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Ali Parsai Kia

As seen in: Wiley Online Library
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Articles

TinyML Autoencoder-Based On-Board Denoising and Drift Detection in Electrochemical Sensors

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By Byunghyun Ban, Ali Parsai Kia, Batuhan Uzunoglu
| preprints.org
You are already at the latest version Wearable electrochemical biosensors often producevoltammetric signals that are corrupted by noise and long-term drift.Effective on-device denoising is critical to improve signal quality anddetect anomalies due to sensor drift or interference. This paperexplores lightweight TinyML models for denoising and drift detectionin wearable sensor voltammograms under the strict memoryconstraints of microcontrollers.
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Intelligent switching gain based sliding mode control for optimization of power consumption in cooperative manipulators

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By Ali Parsai Kia, Moharam Habibnejad Korayem, Naeim Yousefi Lademakhi
| Wiley Online Library Verified
CONFLICT OF INTEREST STATEMENT The author(s) declared no potential conflict of interests with respect to the research, authorship and/or publication of this article. REFERENCES 1, . An adaptive fuzzy strategy for motion control of robot manipulators. Soft Comput. 2005; 9(3): 185-193. 2, . Adaptive sliding mode control of dynamic system using RBF neural network. Nonlin Dynam. 2012; 70(2): 1563-1573. 3, . Fuzzy-neural-network inherited sliding-mode control for robot manipulator including actuator dynamics.
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