Explore MATLAB source code curated for "精确" with clean implementations, documentation, and examples.
Improved Ant Colony Optimization-based path planning system with customizable objective functions and parameters, delivering superior accuracy compared to basic ACO implementations through optimized search mechanisms and multi-factor integration
Monte Carlo simulation is used to calculate European option pricing, offering reasonable accuracy at the cost of significant computational time. This method involves generating multiple random price paths to estimate the option's expected value.
MATLAB implementation of subpixel edge detection algorithm providing higher precision compared to conventional edge detection methods, featuring advanced interpolation techniques and gradient-based approaches for enhanced accuracy.
The ωKA (Omega-K Algorithm) is a prominent method for SAR image formation. This implementation provides both approximate and precise variants of ωKA, with simulation parameters derived from "Synthetic Aperture Radar Imaging: Algorithms and Implementation". The algorithm utilizes Stolt interpolation for target focusing, followed by cross-range and range slicing to evaluate the final image quality.
A fast and accurate first-order sparse image restoration algorithm primarily applied for image denoising, implementing sparse representation and optimization techniques for noise removal.
An original MATLAB program for license plate localization enabling precise positioning through advanced image processing algorithms
This improved technique enables real-time object detection with higher accuracy compared to traditional frame difference methods, implementing advanced multi-frame processing algorithms with optimized thresholding and motion compensation features.
Effective contour extraction solution with simple image import functionality, delivering clear and precise boundary detection through optimized algorithm implementation
The MPPT program employs the traditional Incremental Conductance algorithm, which provides relatively high precision in tracking maximum power points for photovoltaic systems.
Voice Activity Detection (VAD) serves as a fundamental technology in speech recognition with extensive applications across both commercial and civil domains. Accurate endpoint detection becomes particularly challenging in low signal-to-noise ratio (SNR) environments, especially during silent segments or transitional periods before and after phonation.