A translation-invariant based adaptive threshold denoising method formechanical impact signal is proposed. Compared with traditional wavelet denoising methods, itsuppresses pseudo-Gibbs phenomena in the neighborhood o...A translation-invariant based adaptive threshold denoising method formechanical impact signal is proposed. Compared with traditional wavelet denoising methods, itsuppresses pseudo-Gibbs phenomena in the neighborhood of signal discontinuities. To remedy thedrawbacks of conventional threshold functions, a new improved threshold function is introduced. Itpossesses more advantages than others. Moreover, based on utilizing characteristics of signal, aadaptive threshold selection procedure for impact signal is proposed. It is data-driven andlevel-dependent, therefore, it is more rational than other threshold estimation methods. Theproposed method is compared to alternative existing methods, and its superiority is revealed bysimulation and real data examples.展开更多
The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscilla...The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscillator detection system cannot guarantee the immunity to noises （even white noise）. In fact the randomness of noises has a serious or even a destructive effect on the detection results in many cases. To solve this problem, we present a new detecting method based on wavelet threshold processing that can detect the chaotic weak signal accompanied with noise. All theoretical analyses and simulation experiments indicate that the new method reduces the noise interferences to detection significantly, thereby making the corresponding chaotic oscillator that detects the weak signals accompanied with noises more stable and reliable.展开更多
In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and imple...In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and implement a new wavelet thresholding method and evaluate it against other classical wavelet thresholding methods and hence search for the optimal wavelet mother function among the wide families with a suitable level of decomposition and followed by a novel thresholding method among the existing methods. This optimized method will be used to shrink the wavelet coefficients and yield an adequate compressed pressure signal prior to transmit it. While a comparison evaluation analysis is established, A new proposed procedure is used to compress a synthetic signal and obtain the optimal results through minimization the signal memory size and its transmission bandwidth. There are different performance indices to establish the comparison and evaluation process for signal compression;but the most well-known measuring scores are: NMSE, ESNR, and PDR. The obtained results showed the dominant of the square wavelet thresholding method against other methods using different measuring scores and hence the conclusion by the way for adopting this proposed novel wavelet thresholding method for 1D signal compression in future researches.展开更多
Underwater Wireless Communication, largely dependent on the acoustic communication between the machines, is largely affected by various types of noise in the shallow and deep water. However ambient noise which is due ...Underwater Wireless Communication, largely dependent on the acoustic communication between the machines, is largely affected by various types of noise in the shallow and deep water. However ambient noise which is due to multiple sources (e.g. shipping, wind) and no one source dominates. Ambient noise masks the acoustic signal to a large extent. Hence today it has drawn the attention of the experts to reduce its effect on the received signal. This paper discusses ambient noise problem and devises a new wavelet thresholding method to reduce its effect. Afterwards a comparative study on statistical parameters is shown to prove the efficiency of the devised method.展开更多
目的对双耳对称性中重度及重度感音神经性听力损失患者进行可听度对比阈值(audible contrast threshold,ACT)测试和噪声中言语(speech in noise,SIN)测试,研究二者结果的相关性。方法纳入2024年10月至2025年3月于杭州仁爱耳聋康复研究...目的对双耳对称性中重度及重度感音神经性听力损失患者进行可听度对比阈值(audible contrast threshold,ACT)测试和噪声中言语(speech in noise,SIN)测试,研究二者结果的相关性。方法纳入2024年10月至2025年3月于杭州仁爱耳聋康复研究院就诊的双耳对称性中重度及重度感音神经性听力损失患者80例为听损组,听力正常者30名为对照组,完成ACT和SIN测试,比较听损组和对照组ACT值与信噪比损失(signal-to-noise ratio loss,SNRloss)值、SIN测试时间与ACT测试时间。分析SNR值与ACT值的相关性。结果听损组ACT值、SNR-loss值均高于对照组,SIN测试时间、ACT测试时间均短于对照组,差异有统计学意义(P<0.05);两组ACT值均随着SNR-loss值增加而增加,差异有统计学意义(P<0.05)。结论ACT测试与SNR测试具有相关性,ACT测试所得的ACT值可以预测SNR-loss程度。展开更多
针对复杂海洋环境中的船舶辐射噪声信号去噪问题,该文提出了一种基于阿基米德优化算法优化变分模态分解联合小波阈值的非平稳水声信号去噪方法。首先,采用阿基米德优化算法对变分模态分解进行最优参数寻优,确定惩罚因子α和最佳模态分解...针对复杂海洋环境中的船舶辐射噪声信号去噪问题,该文提出了一种基于阿基米德优化算法优化变分模态分解联合小波阈值的非平稳水声信号去噪方法。首先,采用阿基米德优化算法对变分模态分解进行最优参数寻优,确定惩罚因子α和最佳模态分解数k。对原始水声信号进行变分模态分解,通过相关系数及其中心频率选择信号主导模态分量。结合小波阈值去噪对信号主导模态分量进行去噪后完成信号重构。仿真及实验结果表明:相比传统水声信号去噪方法,该文方法在复杂噪声环境下可有效提升信噪比12 d B,降低均方根误差80%,并在去噪的同时保持信号关键特征,具有更优的去噪性能。展开更多
文摘A translation-invariant based adaptive threshold denoising method formechanical impact signal is proposed. Compared with traditional wavelet denoising methods, itsuppresses pseudo-Gibbs phenomena in the neighborhood of signal discontinuities. To remedy thedrawbacks of conventional threshold functions, a new improved threshold function is introduced. Itpossesses more advantages than others. Moreover, based on utilizing characteristics of signal, aadaptive threshold selection procedure for impact signal is proposed. It is data-driven andlevel-dependent, therefore, it is more rational than other threshold estimation methods. Theproposed method is compared to alternative existing methods, and its superiority is revealed bysimulation and real data examples.
