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In embedded computer systems there are often tasks, implemented as stand-alone devices, that are both application-specific and compute intensive. A recurring problem in this area is to design these application-specific embedded systems as close to the power and efficiency envelope as possible. Work has been done on optimizing singlecore systems and memory organisation, but current methods for achieving system design goals are proving limited as the system capabilities and system size increase in the multi- and many-core era. To address this problem, this thesis investigates machine learning approaches to managing the design space presented in the interconnect design of embedded multi-core systems. The design space presented is large due to the system scale and level of interconnectivity, and also feature inter-dependant parameters, further complicating analysis. The results presented in this thesis demonstrate that machine learning approaches, particularly wkNN and random forest, work well in handling the complexity of the design space. The benefits of this approach are in automation, saving time and effort in the system design phase as well as energy and execution time in the finished system.

No description available.

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This study has been conducted in order to determine the existence of predictability for the Stockholm stock exchange. With this purpose the random walk theory has been raised against the theory of mean reversion in order to determine which theory is the most substantial. Data has been collected from Nasdaq OMX Nordic and furtherly been processed using the statistical software EViews. Swedish listed companies’ daily share values between 2000-2014 have been analyzed using two tests; an Augmented Dickey Fuller test and a Variance Ratio test. The results show generally that the null hypothesis - and thus the random walk - is rejected in the short term. This means that both on an aggregated level and on an individual level, the Stockholm stock exchange is predictable in the short term - in the form of mean reversion - and that it is most evident in small cap firms.

This dissertation considers the random access process in the Medium Access Control (MAC) of communications system. New MAC models are developed to improve the performance of random access based systems. The first contribution is the introduction of a general multichannel random access model with a variable radix. This model is general and can be applied to many existing MAC protocols that utilize random access. It is shown that using the standard Binary Exponential Backoff (BEB) to resolve collisions is not always the best choice. By adjusting the radix, contention efficiency can be improved significantly. The analytical results obtained are confirmed by simulation. The second contribution is the investigation of the variable radix backoff strategy with the contention-based bandwidth request (BW-REQ) mechanism in IEEE 802.16 systems. An analytical model of the BW-REQ procedure is presented which includes a variable radix in the backoff process. Analytical results are presented which show that the variable radix can easily be adjusted to the number of users and the available resources to enhance the efficiency of the Random Access Channel in the uplink subframe. Simulations results are presented to confirm the theory. The third contribution is the development of a reliable Quality of Service (QoS) mechanism for random access systems. The available resources are quantitatively categorized to provide differential services to two classes of users. The model is extended to employ a variable radix strategy. Results show that this strategy can be used in combination with differential services to provide an efficient QoS technique for random access. The fourth contribution is an optimized packet-based finite state Markov chain (FSMC) model for the physical channel. This model employs an equal average fade range duration (AFRD) strategy to partition the signal-to-noise ratio (SNR). The Nakagami-m fading channel model is used as it can span a wide range of fading conditions. The accuracy of the analytical results is confirmed by simulation. A cross-layer Markov model encompassing the FSMC model and a general multichannel random access model is introduced. Finally, a simulation toolbox using object oriented programming is presented. It was used to accurately simulate the models developed in this dissertation. This toolbox is general and can be used for a wide range of MAC models. / Graduate

Proefschrift Universiteit van Amsterdam. / Met lit. opg. - Met samenvatting in het Nederlands.

Thesis (Ph. D.)--University of Hong Kong, 2008. / Also available in print.

Thesis (M.S.)--Ohio University, June, 1997. / Title from PDF t.p.