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Cognitive Applications in Resistive Memories
Cognitive Applications in Resistive Memories
60,11
66,79 €
  • We will send in 10–14 business days.
The upcoming trends in information technology follow irresistibly the predicted changes of the Internet of Things (IoT). That requires enhanced performance of mobile electronics, thus memory techniques face a growing number of challenges. Redox-based resistive switches (ReRAM) are highly attractive devices for implementation of ultimately-scaled energy-efficient memories. In this thesis, associative memories and sorting networks based on resistive switches are investigated. These cognitive func…
66.79
  • Publisher:
  • Year: 2020
  • Pages: 172
  • ISBN-10: 3751972862
  • ISBN-13: 9783751972864
  • Format: 14.8 x 21 x 0.9 cm, minkšti viršeliai
  • Language: English
  • SAVE -10% with code: EXTRA

Cognitive Applications in Resistive Memories (e-book) (used book) | bookbook.eu

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The upcoming trends in information technology follow irresistibly the predicted changes of the Internet of Things (IoT). That requires enhanced performance of mobile electronics, thus memory techniques face a growing number of challenges. Redox-based resistive switches (ReRAM) are highly attractive devices for implementation of ultimately-scaled energy-efficient memories. In this thesis, associative memories and sorting networks based on resistive switches are investigated. These cognitive functions highlight the potential of brain inspired computing in memory and are considered as a key-enabler for beyond von-Neumann computer architectures.

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  • Author: Lutz Stephan Nielen
  • Publisher:
  • Year: 2020
  • Pages: 172
  • ISBN-10: 3751972862
  • ISBN-13: 9783751972864
  • Format: 14.8 x 21 x 0.9 cm, minkšti viršeliai
  • Language: English English

The upcoming trends in information technology follow irresistibly the predicted changes of the Internet of Things (IoT). That requires enhanced performance of mobile electronics, thus memory techniques face a growing number of challenges. Redox-based resistive switches (ReRAM) are highly attractive devices for implementation of ultimately-scaled energy-efficient memories. In this thesis, associative memories and sorting networks based on resistive switches are investigated. These cognitive functions highlight the potential of brain inspired computing in memory and are considered as a key-enabler for beyond von-Neumann computer architectures.

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