Results 51 to 60 of about 1,101,519 (253)
Skew Circulant Type Matrices Involving the Sum of Fibonacci and Lucas Numbers
Abstract and Applied Analysis, 2015 Skew circulant and circulant matrices have been an ideal research area and hot issue for solving various differential equations. In this paper, the skew circulant type matrices with the sum of Fibonacci and Lucas numbers are discussed.
Zhaolin Jiang, Yunlan Wei
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An Upper Bound of Fully Entangled Fraction of Mixed States
, 2016 We study the fully entangled fraction of a quantum state. An upper bound is obtained for arbitrary bipartite system.
Huang, Xiaofen +2 more
core +1 more source
Journal of Applied Mathematics, 2013 We propose a new iterative method to find the bisymmetric minimum norm solution of a pair of consistent matrix equations A1XB1=C1, A2XB2=C2. The algorithm can obtain the bisymmetric solution with minimum Frobenius norm in finite iteration steps in the ...
Aijing Liu +2 more
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Approximating the Real Structured Stability Radius with Frobenius-Norm Bounded Perturbations [PDF]
SIAM Journal on Matrix Analysis and Applications, 2017 We propose a fast method to approximate the real stability radius of a linear dynamical system with output feedback, where the perturbations are restricted to be real valued and bounded with respect to the Frobenius norm.
N. Guglielmi +3 more
semanticscholar +1 more source
On subspace distances determined by the Frobenius norm
Linear Algebra and its Applications, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baksalary, Oskar Maria, Trenkler, Götz
openaire +2 more sources
On Skew Circulant Type Matrices Involving Any Continuous Fibonacci Numbers
Abstract and Applied Analysis, 2014 Circulant and skew circulant matrices have become an important tool in networks engineering. In this paper, we consider skew circulant type matrices with any continuous Fibonacci numbers.
Zhaolin Jiang, Jinjiang Yao, Fuliang Lu
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Lower bounds for quantum-inspired classical algorithms via communication complexity [PDF]
QuantumQuantum-inspired classical algorithms provide us with a new way to understand the computational power of quantum computers for practically-relevant problems, especially in machine learning.
Nikhil S. Mande, Changpeng Shao
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Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets [PDF]
, 2016 Nonnegative Matrix Factorization (NMF) with Kullback-Leibler Divergence (NMF-KL) is one of the most significant NMF problems and equivalent to Probabilistic Latent Semantic Indexing (PLSI), which has been successfully applied in many applications.
Ho, Tu Bao, Nguyen, Duy Khuong
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A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios
Journal of Forecasting, Volume 45, Issue 4, Page 1797-1828, July 2026.ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley +1 more source
Deep Fuzzy Clustering Network With Matrix Norm Regularization
IEEE AccessRecently, deep clustering networks, which able to learn latent embedding and clustering assignment simultaneously, attract lots of attention. Among the deep clustering networks, the suitable regularization term is not only beneficial to training of ...
Feiyu Chen, Yan Li, Wei Wang
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