Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs)
Spiking Neural Networks (SNNs) are recognised for processing spatiotemporal information with ultra-low power consumption. However, applying a non-efficient encoding-decoding algorithm can counter the efficiency advantages of the SNNs. In this sense, this paper presents one-step ahead forecasting cen...
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2024-07-01
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| author | Sergio Lucas Eva Portillo |
| author_facet | Sergio Lucas Eva Portillo |
| author_sort | Sergio Lucas |
| collection | DOAJ |
| description | Spiking Neural Networks (SNNs) are recognised for processing spatiotemporal information with ultra-low power consumption. However, applying a non-efficient encoding-decoding algorithm can counter the efficiency advantages of the SNNs. In this sense, this paper presents one-step ahead forecasting centered on the application of an optimised encoding-decoding algorithm based on Pulse Width Modulation (PWM) for SNNs. The validation is carried out with sine-wave, 3 UCI and 1 available real-world datasets. The results show the practical disappearance of the computational and energy costs associated with the encoding and decoding phases (less than 2% of the total costs) and very satisfactory forecasting results (MAE lower than 0.0357) for any dataset. |
| format | Article |
| id | doaj-art-8e729e88bf1843b8b6055170ce7215c9 |
| institution | OA Journals |
| issn | 2673-4591 |
| language | English |
| publishDate | 2024-07-01 |
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| spelling | doaj-art-8e729e88bf1843b8b6055170ce7215c92025-08-20T02:11:26ZengMDPI AGEngineering Proceedings2673-45912024-07-016814110.3390/engproc2024068041Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs)Sergio Lucas0Eva Portillo1Department of Automatic Control and Systems Engineering, Faculty of Engineering of Bilbao, University of the Basque Country (UPV/EHU), 48013 Bilbao, SpainDepartment of Automatic Control and Systems Engineering, Faculty of Engineering of Bilbao, University of the Basque Country (UPV/EHU), 48013 Bilbao, SpainSpiking Neural Networks (SNNs) are recognised for processing spatiotemporal information with ultra-low power consumption. However, applying a non-efficient encoding-decoding algorithm can counter the efficiency advantages of the SNNs. In this sense, this paper presents one-step ahead forecasting centered on the application of an optimised encoding-decoding algorithm based on Pulse Width Modulation (PWM) for SNNs. The validation is carried out with sine-wave, 3 UCI and 1 available real-world datasets. The results show the practical disappearance of the computational and energy costs associated with the encoding and decoding phases (less than 2% of the total costs) and very satisfactory forecasting results (MAE lower than 0.0357) for any dataset.https://www.mdpi.com/2673-4591/68/1/41Spiking Neural NetworksPulse Width Modulation (PWM) based encoding-decoding algorithmforecasting |
| spellingShingle | Sergio Lucas Eva Portillo Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs) Engineering Proceedings Spiking Neural Networks Pulse Width Modulation (PWM) based encoding-decoding algorithm forecasting |
| title | Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs) |
| title_full | Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs) |
| title_fullStr | Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs) |
| title_full_unstemmed | Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs) |
| title_short | Application of the Optimised Pulse Width Modulation (PWM) Based Encoding-Decoding Algorithm for Forecasting with Spiking Neural Networks (SNNs) |
| title_sort | application of the optimised pulse width modulation pwm based encoding decoding algorithm for forecasting with spiking neural networks snns |
| topic | Spiking Neural Networks Pulse Width Modulation (PWM) based encoding-decoding algorithm forecasting |
| url | https://www.mdpi.com/2673-4591/68/1/41 |
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