Name: Optimization of Spiking Neural Networks for Radar Applications (en Inglés)
SKU: 62719103
Price: 1769.82 MXN
Availability: InStock
Author: Muhammad Arsalan
ISBN: 9783658453176

portada Optimization of Spiking Neural Networks for Radar Applications (en Inglés)

Optimization of Spiking Neural Networks for Radar Applications (en Inglés)

Formato

Libro Físico

Editorial

Springer Vieweg

Autor

Muhammad Arsalan

Idioma

Inglés

N° páginas

260

Encuadernación

Tapa Blanda

ISBN13

9783658453176

N° edición

2024th

Optimization of Spiking Neural Networks for Radar Applications (en Inglés)

Muhammad Arsalan (Autor) · Springer Vieweg · Tapa Blanda

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Reseña del libro "Optimization of Spiking Neural Networks for Radar Applications (en Inglés)"

This book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. By providing real-time processing, reduced latency, increased efficiency, improved security, and scalability, edge devices are at the forefront of enabling IoT growth and success. As the adoption of AI on the edge continues to surge, the demand for real-time data processing is escalating, driving innovation in AI and fostering the development of cutting-edge applications and use cases. 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. The energy consumption of deepNets, largely attributed to Multiply-accumulate (MAC) operations between layers, is scrutinized. Researchers are actively working on reducing energy consumption through strategies such as tiny networks, pruning approaches, and weight quantization. Additionally, the book sheds light on the challenges posed by the physical size of AI accelerators for edge devices. The central focus of the book is an in-depth examination of SNNs' capabilities in radar data processing, featuring the development of optimized algorithms.