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Nadia Nedjah
Researcher at Rio de Janeiro State University
Publications - 346
Citations - 2931
Nadia Nedjah is an academic researcher from Rio de Janeiro State University. The author has contributed to research in topics: Modular exponentiation & Hardware architecture. The author has an hindex of 24, co-authored 319 publications receiving 2489 citations. Previous affiliations of Nadia Nedjah include Monash University, Clayton campus & University of Manchester.
Papers
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Journal ArticleDOI
Modern development methods and tools for embedded reconfigurable systems: A survey
TL;DR: This paper reviews the recent methods and tools for the macro- and micro-architecture synthesis, and for the application mapping of reconfigurable systems, and puts much attention to the relevant and currently hot topic of ASIP instruction set processors (ASIP) synthesis.
Book
Swarm Intelligent Systems
TL;DR: A Matlab Implementation of Swarm Intelligence based Methodology for Identification of Optimized Fuzzy Models and Experiences using Particle Swarm Intelligence.
Journal ArticleDOI
Review of methodologies and tasks in swarm robotics towards standardization
TL;DR: The main goal of this review is to find out the reason behind the lack of exploitation of swarm robotic systems in real-world applications, and emphasize the urgent need for standardization of many aspects in SR, including hardware and software, as to allow a possible flourishing of SR applicability to real- world applications.
Journal ArticleDOI
Soft computing in big data intelligent transportation systems
TL;DR: Experimental results on the prototype system demonstrate NeverStop can efficiently facilitate researchers to reduce the average waiting time for vehicles, and a genetic algorithm illustrating how theaverage waiting time is derived is presented.
Book ChapterDOI
Evolutionary Computation: from Genetic Algorithms to Genetic Programming
TL;DR: This chapter presented the biological motivation and fundamental aspects of evolutionary algorithms and its constituents, namely genetic algorithm, evolution strategies, evolutionary programming and genetic programming, and most popular variants of genetic programming.