F. Puletti

Recognition of multiple partial discharge patterns by multi‐class support vector machine using fractal image processing technique

State-of-the-art in artificial neural network applications: A survey

Review on Machine Vision based Insulator Inspection Systems for Power Distribution System

Classification of Partial Discharge Measured under Different Levels of Noise Contamination

Partial discharge signal denoising with spatially adaptive wavelet thresholding and support vector machines

Application of Complex Wavelet Transform to Suppress White Noise in GIS UHF PD Signals

A Review on State-of-the-Art Power Line Inspection Techniques

Methods for wavelet-based autonomous discrimination of multiple partial discharge sources

Feature extraction of partial discharge signals using the wavelet packet transform and classification with a probabilistic neural network

Rough set theory applied to pattern recognition of Partial Discharge in noise affected cable data

Partial discharge classifications: Review of recent progress

Trends in partial discharge pattern classification: a survey

Cross-wavelet transform as a new paradigm for feature extraction from noisy partial discharge pulses

Pattern recognition techniques and their applications for automatic classification of artificial partial discharge sources

Partial discharge pulse pattern recognition using hidden Markov models

A method for discriminating original pulses in online partial discharge measurement

Partial discharge pattern recognition of power cable joints using extension method with fractal feature enhancement

Classification of simultaneous multiple partial discharge sources based on probabilistic interpretation using a two-step logistic regression algorithm

A new approach to partial discharge testing of HV cable systems

Digital detection and fuzzy classification of partial discharge signals

Advanced PD inference in on-field measurements. I. Noise rejection

A new methodology for the identification of PD in electrical apparatus: properties and applications

Inferring ceramic insulator pollution by an innovative approach resorting to PD detection