Téléchargez le livre : Wireless Communication Using Deep Learning Techniques for Neuromorphic VLSI Computing

Wireless Communication Using Deep Learning Techniques for Neuromorphic VLSI Computing

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Paru le : 2025-01-15

This book describes Deep Learning-based architecture design for intelligent wireless communication systems and specifically for Deep Learning-based receiver design. Deep Learning-based architecture design utilizes Deep Learning (DL) techniques to reformulate the traditional block-based wireless comm...
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Description du livre


This book describes Deep Learning-based architecture design for intelligent wireless communication systems and specifically for Deep Learning-based receiver design. Deep Learning-based architecture design utilizes Deep Learning (DL) techniques to reformulate the traditional block-based wireless communication architecture. Deep Learning-based algorithm design utilizes Deep Learning methods to speed up the processing at a guaranteed high accuracy performance. Automatic signal modulation classification in AI-based wireless communication can be done using deep learning techniques to improve dynamic spectrum allocation. Automatic signal modulation recognition in wireless communication is described using Deep Learning techniques to improve resource shortage and spectrum utilization efficiency. Moreover, using deep learning neural network circuit methods and doing parallel computations on hardware can reduce costs. Spiking neural network (SNN) provides a promising solution for low-power hardware for neuromorphic computing. Spiking Neural Networks circuit functions with a pre-trained network’s weights consume less power. Spiking neural network is more promising than other neural networks that can pave a new way for low-power computing applications. Analog VLSI is utilized to design spiking neural networks circuits such as silicon synapse and CMOS neuron.

À propos

Auteur
Ziad El-Khatib , Sherif Moussa
Éditeur
Springer
Collection
Synthesis Lectures on Engineering, Science, and Technology
Parution
2025-01-15
Pages
99 pages
EAN papier
9783031737992

Auteur(s) du livre


Defaut-Illustration Ziad El-Khatib
Defaut-Illustration Sherif Moussa

Caractéristiques détaillées - droits

EAN PDF
9783031738005
Prix
52,99 €
Nombre pages copiables
0
Nombre pages imprimables
9
Taille du fichier
7803 Ko
Ce livre est accessible aux handicaps informations d'accessibilité
EAN EPUB
9783031738005
Prix
52,99 €
Nombre pages copiables
0
Nombre pages imprimables
9
Taille du fichier
27750 Ko
Ce livre est accessible aux handicaps informations d'accessibilité

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