Name: Enhancing Endurance of non Volatile Memory in Embedded Systems: Based on Optimized Machine Learning and Compression Techniques (en Inglés)
Price: 84.77 USD
Availability: InStock
Author: Shritharanyaa J P; Saravana Kumar R
ISBN: 9786207804832

portada Enhancing Endurance of non Volatile Memory in Embedded Systems: Based on Optimized Machine Learning and Compression Techniques (en Inglés)

Enhancing Endurance of non Volatile Memory in Embedded Systems: Based on Optimized Machine Learning and Compression Techniques (en Inglés)

Formato

Libro Físico

Editorial

Lap Lambert Academic Publishing

Autor

Shritharanyaa J P; Saravana Kumar R

Idioma

Inglés

N° páginas

136

Encuadernación

Tapa Blanda

ISBN13

9786207804832

Enhancing Endurance of non Volatile Memory in Embedded Systems: Based on Optimized Machine Learning and Compression Techniques (en Inglés)

Shritharanyaa J P; Saravana Kumar R (Autor) · Lap Lambert Academic Publishing · Tapa Blanda

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Reseña del libro "Enhancing Endurance of non Volatile Memory in Embedded Systems: Based on Optimized Machine Learning and Compression Techniques (en Inglés)"

This book is focused on enhancing the endurance of Non-Volatile Random Access Memory (NVRAM) for embedded systems applications. It describes the methodology that combines optimized machine learning algorithms based on workload prediction and data compression techniques to prolong the lifespan of NVRAM. The framework utilizes an Instruction Per Cycle-based Dynamic Pattern Compression model to analyze and compress workloads, as well as a Workload Hybrid Energy Adaptive Learning model to categorize and further compress data for storage. The book provides a solution for improving NVRAM endurance, which is crucial for the performance of embedded devices, by addressing workload prediction and efficient compression.