Results 31 to 40 of about 6,305 (217)

A New Generalized Projection and Its Application to Acceleration of Audio Declipping

Axioms, 2019
In convex optimization, it is often inevitable to work with projectors onto convex sets composed with a linear operator. Such a need arises from both the theory and applications, with signal processing being a prominent and broad field where convex ...
Pavel Rajmic, Pavel Záviška, Vítězslav Veselý, Ondřej Mokrý   +3 more
doaj   +1 more source

Air–Rail Connectivity Index: A Comprehensive Study of Multimodal Journeys

Engineering Proceedings
To enhance the accessibility and efficiency of airports, the concept of airport connectivity is extended to High-Speed Rail (HSR), as major hub airports now have direct access to an HSR station.
Clara Buire, Slavica Dožić, Danica Babić, Ismini Stroumpou, Josep L. Larriba, Esteban Gatein, Ruth Parajó   +6 more
doaj   +1 more source

Dynamic MR Image Reconstruction From Highly Undersampled (k, t)-Space Data Exploiting Low Tensor Train Rank and Sparse Prior

IEEE Access, 2020
Dynamic magnetic resonance imaging (dynamic MRI) is used to visualize living tissues and their changes over time. In this paper, we propose a new tensor-based dynamic MRI approach for reconstruction from highly undersampled (k, t)-space data, which ...
Shuli Ma, Huiqian Du, Wenbo Mei
doaj   +1 more source

Twofold Sparsity: Joint Bit- and Network-Level Sparsity for Energy-Efficient Deep Neural Network Using RRAM Based Compute-In-Memory

IEEE Access
On-device intelligence and AI-powered edge devices require compressed deep learning algorithm and energy efficient hardware. Compute-in-memory (CIM) architecture is a more suitable candidate than traditional Complementary Metal-Oxide-Semiconductor (CMOS)
Foroozan Karimzadeh, Arijit Raychowdhury
doaj   +1 more source

Machine Learning Regularization Methods in High-Dimensional Monetary and Financial VARs

Mathematics, 2022
Vector autoregressions (VARs) and their multiple variants are standard models in economic and financial research due to their power for forecasting, data analysis and inference. These properties are a consequence of their capabilities to include multiple
Javier Sánchez García, Salvador Cruz Rambaud   +1 more
doaj   +1 more source

Discrepancy and sparsity

Journal of Combinatorial Theory, Series B
We study the connections between the notions of combinatorial discrepancy and graph degeneracy. In particular, we prove that the maximum discrepancy over all subgraphs $H$ of a graph $G$ of the neighborhood set system of $H$ is sandwiched between $Ω(\log\mathrm{deg}(G))$ and $\mathcal{O}(\mathrm{deg}(G))$, where $\mathrm{deg}(G)$ denotes the degeneracy
Grobler, Mario, Jiang, Yiting, Ossona de Mendez, Patrice, Siebertz, Sebastian, Vigny, Alexandre   +4 more
openaire   +2 more sources

An Efficient Sparse Twin Parametric Insensitive Support Vector Regression Model

Mathematics
This paper proposes a novel sparse twin parametric insensitive support vector regression (STPISVR) model, designed to enhance sparsity and improve generalization performance.
Shuanghong Qu, Yushan Guo, Renato De Leone, Min Huang, Pu Li   +4 more
doaj   +1 more source

Non-Linear Regularized Attenuation Compensation for Microwave Breast Imaging

IEEE Open Journal of Signal Processing, 2023
We develop non-linear optimization algorithms for attenuation compensation of rapidly time-varying microwave signals in the context of breast imaging.
Nasser Kazemi, Elise Fear
doaj   +1 more source

DPC-SMOTE Over-sampling Algorithm for Imbalanced Data Classification

Journal of Harbin University of Science and Technology
An oversampling algorithm based on density peak clustering is proposed to solve the problem of noise and imbalance among classes in imbalanced data sets.
LIU Zhihan, ZHANG Zhonglin, ZHAO Lei
doaj   +1 more source

A Novel Hybrid Item-Based Similarity Method to Mitigate the Effects of Data Sparsity in Multi-Criteria Collaborative Filtering

IEEE Access
Data sparsity presents a significant challenge for Recommendation Systems, particularly in neighborhood-based approaches that rely on co-ratings to compute similarity.
Burcu Demirelli Okkalioglu
doaj   +1 more source