Search Results for author: Antonio Cicone

Found 9 papers, 7 papers with code

RRCNN$^{+}$: An Enhanced Residual Recursive Convolutional Neural Network for Non-stationary Signal Decomposition

1 code implementation • 9 Sep 2023 • Feng Zhou, Antonio Cicone, Haomin Zhou

Time-frequency analysis is an important and challenging task in many applications.

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RRCNN: A novel signal decomposition approach based on recurrent residue convolutional neural network

1 code implementation • 4 Jul 2023 • Feng Zhou, Antonio Cicone, Haomin Zhou

Inspired by the successful applications of deep learning in fields like image processing and natural language processing, and given the lack in the literature of works in which deep learning techniques are used directly to decompose non-stationary signals into simple oscillatory components, we use the convolutional neural network, residual structure and nonlinear activation function to compute in an innovative way the local average of the signal, and study a new non-stationary signal decomposition method under the framework of deep learning.

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Time-frequency representation of nonstationary signals: the IMFogram

no code implementations • 28 Nov 2020 • Philippe Barbe, Antonio Cicone, Wing Suet Li, Haomin Zhou

Iterative filtering methods were introduced around 2010 to improve definitions and measurements of structural features in signal processing.

Numerical Analysis Numerical Analysis

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Multivariate Fast Iterative Filtering for the decomposition of nonstationary signals

2 code implementations • 13 Feb 2019 • Antonio Cicone

In this work, we present a new technique for the decomposition of multivariate data, which we call Multivariate Fast Iterative Filtering (MvFIF) algorithm.

Numerical Analysis Numerical Analysis