Results 71 to 80 of about 6,368,085 (214)
The Jordan cononical form of a product of a Hermitian and a positive semidefinite matrix
The authors characterize matrices C which are the product AB of a positive semidefinite matrix A and a Hermitian matrix B, by the fact that \(C^ 2\) is diagonalizable and has nonnegative eigenvalues. They give applications of this result.
Hong, Yoopyo, Horn, Roger A.
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Positive semidefinite solution to matrix completion problem and matrix approximation problem
In this paper, firstly, we discuss the following matrix completion problem in the spectral norm: ?(A B B* X)?2 < 1 subject to (A B B* X) ? 0. The feasible condition for the above problem is established, in this case, the general positive semidefinite solution and its minimum rank are presented.
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A Quantile Model of Firm Investment
ABSTRACT Are firms risk averse? We propose a dynamic model of firm investment under uncertainty that captures firms' risk attitudes through quantile preferences. The firm maximizes its present value, defined as current profits and investment plus the discounted value of the τ$\tau$‐quantile of its value next period.
Heitor Almeida +3 more
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Trace inequalities for positive semidefinite matrices
Certain trace inequalities for positive definite matrices are generalized for positive semidefinite matrices using the notion of the group generalized inverse.
Choudhury Projesh Nath, Sivakumar K.C.
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The Evolution of Interest‐Rate Models: From the Yield Curve to the Swaption Cube
ABSTRACT Interest‐rate modelling is often taught as a catalogue of competing stochastic equations, obscuring why models were created and why modern sell‐side desks use several simultaneously. This survey reorganises the field around five layers of a pricing architecture: curve construction; arbitrage‐free dynamics; volatility‐smile representation ...
Xuan Feng +2 more
wiley +1 more source
PSDBoost: matrix-generation linear programming for positive semidefinite matrices learning
In this work, we consider the problem of learning a positive semidefinite matrix. The critical issue is how to preserve positive semidefiniteness during the course of learning. Our algorithm is mainly inspired by LPBoost [1] and the general greedy convex
Welsh, A. +5 more
core +1 more source
Operational Choices for Risk Aggregation in Insurance: PSDization and SCR Sensitivity
This work addresses crucial questions about the robustness of the PSDization process for applications in insurance. PSDization refers to the process that forces a matrix to become positive semidefinite.
Xavier Milhaud +2 more
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Frequency‐dependent contraction rates for the Bayesian method to the inverse source problem
Abstract This paper addresses an inverse source problem for acoustic waves in a range of frequencies. Our study has two main goals. First, although the problem is severely ill‐posed with a logarithmic stability estimate, we demonstrate, through careful analysis of the forward map's singular values, that increasing the frequency range enhances stability,
Pu‐Zhao Kow, Jenn‐Nan Wang
wiley +1 more source
Data dissemination scheduling algorithm for V2R/V2V in multi-channel VANET
Considering that the data dissemination in multi-channel VANET (vehicular ad hoc network),a cooperative data dissemination scheduling algorithm was introduced for V2R(vehicle to roadside unit) and V2V(vehicle to vehicle).The algorithm created initial ...
Xin PENG +5 more
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Norm inequalities for functions of matrices
In this paper, we prove several spectral norm and unitarily invariant norm inequalities for matrices in which the special cases of our results present some known inequalities. Also, some of our results give interpolating inequalities which are related to
Ahmad Al-Natoor
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