Stochastic resonance induced weak signal enhancement in a second-order tri-stable system with single-parameter adjusting

随机共振 信号(编程语言) 背景(考古学) 噪音(视频) 计算机科学 信号处理 估计理论 信噪比(成像) 控制理论(社会学) 算法 人工智能 数字信号处理 古生物学 电信 控制(管理) 计算机硬件 图像(数学) 生物 程序设计语言
作者
Cailiang Zhang,Zhihui Lai,Zhisheng Tu,Hanqiu Liu,Yong Chen,Ronghua Zhu
出处
期刊:Applied Acoustics [Elsevier BV]
卷期号:216: 109753-109753 被引量:6
标识
DOI:10.1016/j.apacoust.2023.109753
摘要

Weak signal detection methods based on stochastic resonance (SR) have been extensively studied due to their capability to utilize noise energy for enhancing weak signals. Among various SR models, the second-order tri-stable SR models have demonstrated their superiority in weak-signal detection with better output performance compared to other SR models. To optimize the output performance of the second-order tri-stable systems, a variety of parameter optimization methods have been proposed to optimize the parameters of the system. However, these optimization methods often require to optimize multiple parameters, which leads to an increase in computational costs and reduces the real-time processing efficiency of signal processing. Such multi-parameter optimization methods cannot meet the demands for timely signal processing in the context of big data. To address this challenge, this paper proposes two single-parameter-adjusting SR models. The proposed models can attain an ideal output performance by adjusting a single parameter in the SR system. The spectral amplification as an indicator is derived to quantitatively analyze the effects of the proposed models on SR output. On this basis, the influences of the proposed models on the SR output under different potential well parameters, noise intensities, signal frequency, and damping ratio are fully investigated through numerical simulations. At last, the proposed models are employed to process an experimental signal with a weak fault feature, and the experimental results verify the feasibility of the proposed models in optimizing the SR output. The research results can guide the design of tri-stable SR models and support the application of the SR-based signal processing model in the context of big data.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刘老哥6发布了新的文献求助10
1秒前
Orange应助科研通管家采纳,获得10
1秒前
anastasia完成签到,获得积分10
1秒前
田様应助科研通管家采纳,获得10
1秒前
上官若男应助科研通管家采纳,获得30
1秒前
在水一方应助科研通管家采纳,获得10
1秒前
Hello应助科研通管家采纳,获得10
1秒前
我是老大应助科研通管家采纳,获得10
1秒前
SYLH应助科研通管家采纳,获得10
1秒前
田yg完成签到,获得积分10
2秒前
SYLH应助科研通管家采纳,获得10
2秒前
SYLH应助科研通管家采纳,获得10
2秒前
852应助科研通管家采纳,获得10
2秒前
SYLH应助科研通管家采纳,获得10
2秒前
共享精神应助科研通管家采纳,获得10
2秒前
vlots应助科研通管家采纳,获得30
2秒前
SYLH应助科研通管家采纳,获得10
2秒前
2秒前
斯文败类应助科研通管家采纳,获得10
2秒前
华仔应助科研通管家采纳,获得10
2秒前
Owen应助科研通管家采纳,获得10
2秒前
SYLH应助科研通管家采纳,获得20
2秒前
思源应助科研通管家采纳,获得10
2秒前
李健应助科研通管家采纳,获得10
2秒前
ding应助科研通管家采纳,获得10
2秒前
酷波er应助科研通管家采纳,获得10
2秒前
SciGPT应助科研通管家采纳,获得10
3秒前
CodeCraft应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
赘婿应助科研通管家采纳,获得10
3秒前
3秒前
3秒前
3秒前
wang发布了新的文献求助10
3秒前
3秒前
jinxli完成签到 ,获得积分10
4秒前
5秒前
封迎松完成签到 ,获得积分10
6秒前
小李子发布了新的文献求助10
6秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Indomethacinのヒトにおける経皮吸収 400
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 370
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
Aktuelle Entwicklungen in der linguistischen Forschung 300
Current Perspectives on Generative SLA - Processing, Influence, and Interfaces 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3992562
求助须知:如何正确求助?哪些是违规求助? 3533545
关于积分的说明 11262757
捐赠科研通 3273163
什么是DOI,文献DOI怎么找? 1805959
邀请新用户注册赠送积分活动 882889
科研通“疑难数据库(出版商)”最低求助积分说明 809513