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431 articles for “Signal”
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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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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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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 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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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Investigation of the Modulation of Solar Wind and Communication Signal Waves and its Effect on Earth Navigation System
Abstract: The solar wind is an uninterrupted outflow of magnetized plasma from the solar corona that reaches interplanetary space and accumulates in the earth's outer atmosphere disturbing the navigation and communication systems. Incoming solar winds move across in the space, form waves during times of robust solar activity. These waves undergo modification in Earth's atmospheric and interfere with communication signal. Navi-Aid Airport frequency communication data, together with ACE Satellite Electron and …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 3, 2024 · pp. 26–32 Read article
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AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Nutrient-Mediated Activation of Cellular Signaling Pathways: Mechanistic Insights into Attenuation of Toxin Induced Inflammation in Food Animals
Abstract: Dietary and environmental toxins remain a persistent challenge in food animal production, where subclinical and clinical inflammation compromises health, productivity, and food safety. Toxin induced inflammation is driven by oxidative stress, mitochondrial dysfunction, and dysregulated immune signaling, resulting in impaired metabolic efficiency and increased disease susceptibility. Recent advances in nutritional science have revealed that nutrients act not only as substrates for growth but also as signaling molecules capable of modulating …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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“Microvita‑Inspired Informational Field Dynamics as a Nonlinear Signal‑Generation Mechanism in Matter–Life–Mind Systems”
Abstract: Recognizing how matter, life, and consciousness relate to one another continues to be among the most essential challenges faced by modern science. Contemporary physical theories successfully describe the behavior of elementary particles and large-scale cosmological structures, yet they do not fully explain the emergence of informational complexity and organized patterns observed in biological and cognitive systems. This study proposes a theoretical framework in which Microvita are interpreted as subtle informational …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Analysis of the Wave Function of Perturbed Ionospheric Waves for Communication Signals
Abstract: Our daily communications and navigational systems rely on the ionospheric conditions, and this sensitive region of the atmosphere is traversed and governed by radio and global positioning system (GPS) signals which broadcast on bouncing off the ionosphere to reach their destinations. All the communication signals can be interfered with modifications because of the changes in the ionosphere's density and its composition so that large percentage of the free electrons in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 3, 2024 · pp. 13–20 Read article
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Arabidopsis thaliana. (L.) Heynh Multifunctional Sensor Proteins and Signaling Networks Plant Photoreceptors
Abstract: Light is a crucial environmental cue for the growth and development of plants as well as the production of photosynthetic energy. In order to recognize and process information from incoming light, plants employ sophisticated mechanisms. With the model plant Arabidopsis thaliana, five different types of photoreceptors have been found. (L.) Heynh Photoreceptors play a specialized and/or recurring role in fine-tuning many aspects of the plant's life cycle. Unlike mobile animals, …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 1, Issue 2, 2023 · pp. 08–24 Read article
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Ionospheric Disturbances and Communication Signal anomalies due to eruption of Solar flare Activity
Abstract: Solar flares tend to disrupt the radio communication systems and modulate active radio wave frequencies, particularly the ones that have utility in High Frequency (HF) radio signals and transceiver signals because they are the ones who find utility in radio communications systems. Solar flares generate electromagnetic waves which interact with the earth’s atmospheric medium and travel through the ionospheric region. These electromagnetic waves modulate radio frequency communication signals. This modulation …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 7–14 Read article
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Host-Microbiota Crosstalk in the Rumen: Signaling Pathways for Nutrient Metabolism and Disease Resilience in Dairy Cows
Abstract: The rumen serves as a highly intricate microbial ecosystem, fundamentally responsible for the degradation of fibrous plant materials in ruminant. The intricate host-microbiota crosstalk within the rumen significantly influences nutrient metabolism, growth, and health outcomes in livestock. The interaction between the host and its microbial community, mediated through signaling pathways including the production of short-chain fatty acids (SCFAs), bile acids, and various metabolites, is crucial for enhancing nutrient absorption, fermentation …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 15, Issue 1, 2025 · pp. 29–41 Read article
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Diet-Gene Interactions in Farm Animals: Molecular Dynamics, Gene Expressions, Signalling Pathways and Precision Nutrition for Sustainable Productivity
Abstract: Diet-gene interactions represent a central mechanism through which nutrition influences growth, health, and productivity in farm animals. Recent advances in molecular biology and genetics have revealed that nutrients act not only as metabolic substrates but also as signalling molecules capable of modulating gene expression, cellular pathways, and epigenetic regulation. This review synthesizes current knowledge on the molecular dynamics of nutrient utilization in farm animals, with emphasis on nutrigenomic responses, nutrient …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Synthesis of Brassinosteroid with Signaling and Response to Abiotic Stress: Review
Abstract: Brassinosteroids (BRs) are a group of plant steroid hormones with multiple roles in plant growth, development, and responses to stresses and signaling functions to promote cell expansion and cell division and plays a role in etiolation and reproduction. The entire synthetic pathway of sterol biosynthesis is brassinolide (BL) from the general campesterol synthesis pathway in Arabidopsis. Campesterol converts to BL in two different ways campesterol dependent or campesterol independent pathway. …
Published in Research & Reviews : Journal of Botany Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article