Análisis de vibraciones para el diagnóstico aplicando procesamiento estadístico de orden superior. // Diagnosis by vibration analysis applying higher-order statistics signal processing. by F. E. Hernández Montero, E. Palomino Marín, V. Atxa Uribe, M. Luis Ruiz Barrios

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Estimation of Spatially Varying Parameters with Application to Hyperbolic SPDES by David Angwenyi

“…Parameter estimation is a growing area of interest in statistical signal processing. Some parameters in real-life applications vary in space as opposed to those that are static. …”
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Robust IoT Activity Recognition via Stochastic and Deep Learning by Xuewei Wang, Shihao Wang, Xiaoxi Zhang, Chunsheng Li

“…To address these challenges, we propose a novel framework that synergizes advanced statistical signal processing with state-of-the-art machine learning and deep learning models. …”
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Graph-based fault diagnosis for rotating machinery: Adaptive segmentation and structural feature integration by Moirangthem Tiken Singh

“…Combining graph-theoretic analysis with statistical signal processing eliminates the need for resource-intensive models, making it ideal for industrial fault diagnosis and predictive maintenance applications.…”
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UTILIZATION OF IMAGE AND SIGNAL PROCESSING TECHNIQUES FOR ASSESSMENT OF BUILT HERITAGE CONDITION by Petr Koudelka, Veronika Koudelková, Tomáš Doktor, Ivana Kumpová, Daniel Kytýř, Jaroslav Valach

“…As many historical buildings in the Czech Republic are built using sandstone that can be considered as a typical heterogeneous system, statistical signal processing is a promising approach for determination of the representative volume element (RVE) dimensions. …”
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Robustness and generalisation study of a new regression-based neural network method for capacitors in power electronics by Christian Vorobev, Daniel Vahle, Volker Staudt

“…The novel extrapolation scheme estimates continuous capacitance values not present in the training data by combining regression with additional statistical signal processing. This generalisation performance of this approach is validated using measurement data of an MMC test bench to predict a large range of DC-link capacitance values which were not present in training data. …”
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Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models by Adit Jain, Vikram Krishnamurthy

“…This paper discusses the theory and algorithms for interacting large language model agents (LLMAs) using methods from statistical signal processing and microeconomics. While both fields are mature, their application to decision-making involving interacting LLMAs remains unexplored. …”
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