
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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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