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Article

Band-Limited Proximal FISTA for Efficient Sparse Harmonic Recovery on MCU

1
School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
2
School of Electronics Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
*
Author to whom correspondence should be addressed.
Big Data Cogn. Comput. 2026, 10(7), 205; https://doi.org/10.3390/bdcc10070205 (registering DOI)
Submission received: 22 December 2025 / Revised: 29 January 2026 / Accepted: 21 June 2026 / Published: 25 June 2026
(This article belongs to the Special Issue Cognitive Computing for Image, Signal, and Biomedical Applications)

Abstract

Compressed sensing (CS) enables signal reconstruction from fewer measurements when the signal is sparse in a transform domain. However, executing 1-regularized recovery on MCU-class hardware is challenging due to limited compute resources and the cost of repeated forward and adjoint operator evaluations. This paper presents a band-limited proximal variant of FISTA that enforces known spectral support during thresholding, restricting the effective optimization domain without changing the measurement model. We implement a complete CS reconstruction pipeline on an STM32F407 (Cortex-M4) using CMSIS-DSP FFT/IFFT kernels and evaluate it using ECG waveforms acquired through an AD8232 front end as benchmark signals. With M=340 measurements (33% of uniform sampling), the embedded implementation achieves a PRDN of 24.38%, closely matching MATLAB references (CVX: 22.64%, FISTA: 22.39%) under identical hyperparameters. Cycle-accurate profiling shows that FFT/IFFT-based forward/adjoint operators dominate the per-iteration runtime. Under a 60 Hz band-limited setting, the required iterations are reduced from 30 to 16 with an acceptable PRDN, demonstrating a practical trade-off between reconstruction accuracy and computational cost on MCU-class devices.
Keywords: compressed sensing; sparse recovery; band-limited proximal operator; ℓ1-regularized optimization; FISTA; Cortex-M4 compressed sensing; sparse recovery; band-limited proximal operator; ℓ1-regularized optimization; FISTA; Cortex-M4

Share and Cite

MDPI and ACS Style

Cho, S.; Kim, M.; Park, D. Band-Limited Proximal FISTA for Efficient Sparse Harmonic Recovery on MCU. Big Data Cogn. Comput. 2026, 10, 205. https://doi.org/10.3390/bdcc10070205

AMA Style

Cho S, Kim M, Park D. Band-Limited Proximal FISTA for Efficient Sparse Harmonic Recovery on MCU. Big Data and Cognitive Computing. 2026; 10(7):205. https://doi.org/10.3390/bdcc10070205

Chicago/Turabian Style

Cho, Seongho, Minjung Kim, and Daejin Park. 2026. "Band-Limited Proximal FISTA for Efficient Sparse Harmonic Recovery on MCU" Big Data and Cognitive Computing 10, no. 7: 205. https://doi.org/10.3390/bdcc10070205

APA Style

Cho, S., Kim, M., & Park, D. (2026). Band-Limited Proximal FISTA for Efficient Sparse Harmonic Recovery on MCU. Big Data and Cognitive Computing, 10(7), 205. https://doi.org/10.3390/bdcc10070205

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