The -(anti-)Hermitian solution to a constrained Sylvester-type generalized commutative quaternion matrix equation
XY Chen, QW Wang - Banach Journal of Mathematical Analysis, 2023 - Springer
We present some practical necessary and sufficient conditions for the existence of an η-(anti-
) Hermitian solution to a constrained Sylvester-type generalized commutative quaternion …
) Hermitian solution to a constrained Sylvester-type generalized commutative quaternion …
The Hermitian solution to a new system of commutative quaternion matrix equations
Y Zhang, QW Wang, LM **e - Symmetry, 2024 - mdpi.com
This paper considers the Hermitian solutions of a new system of commutative quaternion
matrix equations, where we establish both necessary and sufficient conditions for the …
matrix equations, where we establish both necessary and sufficient conditions for the …
Global exponential stability of Clifford-valued recurrent neural networks
J Zhu, J Sun - Neurocomputing, 2016 - Elsevier
This paper investigates global exponential stability of a class of Clifford-valued recurrent
neural networks. By using Brouwer's fixed point theorem, the existence of the equilibrium …
neural networks. By using Brouwer's fixed point theorem, the existence of the equilibrium …
Hyperbolic Hopfield neural networks
M Kobayashi - IEEE transactions on neural networks and …, 2012 - ieeexplore.ieee.org
In recent years, several neural networks using Clifford algebra have been studied. Clifford
algebra is also called geometric algebra. Complex-valued Hopfield neural networks …
algebra is also called geometric algebra. Complex-valued Hopfield neural networks …
A broad class of discrete-time hypercomplex-valued Hopfield neural networks
In this paper, we address the stability of a broad class of discrete-time hypercomplex-valued
Hopfield-type neural networks. To ensure the neural networks belonging to this class always …
Hopfield-type neural networks. To ensure the neural networks belonging to this class always …
Twin-multistate commutative quaternion Hopfield neural networks
M Kobayashi - Neurocomputing, 2018 - Elsevier
The complex-valued Hopfield neural network (CHNN) can deal with multi-level information,
and has often been applied to the storage of image data. The quaternion Hopfield neural …
and has often been applied to the storage of image data. The quaternion Hopfield neural …
Regularization method for reduced biquaternion neural network
S Gai, X Huang - Applied Soft Computing, 2024 - Elsevier
A reduced biquaternion neural network (RQNN) has achieved significant success in
machine learning. However, as the reduced biquaternion algebra system contains infinite …
machine learning. However, as the reduced biquaternion algebra system contains infinite …
Noise robust projection rule for hyperbolic Hopfield neural networks
M Kobayashi - IEEE Transactions on Neural Networks and …, 2019 - ieeexplore.ieee.org
A complex-valued Hopfield neural network (CHNN) is a multistate Hopfield model. Low
noise tolerance is the main disadvantage of CHNNs. The hyperbolic Hopfield neural …
noise tolerance is the main disadvantage of CHNNs. The hyperbolic Hopfield neural …
Solving the Dual Generalized Commutative Quaternion Matrix Equation AXB= C.
L Shi, QW Wang, LM **e, XF Zhang - Symmetry (20738994), 2024 - search.ebscohost.com
Dual generalized commutative quaternions have broad application prospects in many fields.
Additionally, the matrix equation AXB= C has important applications in mathematics and …
Additionally, the matrix equation AXB= C has important applications in mathematics and …
Least-squares solutions of the reduced biquaternion matrix equation AX=B and their applications in colour image restoration
HH Kösal - Journal of Modern Optics, 2019 - Taylor & Francis
In this study, we derive the expressions of the minimal norm least-squares solution for the
reduced biquaternion (RB) matrix equation AX= B by using the e 1− e 2 form of RB matrices …
reduced biquaternion (RB) matrix equation AX= B by using the e 1− e 2 form of RB matrices …