基于小波滤波器组和支持向量机的地震识别硬件友好算法

O. Saad, A. Shalaby, Koji Inoue, M. Sayed
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引用次数: 0

摘要

地震与爆炸的区分是地震学领域的主要挑战之一。在某些情况下,爆炸被记录为地震,反之亦然,这可能会污染地震目录。为了支持实时地震应用,需要快速识别。该判别算法基于小波滤波器库提取判别特征,支持向量机(SVM)作为分类器。因此;我们提出在现场可编程门阵列(FPGA)上优化识别算法的硬件实现。首先,采用优化后的提升方案实现小波滤波器组。然后利用线性分类器实现支持向量机分类器。最后,我们优化了识别算法的硬件资源,使其能够在低成本的FPGA TE0711板(Xilinx Artix7)上使用。实现的设计分别利用了FPGA查找表(LUT)和寄存器资源的1.2%和39.8%。
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Hardware Friendly Algorithm for Earthquakes Discrimination Based on Wavelet Filter Bank and Support Vector Machine
Discrimination between earthquakes and explosion is one of the main challenges in the field of seismology. In some cases, the explosions recorded as an earthquake or vice verse, which can contaminate the seismic catalog. Rapid discrimination is required to support the real-time seismic application. The discrimination algorithm is based on a wavelet filter bank to extract the discriminative features, and support vector machine (SVM) as a classifier. Therefore; we propose to optimize the hardware implementation of the discrimination algorithm on Field Programmable Gate Array (FPGA). First, we implement the wavelet filter bank using optimized lifting scheme. Then, we utilize the linear classifier to implement the SVM classifier. Finally, we optimize the hardware resources of the discrimination algorithm to be utilized on low-cost FPGA called TE0711 board (Xilinx Artix7). The implemented design is utilized 1.2% and 39.8% of the FPGA's Look Up Table (LUT) and register resources, respectively.
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