Spelling suggestions: "subject:"stochastic processes data processing"" "subject:"stochastic processes mata processing""
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Computational issues of Stochastic-Alpha-Beta-Rho (SABR) model. / CUHK electronic theses & dissertations collectionJanuary 2013 (has links)
Yang, Nian. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 95-100). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.
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A dynamic program for minimum cost ship routing under uncertaintyChen, H. (Henry) January 1978 (has links)
Thesis. 1978. Ph.D.--Massachusetts Institute of Technology. Dept. of Ocean Engineering. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING / Includes bibliographical references. / by H.T. Chen. / Ph.D.
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Stochastic optimization of energy for multi-user wireless networks over fading channelsUnknown Date (has links)
Wireless devices in wireless networks are powered typically by small batteries that are not replaceable nor recharged in a convenient way. To prolong the operating lifetime of networks, energy efficiency is indicated as a critical issue and energy-efficient resource allocation designs have been extensively developed. We investigated energy-efficient schemes that prolong network operating lifetime in wireless sensor networks and in wireless relay networks. In Chapter 2, the energy-efficient resource allocation that minimizes a general cost function of average user powers for small- or medium-scale wireless sensor networks, where the simple time-division multiple-access (TDMA) is adopted as the multiple access scheme. A class of Ç-fair cost-functions is derived to balance the tradeoff between efficiency and fairness in energy-efficient designs. Based on such cost functions, optimal channel-adaptive resource allocation schemes are developed for both single-hop and multi-hop TDMA sensor networks. In Chapter 3, optimal power control methods to balance the tradeoff between energy efficiency and fairness for wireless cooperative networks are developed. It is important to maximize power efficiency by minimizing power consumption for a given quality of service, such as the data rate; it is also equally important to evenly or fairly distribute power consumption to all nodes to maximize the network life. The optimal power control policy proposed is derived in a quasi-closed form by solving a convex optimization problem with a properly chosen cost-function. To further optimize a wireless relay network performance, an orthogonal frequency division multiplexing (OFDM) based multi-user wireless relay network is considered in Chapter 4. / In the OFDM approach, each subcarrier is dynamically assigned to a source- destination link, and several relays assist communication between pairs of source-destination over their assigned subcarriers. Using a class of Ç-fair cost-functions to balance the tradeoff between energy efficiency and fairness, jointly with optimal subcarrier and power allocation schemes at the relays. Relevant algorithms are derived in quasi-closed form. Lastly, the proposed energy-efficient schemes are summarized and future work is discussed in Chapter 5. / by Di Wang. / Thesis (Ph.D.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.
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Theoretical Aspects of Randomization in ComputationVishnoi, Nisheeth Kumar 12 July 2004 (has links)
Randomness has proved to be a powerful tool in all of computation. It is pervasive in areas such as networking, machine learning, computer graphics, optimization, computational number theory and is "necessary" for cryptography. Though randomized algorithms and protocols assume access to "truly" random bits, in practice, they rely on the output of "imperfect" sources of randomness such as pseudo-random number generators or physical sources. Hence, from a theoretical standpoint, it becomes important to view randomness as a resource and to study the following fundamental questions pertaining to it: Extraction: How do we generate "high quality" random bits from "imperfect" sources? Randomization: How do we use randomness to obtain efficient algorithms? Derandomization: How (and when) can we "remove" our dependence on random bits? In this thesis, we consider important problems in these three prominent and diverse areas pertaining to randomness. In randomness extraction, we present extractors for "oblivious bit fixing sources". In (a non-traditional use of) randomization, we have obtained results in machine learning (learning juntas) and proved hardness of lattice problems. While in derandomization, we present a deterministic algorithm for a fundamental problem called "identity testing". In this thesis we also initiate a complexity theoretic study of Hilbert's 17th problem. Here identity testing is used in an interesting manner. A common theme in this work has been the use of tools from areas such as number theory in a variety of ways, and often the techniques themselves are quite interesting.
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Multi-objective optimization of an interior permanent magnet motorRay, Subhasis. January 2008 (has links)
In recent years, due to growing environmental awareness regarding global warming, green cars, such as hybrid electric vehicles, have gained a lot of importance. With the decreasing cost of rare earth magnets, brushless permanent magnet motors, such as the Interior Permanent Magnet Motor, have found usage as part of the traction drive system in these types of vehicles. As a design issue, building a motor with a performance curve that suits both city and highway driving has been treated in this thesis as a multi-objective problem; matching specific points of the torque-speed curve to the desired performance output. Conventionally, this has been treated as separate problems or as a combination of several individual problems, but doing so gives little information about the trade-offs involved. As a means of identifying the compromising solutions, we have developed a stochastic optimizer for tackling electromagnetic device optimization and have also demonstrated a new innovative way of studying how different design parameters affect performance.
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Multi-objective optimization of an interior permanent magnet motorRay, Subhasis. January 2008 (has links)
No description available.
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