Hardware Acceleration of Singular Spectral Analysis: A Case Study on NQR Spectroscopy
Singular Spectral Analysis (SSA) is a computationally intensive approach to denoise and detect a time-series signal. It requires the evaluation of eigenvalues and eigenvectors of a covariance matrix, which is the computationally intensive step in the SSA algorithm. The current work presents a f...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Banja Luka
2025-06-01
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| Series: | Electronics |
| Online Access: | https://els-journal.net/wp/?page_id=914 |
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| Summary: | Singular Spectral Analysis (SSA) is a computationally intensive approach to denoise and detect a time-series signal. It requires the evaluation of eigenvalues and eigenvectors of a
covariance matrix, which is the computationally intensive step in the SSA algorithm. The current work presents a feasible approach to implement the algorithm in embedded hardware using a PYNQ-Z2 Field Programmable Gate Array (FPGA) board. We implemented the algorithm using both the Processing System (PS) and the Programmable Logic (PL) of the PYNQ-Z2 System on Chip (SoC) with the help of a High-Level Synthesis (HLS) tool. A case study is carried out on a Nuclear Quadruple Resonance (NQR) signal. The implementation result demonstrates a hardware acceleration of 15.48x with respect to the equivalent software implementation of the algorithm on the ARM Cortex-A9 processor. |
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| ISSN: | 1450-5843 2831-0128 |