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Yayın Decision making and Yarsoy decision support tool(Işık Üniversitesi, 2002-09) Atasoy, Ercan; Yarman, Bekir Sıddık Binboğa; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Elektronik Mühendisliği Yüksek Lisans ProgramıEvery human makes decisions in the course of his interactions with the world and other human acting in the world. To make good decisions, we need knowledge about events that occur in the world and preferences we have. Decision Support Systems try to gather information, keep it in database, classify it, give a fast and easy access to his information and by analyzing it help user to make consistent decisions. In this thesis a model driven decision support tool with the name 2YARSOY3 is developed using designated decision making models. It is developed using C++ Builder 5.0 programming tools. YARSOY is very flexible, user friendly and unique with its models. It can be used for a daily life decisions such as car or job choices, employee selection, vote selection and swot analyses. People usually make decisions by taking three or five factors into account. In order to attain the existent objectives, the events, factors and alternatives that will realize the objective must be analysed cearfully. This program gives us opportunity to evaluate, compare and analyse the events and alternatives in detail based on mathematical methods.Yayın Low complexity inter-mode selection for H.264(IEEE, 2006) Ba, Seydou Nourou; Altunbaşak, Yücel; Ateş, Hasan FehmiThe coding efficiency of the H.264/AVC standard enables the transmission of high quality video over bandwidth limited networks. Due to the use of multiple Macroblock (MB) partitions, the Motion estimation module has extremely high complexity that makes it unpractical for most real-time applications on resource-limited platforms such as hand held devices. In this paper we propose a novel algorithm that significantly reduces the encoding complexity while maintaining high rate distortion performance. The proposed method reduces the Motion estimation (ME) computational complexity by accurately predicting the optimal MB partitions and restricting the number of candidate modes based on a-priori probabilities computed from spatio-temporal information. The experimental results show that the speed up of UmHexagonS [1] (one of the most efficient ME algorithms) can be doubled while maintaining the coding efficiency of Full Search.Yayın Rate-distortion and complexity optimized motion estimation for H.264 video coding(IEEE-INST Electrical Electronics Engineers Inc, 2008-02) Ateş, Hasan Fehmi; Altunbaşak, Yücel11.264 video coding standard supports several inter-prediction coding modes that use macroblock (MB) partitions with variable block sizes. Rate-distortion (R-D) optimal selection of both the motion vectors (MVs) and the coding mode of each MB is essential for an H.264 encoder to achieve superior coding efficiency. Unfortunately, searching for optimal MVs of each possible subblock incurs a heavy computational cost. In this paper, in order to reduce the computational burden of integer-pel motion estimation (ME) without sacrificing from the coding performance, we propose a R-D and complexity joint optimization framework. Within this framework, we develop a simple method that determines for each MB which partitions are likely to be optimal. MV search is carried out for only the selected partitions, thus reducing the complexity of the ME step. The mode selection criteria is based on a measure of spatiotemporal activity within the MB. The procedure minimizes the coding loss at a given level of computational complexity either for the full video sequence or for each single frame. For the latter case, the algorithm provides a tight upper bound on the worst case complexity/execution time of the ME module. Simulation results show that the algorithm speeds up integer-pel ME by a factor of up to 40 with less than 0.2 dB loss in coding efficiency.
