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12 articles for “Signal Reconstruction”
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 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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A Comprehensive Review of Deep Compressive Sensing for Efficient IoT Data Management
Abstract: The Internet of Things has revolutionized data-driven ecosystems and offers advanced services, such as live monitoring and automation in various domains: smart cities, healthcare, and industrial automation. However, with the exponential growth of IoT devices, comes a large amount of data generation, which poses considerable problems like network congestion, latency, and energy inefficiency. Compressive sensing (CS), one of the newest signal processing methodologies, has emerged as an enabler to meet …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 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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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
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Spectral Mapping and Tracking Error of MBOC signal and Wavelet based GNSS receiver
Abstract: This research paper delves into the historical evolution and contemporary state of the art in navigation technologies, emphasizing the paramount importance of reliable positioning systems. Tracing the journey from ancient primitive methods to the present-day Global Navigation Satellite Systems (GNSS), with a focus on the Global Positioning System (GPS), the paper explores the diverse instruments and methods developed by civilizations throughout history to determine location and navigate effectively. The main …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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From High-Resolution Optics to High-Bandwidth Telemetry: The Evolution of Deep-Space Imaging Satellites
Abstract: The development of deep space imaging satellites has significantly enhanced satellite communication and space exploration capabilities. Earlier satellite systems relied on low-resolution imaging and conventional radio-frequency (RF) communication, which limited data transmission rates and image quality. With advancements in technology, modern satellites are equipped with high-resolution optical systems capable of capturing detailed images of celestial bodies. Furthermore, the introduction of high-bandwidth telemetry systems, such as Ka- band and optical (laser) …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 34–40 Read article
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Cross-Domain Comparative Analysis of Microwave Imaging Systems for Medical Diagnostics and Industrial Testing
Abstract: Microwave imaging is gaining significant traction as a non-ionizing, low-cost, and portable alternative to conventional diagnostic and inspection modalities in both medical and industrial domains. Leveraging the dielectric contrast between healthy and anomalous tissues or materials, microwave imaging systems enable early-stage detection and characterization of pathological or structural anomalies. This review provides a detailed comparative analysis of microwave imaging systems tailored for three critical applications: breast cancer detection, brain stroke …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 39–48 Read article
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Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 Read article
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Efficient Gabor Filter Design Using Verilog HDL with Multiplier-accumulator (MAC) Implementation
Abstract: This paper introduces a novel and enhanced Gabor filter design aimed at addressing the demands of image processing applications using the Verilog Hardware Description Language (HDL). Specifically, it leverages the Reconstruct Gabor filter technique to elevate the performance and quality of standard image outputs. The primary objective of this research endeavor is to simplify the study, conduct an in-depth analysis, and substantially enhance the design's efficiency, all while ensuring the …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 2, 2023 · pp. 40–46 Read article
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Bone Grafting in Dentistry: From Biological Principles to Contemporary Regenerative Applications
Abstract: Bone grafting plays a pivotal role in contemporary regenerative dentistry by enabling predictable reconstruction of alveolar bone defects resulting from periodontal disease, tooth extraction, trauma, or pathology. Adequate bone volume and quality are essential prerequisites for successful implant placement, periodontal regeneration, and long-term functional and esthetic outcomes. Bone graft materials act as biological or synthetic scaffolds that facilitate new bone formation through the primary mechanisms of osteogenesis, osteoinduction, osteoconduction, and …
Published in Research and Reviews: A Journal of Dentistry · Vol. 17, Issue 1, 2026 · pp. 6–13 Read article