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Learning in Energy-Efficient Neuromorphic Computing - Algorithm and Architecture Co-Design

to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers;

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Deep Learning on Edge Computing Devices

devices through algorithm-hardware co-design. Focuses on hardware architecture and embedded deep learning, including neural networks

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Neuromorphic Computing Principles and Organization

to design a spike-based neuromorphic system to perform network of spiking neurons communication, computing, and adaptive learning for;

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Heterogeneous Reconfigurable Processors for Real Time Baseband Processing

implementation cost, achieving balanced trade-offs among flexibility, performance, and hardware costs. The authors discuss efficient design methods for;

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Neuromorphic Cognitive Systems

This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system;

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Event-Based Neuromorphic Systems

sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to;

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Thinking Machines

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic;

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Handbook of Energy-Aware and Green Computing - Two Volume Set

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As;

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Handbook of Energy-Aware and Green Computing - Two Volume Set

Implementing energy-efficient CPUs and peripherals as well as reducing resource consumption have become emerging trends in computing. As;

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High Performance Computing for Big Data

applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning;

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High Performance Computing for Big Data

applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning;

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Advances in Big Data

-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs;

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Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing

-electroactive memories and neuromorphic computing systems, suggests possible solutions to the challenges of device design, and evaluates the prospects;

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Mobile Edge Artificial Intelligence

optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical;

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Advances in Mobile Cloud Computing Systems

devices and the cloud Design and architecture of a Proximity Cloud that delivers low-latency, bandwidth-efficient end-user services;

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Advances in Mobile Cloud Computing Systems

devices and the cloud Design and architecture of a Proximity Cloud that delivers low-latency, bandwidth-efficient end-user services;

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Parallel Programming with Co-arrays

Parallel Programming with Co-Arrays describes the basic techniques used to design parallel algorithms for high-performance, scientific;

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Neuromorphic Engineering

The book presents the field of neuromorphic engineering from the perspectives of the scientist, the algorithm designer, and the computer;

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Coarrays

Parallel Programming with Co-Arrays describes the basic techniques used to design parallel algorithms for high-performance, scientific;

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Computing and Combinatorics

various topics, including algorithm design, approximation algorithm, graph theory, complexity theory, problem solving, optimization, computational;

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Energy Efficient Hardware-Software Co-Synthesis Using Reconfigurable Hardware

performance metric. Helping overcome these challenges, Energy Efficient Hardware-Software Co-Synthesis Using Reconfigurable Hardware offers solutions;

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Energy Efficient Hardware-Software Co-Synthesis Using Reconfigurable Hardware

estimation technique and a domain-specific modeling technique to provide rapid and fairly accurate energy estimation for hardware-software co-designs;

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Reversible and DNA Computing

circuits, and reversible DNA circuits. Reversible and DNA Computing contains a practical approach to understanding energy-efficient DNA;

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Advances in Computers: Volume 126

in Environmental Monitoring: Data Acquisition and Dissemination Aspects, Energy efficient implementation of tensor operations using dataflow paradigm for;

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Neural Information Processing Part I

analysis; robotics and control; bio-inspiredenergy efficient information processing; whole brain architecture; neurodynamics; bioinformatics;

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Neural Information Processing Part II

analysis; robotics and control; bio-inspiredenergy efficient information processing; whole brain architecture; neurodynamics; bioinformatics;

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Neural Information Processing Part III

analysis; robotics and control; bio-inspiredenergy efficient information processing; whole brain architecture; neurodynamics; bioinformatics;

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