Explore MATLAB source code curated for "特征向量" with clean implementations, documentation, and examples.
Perform singular value decomposition on the covariance matrix of arbitrary array output data to obtain eigenvalues and eigenvectors, then construct a spatial spectrum function utilizing the orthogonality between signal subspace and noise subspace with MATLAB implementation
MATLAB implementations of power iteration and inverse iteration methods for calculating eigenvalues and eigenvectors, along with the MINRES algorithm for matrix computations
Implementing color image segmentation through Fuzzy C-Means (FCM) clustering algorithm with various feature vector representations for enhanced image characterization
Face recognition system implemented using the open-source Yale face database, employing Local Binary Patterns (LBP) for facial feature extraction and K-Nearest Neighbors algorithm for classifying facial feature vectors, achieving approximately 90% recognition accuracy with excellent performance results.
MATLAB Implementation of Gradient Histogram for Image Feature Vector Extraction
This document implements graphic character recognition through feature matching approach, extracting 13 distinct feature vectors for pattern identification
This MATLAB-based code extracts 7 Hu moments as feature vectors to characterize image geometric properties. It can be applied to content-based image retrieval systems for robust feature representation.
Extraction of full autocorrelation coefficients for weak signals and their representation as sample feature vectors, including implementation approaches and algorithm explanations.
A comprehensive MATLAB application utilizing wavelet packet transform to extract feature vectors and frequency component power spectra from two signals, with detailed algorithm implementation and function descriptions
Developed based on Dalal's HOG feature algorithm, this code features simple implementation with clear comments. By modifying the image path parameter, it generates a 36×105 feature vector suitable for image processing applications.