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Design Automation for Embedded Systems

An International Journal

Design Automation for Embedded Systems OnlineFirst articles


Deep learning controller design of embedded control system for maglev train via deep belief network algorithm

The maglev train has been successful in practice as a new type of ground transportation. Owing to the inherent nonlinearity and open-loop instability of the electromagnetic suspension (EMS) system, an analogue or a digital controller is used to …


Reducing neighbor discovery time in sensor networks with directional antennas using dynamic contention resolution

In this paper we present, simulate, and evaluate Dynamic Asynchronous Neighbor Discovery protocol for Directional Antennas (DANDi), a neighbor discovery protocol for Wireless Sensor Networks (WSN) with directional antennas that guarantees that …


Deep learning parallel computing and evaluation for embedded system clustering architecture processor

In the era of intelligence, the processing of a large amount of information and various intelligent applications need to rely on embedded devices. This trend has made machine learning algorithms play an increasingly important role.


Nested genetic algorithm for highly reliable and efficient embedded system design

Modern embedded systems must have high reliability and performance. They should be able to tolerate both hard as well as soft errors occurring in the resources constituting the system. Reliability must be part of the system design and the system …


Optimization of multitask parallel mobile edge computing strategy based on deep learning architecture

As a mainstream computing and storage strategy for mobile communications, Internet of Things and large data applications, mobile edge computing strategy mainly benefits from the deployment and allocation of small base stations. Mobile edge …

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Design Automation for Embedded Systems is a multidisciplinary journal addressing the systematic design of embedded systems. It offers a forum for scientists and engineers to report their latest work and results on algorithms, tools, architectures, case studies, and actual design examples. The journal focuses primarily on tools, methodologies and architectures for embedded systems, including HW/SW co-design, simulation and modeling approaches, synthesis techniques, architectures, and design exploration.

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