KPCA-MATLAB

KPCA tool

An implementation of Kernel Principal Component Analysis for dimensionality reduction and fault detection in MATLAB.

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).

GitHub

238 stars
10 watching
80 forks
Language: MATLAB
last commit: almost 3 years ago
Linked from 1 awesome list

dimensionality-reductionfault-detectionfault-diagnosiskpca

Backlinks from these awesome lists:

Related projects:

Repository Description Stars
mljs/pca Tool for reducing dimensionality of data by identifying and preserving the most informative directions. 98
xiaoyang-rebecca/patternrecognition_matlab An investigation into feature reduction and classification methods for pattern recognition using various techniques such as PCA, LDA, and SVM. 71
iqiukp/zoomplot-matlab Interactive plotting and zooming tool for MATLAB 346
dlaptev/robustpca A Matlab implementation of Robust Principal Component Analysis (PCA) with an ADMM optimization method for matrix factorization. 196
kosyoshida/tskcca A Matlab implementation of two-stage kernel canonical correlation analysis for feature selection and multiple component capture in machine learning 6
trendscenter/gift An ICA/IVA software application that analyzes EEG and fMRI data using multiple algorithms for independent component analysis and blind source separation. 73
helloyaozhang/face-recognition-using-pca An implementation of Principal Components Analysis algorithm in MATLAB for facial recognition 56
andylamp/federated_pca An algorithm for performing dimensionality reduction on decentralized data with differential privacy guarantees 39
rulixiang/changedetectionpcakmeans This MATLAB implementation detects changes in various types of land cover in satellite images using PCA and k-Means clustering 77
stephenbeckr/fastrpca Matlab code implementing variants of robust PCA and SPCP algorithms 116
pachterlab/pcca A software project that performs statistical analysis on biological data using Principal Component Correlation Analysis (PCCA) and related methods. 18
mstorath/pottslab A toolbox for unsupervised multilabel image segmentation using the Potts model. 109
steven2358/kmbox A collection of MATLAB programs implementing kernel-based algorithms for nonlinear signal processing and machine learning. 52
hwang64/mlkp A method for compactly representing object proposals in object detection using high-order statistics 107
pkunlp-icler/pca-eval An open-source benchmark and evaluation tool for assessing multimodal large language models' performance in embodied decision-making tasks 99