Search for dissertations about: "Consensus Algorithms"
Showing result 6 - 10 of 36 swedish dissertations containing the words Consensus Algorithms.
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6. Consensus Algorithms in Dynamical Network Systems
Abstract : Dynamical network systems are complex interconnected systems describing many real world problems. The current trend is to connect more and more systems together, and at the same time requiring continuous availability. To this end, it is crucial to understand the dynamic behaviors of networked systems. READ MORE
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7. Cooperative Compressive Sampling
Abstract : Compressed Sampling (CS) is a promising technique capable of acquiring and processing data of large sizes efficiently. The CS technique exploits the inherent sparsity present in most real-world signals to achieve this feat. Most real-world signals, for example, sound, image, physical phenomenon etc., are compressible or sparse in nature. READ MORE
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8. Exact and approximation algorithms for graph problems with some biological applications
Abstract : In this thesis we study several combinatorial problems in algorithmic graph theory and computational biology, and different algorithmical approaches for solving them. In particular, we focus on graph algorithms, seeking for the most part polynomial or sub-exponential exact solutions, but in some cases also approximate solutions. READ MORE
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9. Coordination and Self-Adaptive Communication Primitives for Low-Power Wireless Networks
Abstract : The Internet of Things (IoT) is a recent trend where objects are augmented with computing and communication capabilities, often via low-power wireless radios. The Internet of Things is an enabler for a connected and more sustainable modern society: smart grids are deployed to improve energy production and consumption, wireless monitoring systems allow smart factories to detect faults early and reduce waste, while connected vehicles coordinate on the road to ensure our safety and save fuel. READ MORE
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10. Novel Hessian approximations in optimization algorithms
Abstract : There are several benefits of taking the Hessian of the objective function into account when designing optimization algorithms. Compared to using strictly gradient-based algorithms, Hessian-based algorithms usually require fewer iterations to converge. READ MORE