基金Project supported by the National Natural Science Foundation of China (Grant No. 10731050)the Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China (Grant No. IRTO0742)
文摘The chaotic oscillator has already been considered as a powerful method to detect weak signals, even weak signals accompanied with noises. However, many examples, analyses and simulations indicate that chaotic oscillator detection system cannot guarantee the immunity to noises （even white noise）. In fact the randomness of noises has a serious or even a destructive effect on the detection results in many cases. To solve this problem, we present a new detecting method based on wavelet threshold processing that can detect the chaotic weak signal accompanied with noise. All theoretical analyses and simulation experiments indicate that the new method reduces the noise interferences to detection significantly, thereby making the corresponding chaotic oscillator that detects the weak signals accompanied with noises more stable and reliable.
文摘In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and implement a new wavelet thresholding method and evaluate it against other classical wavelet thresholding methods and hence search for the optimal wavelet mother function among the wide families with a suitable level of decomposition and followed by a novel thresholding method among the existing methods. This optimized method will be used to shrink the wavelet coefficients and yield an adequate compressed pressure signal prior to transmit it. While a comparison evaluation analysis is established, A new proposed procedure is used to compress a synthetic signal and obtain the optimal results through minimization the signal memory size and its transmission bandwidth. There are different performance indices to establish the comparison and evaluation process for signal compression;but the most well-known measuring scores are: NMSE, ESNR, and PDR. The obtained results showed the dominant of the square wavelet thresholding method against other methods using different measuring scores and hence the conclusion by the way for adopting this proposed novel wavelet thresholding method for 1D signal compression in future researches.
文摘Underwater Wireless Communication, largely dependent on the acoustic communication between the machines, is largely affected by various types of noise in the shallow and deep water. However ambient noise which is due to multiple sources (e.g. shipping, wind) and no one source dominates. Ambient noise masks the acoustic signal to a large extent. Hence today it has drawn the attention of the experts to reduce its effect on the received signal. This paper discusses ambient noise problem and devises a new wavelet thresholding method to reduce its effect. Afterwards a comparative study on statistical parameters is shown to prove the efficiency of the devised method.
文摘目的对双耳对称性中重度及重度感音神经性听力损失患者进行可听度对比阈值(audible contrast threshold,ACT)测试和噪声中言语(speech in noise,SIN)测试,研究二者结果的相关性。方法纳入2024年10月至2025年3月于杭州仁爱耳聋康复研究院就诊的双耳对称性中重度及重度感音神经性听力损失患者80例为听损组,听力正常者30名为对照组,完成ACT和SIN测试,比较听损组和对照组ACT值与信噪比损失(signal-to-noise ratio loss,SNRloss)值、SIN测试时间与ACT测试时间。分析SNR值与ACT值的相关性。结果听损组ACT值、SNR-loss值均高于对照组,SIN测试时间、ACT测试时间均短于对照组,差异有统计学意义(P<0.05);两组ACT值均随着SNR-loss值增加而增加,差异有统计学意义(P<0.05)。结论ACT测试与SNR测试具有相关性,ACT测试所得的ACT值可以预测SNR-loss程度。
文摘针对复杂海洋环境中的船舶辐射噪声信号去噪问题,该文提出了一种基于阿基米德优化算法优化变分模态分解联合小波阈值的非平稳水声信号去噪方法。首先,采用阿基米德优化算法对变分模态分解进行最优参数寻优,确定惩罚因子α和最佳模态分解数k。对原始水声信号进行变分模态分解,通过相关系数及其中心频率选择信号主导模态分量。结合小波阈值去噪对信号主导模态分量进行去噪后完成信号重构。仿真及实验结果表明:相比传统水声信号去噪方法,该文方法在复杂噪声环境下可有效提升信噪比12 d B,降低均方根误差80%,并在去噪的同时保持信号关键特征,具有更优的去噪性能。
