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Enhance accuracy in pole identification of system by wavelet transform de-noising

机译:通过小波变换去噪提高系统极点识别的准确性

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摘要

Based on the multiscale character of wavelet transform, the method of wavelet transform de-noising (WTDN) is introduced to improve the signal-noise ratio (SNR) of sampled data and to enhance the accuracy of pole identification of system with N4SID (numerical algorithms for subspace state system identification) method. The WTDN method does not require extra limit of the frequency range for the processed signal, and does not need a prior estimate of impulse response for identified system. So it is especially suitable to de-noise the wide-band signal and the noisy impulse response of the blind system. The results of numerical simulation indicate that the WTDN method is reliable. The WTDN method is used to process the sampled data from actual preamplifier coupled to a gas detector. The experimental results show that the WTDN method improves effectively the SNR of sampled data, which can help to enhance the accuracy in pole identification of system with the N4SID method.
机译:基于小波变换的多尺度特性,引入小波变换去噪(WTDN)方法,提高了采样数据的信噪比(SNR),提高了N4SID系统极点识别的准确性。用于子空间状态系统识别)方法。 WTDN方法不需要额外限制处理信号的频率范围,并且不需要对已识别系统的冲激响应进行事先估计。因此,特别适合对宽带信号和盲系统的噪声冲激响应进行消噪。数值模拟结果表明,该方法是可靠的。 WTDN方法用于处理来自与气体检测器耦合的实际前置放大器的采样数据。实验结果表明,WTDN方法有效地提高了采样数据的信噪比,可以帮助提高N4SID方法在系统极点识别中的准确性。

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