Simulation Algorithm for Duffing Oscillator
Simulation algorithm for the Duffing oscillator. By modifying program parameters, different state diagrams can be generated for studying nonlinear system behaviors.
Explore MATLAB source code curated for "算子" with clean implementations, documentation, and examples.
Simulation algorithm for the Duffing oscillator. By modifying program parameters, different state diagrams can be generated for studying nonlinear system behaviors.
Implementation of spatial domain filtering with five distinct operators to achieve effective image deblurring results through various convolution techniques.
Experimental report on medical image segmentation (with source code) featuring: comparative analysis of edge detection using various operators (Sobel, Prewitt, Roberts, Laplacian); threshold-based segmentation; and segmentation discussion using watershed method with implementation insights.
Whale Optimization Algorithm (WOA) is a novel metaheuristic optimization technique designed for solving optimization problems. The algorithm employs three core operators to simulate humpback whales' predatory behaviors: encircling prey, bubble-net feeding, and hunting mechanisms. It is specifically tailored for single-objective optimization tasks. The copyright belongs to the original developers, to whom we extend our respect. Key implementations include mathematical modeling of whale movement patterns and position updates using logarithmic spiral equations.
Local Binary Patterns as an operator for describing image texture characteristics with code implementation insights
MATLAB implementation of image sharpening techniques using various operators including Sobel, Laplacian, and Prewitt filters for edge enhancement and detail processing
Genetic Algorithm Toolbox featuring crossover, inheritance, and operators - excellent for optimization problems
This code implements the source program described in the paper "Saliency Detection via Graph-Based Manifold Ranking" by Chuan Yang, Lihe Zhang, Huchuan Lu, Ming-Hsuan Yang, and Xiang Ruan. Key feature: Implements Canny edge detection to compute binary edge maps using MATLAB's edge() function with specific threshold parameters.
Implementation and comparison of edge detection using Roberts, Prewitt, Sobel, Marr, and Canny operators on input images, with performance evaluation against MATLAB's built-in edge detection functions through code analysis and practical demonstrations.
A versatile edge detection function that implements Sobel, Prewitt, Roberts, Marr, and Canny operators through parameter configuration, featuring gradient-based and zero-crossing algorithms for comprehensive edge extraction.