Optimization of Spiking Neural Networks for Radar Applications

Häftad, Engelska, 2024

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Beskrivning

This book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. Delving into the intricacies of traditional deep neural network (deepNet) approaches, the book addresses concerns about their energy efficiency during inference, particularly for edge devices.

Produktinformation

Utgivningsdatum:2024-09-02
Mått:148 x 210 x 15 mm
Vikt:346 g
Format:Häftad
Språk:Engelska
Antal sidor:209
Förlag:Springer Fachmedien Wiesbaden
ISBN:9783658453176

Utforska kategorier

Optimering inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Tillämpad matematik inom Naturvetenskap och teknik

Mer om författaren

Muhammad Arsalan received the M.Sc. degree in Computational Engineering from the University of Rostock, and the M.Sc. degree in Biomedical Computing from the Technical University of Munich. He is currently working as a Senior Data Scientist.

Innehållsförteckning

Introduction.- Background.- Signal Processing Chain with Spiking Neural Networks for Radar-based Gesture Sensing.- Radar-based Air-writing for Embedded Devices.- Time Series Forecasting of Healthcare Data.- Conclusion and Future Directions.