Doubly Stochastic Processing on Jacket Matrices
Summary :
In this letter, we define the generalized doubly stochastic processing via Jacket matrices of order-2n and 2n with the integer, n≥2. Different from the Hadamard factorization scheme, we propose a more general case to obtain a set of doubly stochastic matrices according to decomposition of the fundaments of Jacket matrices. From order-2n and order-2n Jacket matrices, we always have the orthostochastoc case, which is the same as that of the Hadamard matrices, if the eigenvalue λ1 = 1, the other ones are zeros. In the case of doubly stochastic, the eigenvalues should lead to nonnegative elements in the probability matrix. The results can be applied to stochastic signal processing, pattern analysis and orthogonal designs.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E89-A No.11 pp.3368-3372
- Publication Date
- 2006/11/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e89-a.11.3368
- Type of Manuscript
- LETTER
- Category
- General Fundamentals and Boundaries
Authors
Keyword
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Jia HOU, Moon Ho LEE, Kwangjae LEE, "Doubly Stochastic Processing on Jacket Matrices" in IEICE TRANSACTIONS on Fundamentals,
vol. E89-A, no. 11, pp. 3368-3372, November 2006, doi: 10.1093/ietfec/e89-a.11.3368.
Abstract: In this letter, we define the generalized doubly stochastic processing via Jacket matrices of order-2n and 2n with the integer, n≥2. Different from the Hadamard factorization scheme, we propose a more general case to obtain a set of doubly stochastic matrices according to decomposition of the fundaments of Jacket matrices. From order-2n and order-2n Jacket matrices, we always have the orthostochastoc case, which is the same as that of the Hadamard matrices, if the eigenvalue λ1 = 1, the other ones are zeros. In the case of doubly stochastic, the eigenvalues should lead to nonnegative elements in the probability matrix. The results can be applied to stochastic signal processing, pattern analysis and orthogonal designs.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e89-a.11.3368/_p
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@ARTICLE{e89-a_11_3368,
author={Jia HOU, Moon Ho LEE, Kwangjae LEE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Doubly Stochastic Processing on Jacket Matrices},
year={2006},
volume={E89-A},
number={11},
pages={3368-3372},
abstract={In this letter, we define the generalized doubly stochastic processing via Jacket matrices of order-2n and 2n with the integer, n≥2. Different from the Hadamard factorization scheme, we propose a more general case to obtain a set of doubly stochastic matrices according to decomposition of the fundaments of Jacket matrices. From order-2n and order-2n Jacket matrices, we always have the orthostochastoc case, which is the same as that of the Hadamard matrices, if the eigenvalue λ1 = 1, the other ones are zeros. In the case of doubly stochastic, the eigenvalues should lead to nonnegative elements in the probability matrix. The results can be applied to stochastic signal processing, pattern analysis and orthogonal designs.},
keywords={},
doi={10.1093/ietfec/e89-a.11.3368},
ISSN={1745-1337},
month={November},}
Copy
TY - JOUR
TI - Doubly Stochastic Processing on Jacket Matrices
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3368
EP - 3372
AU - Jia HOU
AU - Moon Ho LEE
AU - Kwangjae LEE
PY - 2006
DO - 10.1093/ietfec/e89-a.11.3368
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E89-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2006
AB - In this letter, we define the generalized doubly stochastic processing via Jacket matrices of order-2n and 2n with the integer, n≥2. Different from the Hadamard factorization scheme, we propose a more general case to obtain a set of doubly stochastic matrices according to decomposition of the fundaments of Jacket matrices. From order-2n and order-2n Jacket matrices, we always have the orthostochastoc case, which is the same as that of the Hadamard matrices, if the eigenvalue λ1 = 1, the other ones are zeros. In the case of doubly stochastic, the eigenvalues should lead to nonnegative elements in the probability matrix. The results can be applied to stochastic signal processing, pattern analysis and orthogonal designs.
ER -
English
