Hai Li – författare & böcker

Nonvolatile Memory Design

Magnetic, Resistive, and Phase Change

Häftad, Engelska, 2017

1 678 kr

Skickas inom 10-15 vardagar

The manufacture of flash memory, which is the dominant nonvolatile memory technology, is facing severe technical barriers. So much so, that some emerging technologies have been proposed as alternatives to flash memory in the nano-regime. Nonvolatile Memory Design: Magnetic, Resistive, and Phase Changing introduces three promising candidates: phase-change memory, magnetic random access memory, and resistive random access memory. The text illustrates the fundamental storage mechanism of these technologies and examines their differences from flash memory techniques. Based on the latest advances, the authors discuss key design methodologies as well as the various functions and capabilities of the three nonvolatile memory technologies.

Nonvolatile Memory Design

Magnetic, Resistive, and Phase Change

AvYiran Chen,Hai Li

E-bok

Engelska, 2017

2 017 kr

Läs direkt efter köp

The manufacture of flash memory, which is the dominant nonvolatile memory technology, is facing severe technical barriers. So much so, that some emerging technologies have been proposed as alternatives to flash memory in the nano-regime. Nonvolatile Memory Design: Magnetic, Resistive, and Phase Changing introduces three promising candidates: phase-change memory, magnetic random access memory, and resistive random access memory. The text illustrates the fundamental storage mechanism of these technologies and examines their differences from flash memory techniques. Based on the latest advances, the authors discuss key design methodologies as well as the various functions and capabilities of the three nonvolatile memory technologies.

Nonvolatile Memory Design

Magnetic, Resistive, and Phase Change

AvHai Li,Yiran Chen

Inbunden, Engelska, 2011

4 049 kr

Skickas inom 10-15 vardagar

The manufacture of flash memory, which is the dominant nonvolatile memory technology, is facing severe technical barriers. So much so, that some emerging technologies have been proposed as alternatives to flash memory in the nano-regime. Nonvolatile Memory Design: Magnetic, Resistive, and Phase Changing introduces three promising candidates: phase-change memory, magnetic random access memory, and resistive random access memory. The text illustrates the fundamental storage mechanism of these technologies and examines their differences from flash memory techniques. Based on the latest advances, the authors discuss key design methodologies as well as the various functions and capabilities of the three nonvolatile memory technologies.

Nonvolatile Memory Design

Magnetic, Resistive, and Phase Change

AvYiran Chen,Hai Li

E-bok

PDF, Engelska, 2017

2 017 kr

Läs direkt efter köp

The manufacture of flash memory, which is the dominant nonvolatile memory technology, is facing severe technical barriers. So much so, that some emerging technologies have been proposed as alternatives to flash memory in the nano-regime. Nonvolatile Memory Design: Magnetic, Resistive, and Phase Changing introduces three promising candidates: phase-change memory, magnetic random access memory, and resistive random access memory. The text illustrates the fundamental storage mechanism of these technologies and examines their differences from flash memory techniques. Based on the latest advances, the authors discuss key design methodologies as well as the various functions and capabilities of the three nonvolatile memory technologies.

Computer Engineering Machine Learning and Neural Networks

A Computer Engineering Perspective

AvYiran Chen,Hai Lim. fl.

Inbunden, Engelska, 2026

756 kr

Skickas inom 10-15 vardagar

This is the first textbook focusing on practicality of machine learning (ML) and deep neural networks (DNN), by introducing methods that enable engineering applications of ML and DNN models. The authors describe many methodologies that are widely used in designing, training, and deploying of these models and discuss their applicability under various contexts. Coverage begins with the basic knowledge of machine learning and deep neural networks and their applications in solving practical engineering problems. It then proceeds through a series of computer engineering methods commonly used in developing machine learning and deep neural network models. The book also explains how to improve the training and inference performance in terms of model accuracy, size, runtime, etc. by considering various requirements and availability of data in the applications. Techniques that are widely adopted in both industry and academia are discussed. Tutorials and projects designed to practice the introduced techniques are provided using popular development frameworks of machine learning. Emphasizes practice over theoretical foundations, making content accessible to engineering students and engineers;Includes in-depth discussion of popular DNN models and their applications;Discusses engineering methods and tricks widely adopted in practice for using ML and DNN to solve engineering problems.

Computer Engineering Machine Learning and Neural Networks

A Computer Engineering Perspective

AvHuanrui Yang,Hai Lim. fl.

E-bok

Engelska, 2026

950 kr

Läs direkt efter köp

This is the first textbook focusing on practicality of machine learning (ML) and deep neural networks (DNN), by introducing methods that enable engineering applications of ML and DNN models. The authors describe many methodologies that are widely used in designing, training, and deploying of these models and discuss their applicability under various contexts. Coverage begins with the basic knowledge of machine learning and deep neural networks and their applications in solving practical engineering problems. It then proceeds through a series of computer engineering methods commonly used in developing machine learning and deep neural network models. The book also explains how to improve the training and inference performance in terms of model accuracy, size, runtime, etc. by considering various requirements and availability of data in the applications. Techniques that are widely adopted in both industry and academia are discussed. Tutorials and projects designed to practice the introduced techniques are provided using popular development frameworks of machine learning. Emphasizes practice over theoretical foundations, making content accessible to engineering students and engineers;Includes in-depth discussion of popular DNN models and their applications;Discusses engineering methods and tricks widely adopted in practice for using ML and DNN to solve engineering problems.

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Nonvolatile Memory Design

Nonvolatile Memory Design

Nonvolatile Memory Design

Nonvolatile Memory Design

Computer Engineering Machine Learning and Neural Networks

Computer Engineering Machine Learning and Neural Networks

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