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Semi-periodic Activation for Time Series Classification

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Author(s):
Barbosa de Medeiros Junior, Jose Gilberto ; de Mitri, Andre Guarnier ; Silva, Diego Furtado
Total Authors: 3
Document type: Journal article
Source: INTELLIGENT SYSTEMS, BRACIS 2024, PT IV; v. 15415, p. 15-pg., 2025-01-01.
Abstract

This paper investigates the lack of research on activation functions for neural network models in time series tasks. It highlights the need to identify essential properties of these activations to improve their effectiveness in specific domains. To this end, the study comprehensively analyzes properties, such as bounded, monotonic, nonlinearity, and periodicity, for activation in time series neural networks. We propose a new activation that maximizes the coverage of these properties, called LeakySineLU. We empirically evaluate the LeakySineLU against commonly used activations in the literature using 112 benchmark datasets for time series classification, obtaining the best average ranking in all comparative scenarios. (AU)

FAPESP's process: 23/11775-5 - Cross-convolution for multivariate time series tasks
Grantee:José Gilberto Barbosa de Medeiros Júnior
Support Opportunities: Scholarships abroad - Research Internship - Master's degree
FAPESP's process: 23/02680-0 - Transfer of Learning to Deal with Devices Heterogeneity
Grantee:José Gilberto Barbosa de Medeiros Júnior
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 22/03176-1 - Machine learning for time series obtained in mHealth applications
Grantee:Diego Furtado Silva
Support Opportunities: Research Grants - Initial Project
FAPESP's process: 23/11745-9 - Experimenting deep learning-based strategies to deal with multivariate time series tasks.
Grantee:Andre Guarnier De Mitri
Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
FAPESP's process: 23/05041-9 - Adapting Time Series Classification Algorithms to Regression
Grantee:Andre Guarnier De Mitri
Support Opportunities: Scholarships in Brazil - Scientific Initiation