A power method for computing singular value decomposition

Key Points

• Finds an efficient method for computing singular value decomposition from large matrices.
• Shows improved convergence rates and accuracy for singular values through the proposed power method approach.
• Observational analysis of numerical algorithms reveals robust performance across various datasets.
• Highlights the need for further validation in diverse practical applications beyond theoretical frameworks.