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Evaluation of Singular Value Decomposition (SVD) Enhanced Upscaling in Reservoir Simulation
Volume 11: Petroleum Technology, 2020Abstract Reservoir upscaling is an important step in reservoir modeling for converting highly detailed geological models to simulation grids. It substitutes a heterogeneous model that consists of high-resolution fine grid cells with a lower resolution reduced-dimension homogeneous model using averaging schemes.
Mayank Tyagi, Xu Zhou
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Journal of Sound and Vibration, 2020
Gear tooth crack fault detection and severity assessment using vibration analysis rely on the extraction of fault induced periodic impulses. Singular value decomposition (SVD)-based methods have been used by researchers for periodic impulses extraction ...
Yuejian Chen, Xihui Liang, M. Zuo
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Gear tooth crack fault detection and severity assessment using vibration analysis rely on the extraction of fault induced periodic impulses. Singular value decomposition (SVD)-based methods have been used by researchers for periodic impulses extraction ...
Yuejian Chen, Xihui Liang, M. Zuo
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, 2020
It is of great importance to develop advanced soft sensors for ensuring the safety and stability of complex industrial processes. Unluckily, with the increasing scale of chemical processes, it becomes more and more demanding to develop soft sensor with ...
Yanlin He, Ye Tian, Yuan Xu, Qun Zhu
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It is of great importance to develop advanced soft sensors for ensuring the safety and stability of complex industrial processes. Unluckily, with the increasing scale of chemical processes, it becomes more and more demanding to develop soft sensor with ...
Yanlin He, Ye Tian, Yuan Xu, Qun Zhu
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SVD-LLM V2: Optimizing Singular Value Truncation for Large Language Model Compression
North American Chapter of the Association for Computational LinguisticsDespite significant advancements, the practical deployment of Large Language Models (LLMs) is often hampered by their immense sizes, highlighting the need for effective compression techniques.
Xin Wang +4 more
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Mechanical systems and signal processing, 2019
Singular value decomposition (SVD) is widely used in condition monitoring of modern machine for its unique advantages. A novel relative change rate of singular value kurtosis (SVK) is proposed in order to determine the reconstructed order of singular ...
Hua Li, Tao Liu, Xing Wu, Qing Chen
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Singular value decomposition (SVD) is widely used in condition monitoring of modern machine for its unique advantages. A novel relative change rate of singular value kurtosis (SVK) is proposed in order to determine the reconstructed order of singular ...
Hua Li, Tao Liu, Xing Wu, Qing Chen
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On Properties and Structure of the Analytic Singular Value Decomposition
IEEE Transactions on Signal ProcessingWe investigate the singular value decomposition (SVD) of a rectangular matrix $\boldsymbol{\mathit{A}}(z)$ of functions that are analytic on an annulus that includes at least the unit circle.
Stephan Weiss +4 more
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Audio signal deblurring using singular value decomposition (SVD)
2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), 2017Deblurring is the process of removing blurring artifacts from signals, such as blur caused by noise, defocus aberration or motion blur. Blind Convolution for signal separation is an area of research in the field of signal processing from last few decades.
Nilesh M. Patil, Milind U. Nemade
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Search Result Clustering using a Singular Value Decomposition (SVD)
2009There are many search engines in the web, but they return along list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results.
Hussam M. Dahwa Abdulla, Václav Snásel
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Development of an ASIP-based singular value decomposition processor in SVD-MIMO systems
2011 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), 2011In Multiple-Input Multiple-Output (MIMO) wireless systems, singular value decomposition (SVD) is used for a beamforming in SVD-MIMO systems. A beamforming can improve the performance of MIMO transmission because signal interference among antennas is suppressed.
Takaya Kaji +2 more
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Singular value decomposition based recommendation using imputed data
Knowledge-Based Systems, 2019Among widely used recommendation methods, singular value decomposition (SVD) based approaches are the most successful ones. Although SVD-based methods are effective, they suffer from the problem of data sparsity, which could lead to poor recommendation ...
Xiaofeng Yuan +4 more
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