Results 201 to 210 of about 3,814,069 (243)
Advanced Science, EarlyView.A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei +7 more
wiley +1 more source
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An iterative algorithm for searching a scaling matrix for diagonal dominance
Applied Mathematics and Computation, 2005It is well known that a real (or complex) square matrix \(A\) is an \(M\)-matrix (or \(H\)-matrix) if and only if there exists a positive diagonal matrix \(D\) such that \(AD\) is strictly diagonally dominant. The paper introduces a convergent iteration algorithm to compute the scaling matrix \(D\) for irreducible \(M\) (or \(H\)) matrices.
Ting-Zhu Huang
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Beamforming algorithm of diagonal loading based on matrix decomposition
2011 4th IEEE International Conference on Broadband Network and Multimedia Technology, 2011In the beamforming algorithm of the matrix decomposition, through QR decomposition of data matrix, the QR decomposition algorithm transforms the problem of solving the weighted vector into the problem of solving a triangular linear equations, which avoids to estimating and inversing of array signal covariance matrix, improves the robustness of the data;
Zhaohua Zeng
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2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
We propose a new algorithm for approximate joint diagonalization (AJD) with two main advantages over existing state-of-the-art algorithms: Improved overall running speed, especially in large-scale (high-dimensional) problems; and an ability to incorporate specially structured weight-matrices into the AJD criterion. The algorithm is based on approximate
Petr Tichavský, Arie Yeredor
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We propose a new algorithm for approximate joint diagonalization (AJD) with two main advantages over existing state-of-the-art algorithms: Improved overall running speed, especially in large-scale (high-dimensional) problems; and an ability to incorporate specially structured weight-matrices into the AJD criterion. The algorithm is based on approximate
Petr Tichavský, Arie Yeredor
exaly +3 more sources
A Diagonal Checksum Algorithm-Based Fault Tolerance for Parallel Matrix Multiplication
2020 Eighth International Symposium on Computing and Networking Workshops (CANDARW), 2020Algorithm-based fault tolerance (ABFT) has been proposed to complete a program on an unreliable computer that would generate bit flips. A famous ABFT technique is to insert checksums into a parallel matrix multiplication, including LU-decomposition. It can correct a single incorrect element caused by a bit flip in computation and communication.
Michihiro Koibuchi
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A divide-and-conquer algorithm for a symmetric tri-block-diagonal matrix
2012 Proceedings of IEEE Southeastcon, 2012We propose a stable and efficient divide-and-conquer algorithm for computing the eigendecomposition of a symmetric tri-block-diagonal matrix. The matrix can be derived from discretizing Laplace operator eigenvalue in some two-dimensional graphs. All numerical results show that our algorithm is competitive with other methods, such as e.g QR algorithm ...
Binh T. Nguyen +3 more
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The Fast Diagonal-Matrix-Weight IMM Algorithm for Target Tracking
Advanced Materials Research, 2012The diagonal-matrix-weight IMM (DIMM) algorithm can solve the IMM algorithm confusions of probability density functions (PDFs) and probability masses of stochastic process. Combingandfilter，the Fast-IMM algorithm has a better performance both in accuracy and reducing computational complexity.
Yang Fu +3 more
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Adaptive Noise Subspace Estimation Algorithm with an Optimal Diagonal-Matrix Step-Size
Signal Processing Systems Design and Implementation (siPS), IEEE Workshop on, 2007In this paper, we propose a new optimal diagonal-matrix step-size for the fast data projection method (FDPM) algorithm. The proposed step-sizes control the decoupled subspace vectors individually as compared to conventional methods where all the subspace vectors are multiplied by the same step-size value (scalar case). Simulation results show that FDPM
Samir Attallah
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Novel Parallel Multiple Minor Components Extraction Algorithm by Diagonal Matrix Method
Neural Processing Letters, 2023Haidi Dong, Xiangyu Kong
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