鲁棒性 Resources

Showing items tagged with "鲁棒性"

This source code implements an isolated word speech recognition algorithm for non-specific speakers, with optimizations tailored for embedded systems with limited processing power and storage capacity. The implementation focuses on feature extraction techniques (like MFCC computation), acoustic modeling approaches, and efficient decoder structures to enhance system robustness while minimizing computational overhead and memory usage.

MATLAB 288 views Tagged
Download

A single-neuron adaptive intelligent PID controller constructed from a single neuron possessing self-learning and adaptive capabilities offers not only a simple structure but also strong adaptability to environmental changes and robust performance.

MATLAB 218 views Tagged
Download

The SURF (Speeded-Up Robust Features) algorithm, as a recently developed feature extraction method, surpasses or approaches previously proposed similar methods in three key aspects: repeatability, distinctiveness, and robustness, while demonstrating significant advantages in computational efficiency. This implementation utilizes the SURF algorithm for image detection, coordinate transformation, and image stitching. The core implementation involves using the Hessian matrix for image detection to identify feature points, followed by refinement through Fast Nearest Neighbor (NN) matching, Random Sample Consensus (RANSAC) algorithm, and Levenberg-Marquardt (LM) parameter optimization for precise feature matching. Finally, coordinate transformation is performed to unify the coordinate systems and achieve seamless image stitching.

MATLAB 224 views Tagged
Download

This code implements covariance tracking for visual object tracking research, which integrates multiple spatiotemporal features into a unified model. The approach demonstrates strong robustness in visual tracking applications and maintains computational efficiency since its dimensionality equals the number of features used rather than their individual dimensions, resulting in lower complexity and better real-time performance.

MATLAB 233 views Tagged
Download

FLICM overcomes limitations of standard FCM while enhancing clustering performance. Its key feature involves a fuzzy local similarity measure incorporating spatial information and gray values, ensuring noise insensitivity and image detail preservation. MATLAB implementation demonstrates FLICM's superior robustness for noisy image segmentation compared to FCM, using neighborhood pixel analysis and adaptive membership functions.

MATLAB 213 views Tagged
Download

Comprehensive DCT-domain digital watermarking source code (my graduation project outcome) featuring watermark embedding, watermark detection, robustness testing through attack experiments, and critical parameter calculations. This implementation provides practical MATLAB-based solutions for digital watermarking researchers and developers.

MATLAB 201 views Tagged
Download

A robust MATLAB implementation for face recognition using sparse coding, derived from Yang's seminal paper, ideal for beginners to systematically learn sparse coding concepts. The algorithm achieves strong performance on both occluded and non-occluded face recognition tasks, featuring sparse representation classification with error tolerance mechanisms.

MATLAB 187 views Tagged
Download

FLICM represents a recent advancement in fuzzy clustering, building upon traditional FCM methods with superior robustness and performance. This algorithm integrates local spatial information with fuzzy clustering principles, featuring improved noise immunity and clustering accuracy through a novel fuzzy local similarity measure implemented in its objective function.

MATLAB 190 views Tagged
Download