A Simple Design of Fractional Delay FIR Filter Based on Binomial Series Expansion Theory

Bensouici, Tahar; Charef, Abdelfatah; Assadi, I.

doi:10.1007/s00034-018-1000-8

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…at means that the explosion vibration signal has a wider autocorrelation function than the ground noise. erefore, with an appropriate delay length, the noise signal will no longer be correlated with the original signal, but the useful signal still keeps a good correlation with it [22,23], as shown in Figure 2. Autocorrelation operation is performed on Part A and Part B, the former containing only noise signal while the latter containing both noise and useful signal.…”

Section: Principle Of D-lms Adaptive Filtersmentioning

confidence: 99%

The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA

Meng

et al. 2020

Shock and Vibration

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In the real-time position technology of underground shallow source, the signal denoising performance of wireless sensor nodes directly determines the location speed and accuracy of underground burst point. Because of the complexity and randomness of the underground medium and the fact that underground explosion is a nonstationary transient process, the problems of low convergence rate and poor steady-state performance of the filter exist when the existing LMS algorithm is used for signal denoising. In light of the above concerns, this paper comes up with a signal denoising algorithm and hardware implementation method based on D-LMS (delay-LMS). Firstly, according to the autocorrelation function characteristic of random signal, using the principle that the autocorrelation function time delay characteristic of narrowband signal such as explosion vibration signal is better than that of wideband random signal such as ground noise, the D-LMS filter algorithm is constructed by introducing the time delay parameter. Secondly, the selection method of key parameters in D-LMS hardware implementation is analyzed. Thirdly, the corresponding hardware circuit is designed by FPGA, and the simulation is carried out. Numerical simulation and experimental verification show that compared with the existing LMS improved algorithm, the D-LMS algorithm proposed in this paper has higher denoising stability and better denoising effect. Compared with the signal postprocessing method based on the host computer, the signal denoising speed of this method is significantly improved. This method will provide a powerful theoretical method to solve the problem of high-precision and fast source positioning and provide technical support for the development of high-speed and real-time source positioning instruments.

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Section: Principle Of D-lms Adaptive Filtersmentioning

confidence: 99%

The On-Chip D-LMS Filter Design Method of Wireless Sensor Node Based on FPGA

Meng

et al. 2020

Shock and Vibration

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“…Hence, these intermediate values can be estimated [1]. It is an important topic because it finds a wide range of applications in the digital signal processing and the digital communications such as the time adjustment in digital receivers, speech coding, time delay estimation and modeling of musical instruments [2]- [7].…”

Section: Introductionmentioning

confidence: 99%

Performing fractional delay via fractional singular spectrum analysis

Zhou

Ling

Huang

et al. 2021

SIViP

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This paper proposes a fractional singular spectrum analysis (SSA) based method for performing the fractional delay. First, the input sequence is divided into two overlapping sequences with the first sequence being the input sequence without its last point and the second sequence being the input sequence without its first point. Then, the singular value decompositions (SVD) are performed on the trajectory matrices constructed based on these two sequences. Next, the designs of both the right unitary matrix and the left unitary matrix for generating the new trajectory matrix are formulated as the quadratically constrained quadratic programing problems. The analytical solutions of these quadratically constrained quadratic programing problems are derived via the SVD approach. Finally, the fractional SSA components are obtained by performing the diagonal averaging operation and the fractional delay sequence is obtained by summing up all the fractional SSA components together. Since the fractional SSA operations are nonlinear and adaptive, our proposed method is a kind of nonlinear and adaptive approach for performing the fractional delay. Besides, by discarding some fractional SSA components, the joint fractional delay operation and the denoising operation can be performed simultaneously.

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