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Based on the fundamental principles and characteristics of Singular Value Decomposition (SVD), this article presents a method for image compression using SVD. The method is illustrated through simple examples demonstrating the basic compression process and workflow. Practical image processing implemented through MATLAB programming validates the effectiveness of the approach, with detailed explanations of key functions like svd() for matrix decomposition and imshow() for image visualization.

MATLAB 161 views Tagged

To enable effective search capabilities, the solution space must have meaningful neighborhoods where solutions exhibit similar properties within a finite range - known as the "proximity implies similarity" principle. This requirement is crucial for the Fireworks Algorithm's optimization effectiveness. In practical implementation, whether using discrete or continuous encoding during problem modeling and solution representation, this fundamental condition must be satisfied. Additionally, the algorithm achieves balance between global and local search capabilities through resource allocation and information exchange among fireworks based on their relative fitness values, while the explosive search mechanism enables...

MATLAB 243 views Tagged