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9 articles for “Signal-to-Noise Ratio (SNR)”
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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From Noise to Insight: An Academic Study of Electrical Signal Processing
Abstract: Electrical signal processing is very important for turning raw, often noisy data into useful and actionable information. This article gives a simple and easy-to-understand summary of the basic ideas and methods used in electrical signal processing, such as filtering, signal representation, modulation, and spectrum analysis. The focus is on how to effectively eliminate noise and interference to improve the quality and dependability of signals. The conversation connects ideas from theory …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Noise-Resilient QPSK Modem for Reliable Communication for Green Communication
Abstract: The channel noise is the severely degraded the performance of communication system and that also limits the maximum data transmission rate. Hence, it is required to design a demodulator in a receiver which overcomes the effect of noise in the received signal, reconstructs un-corrupted information signal and improves data rate. In QPSK, noise effect the phase of the modulated signal and that causes error in the information signal. This study …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 36–46 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Influence of Alkali Treatment on the Tensile Properties of The Hybrid Fiber Reinforced Polymer Matrix Composite
Abstract: In this study, the effect of alkali treatment on the tensile strength of the hibiscus fiber, gongura fiber, and treated madar fiber-reinforced Polymer Matrix Composite (PMC) is studied. The Sodium Hydroxide (NaOH) solution is utilized for madar fiber treatment. The traditional hand layup methodology was used for fabrication. The influence of tensile property control variables such as duration of fiber treatment, concentration of NaOH for treatment, and proportion of fiber …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 28–34 Read article
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Optimized Receivers for Underwater Visible Light Communication
Abstract: For uses like ocean exploration, environmental monitoring, and underwater data transfer, wireless communication under water is crucial. Conventional acoustic and radio frequency communication methods suffer from low bandwidth, high latency, and severe signal attenuation in underwater environments. With its high data rate and low propagation delay, Visible Light Communication (VLC) provides a promising alternative. In this work, an underwater VLC system is implemented using Light Emitting Diodes (LEDs) with intensity …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 22–33 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 17, Issue 2, 2026 Read article