Sequential experimentation is often employed in process optimization wherein a series of small experiments are run successively in order to determine which experimental factor levels are likely to yield a desirable response. Although there currently exists a framework for identifying optimal follow-up designs after an initial experiment has been run, the accepted methods frequently point to multiple designs leaving the practitioner to choose one arbitrarily. In this thesis, we apply preposterior analysis and Bayesian model-averaging to develop a methodology for further discriminating between optimal follow-up designs while controlling for both parameter and model uncertainty.

"This thesis describes the development of an optimized software-defined-radio implementation of a distributed beamforming system and presents experimental results for two-source and three- source wired-channel and acoustic-channel distributed beamforming using the time-slotted round-trip carrier synchronization protocol. The frequency and phase synthesizer used in this system is based on an optimized ``hybrid' phase locked loop (PLL) with averaging window which is shown to have high frequency estimation accuracy and consistency. For the wired-channel experiments, each source node was implemented by a TMS320C6713DSK while for the acoustic experiments, each source node in the system was built using commercial off-the-shelf parts including TMS320C6713DSK, microphone, speaker, audio amplifier, and battery. The source node functionality including phase locked loops and the logic associated with the time-slotted round-trip carrier synchronization protocol was realized through real-time software independently running on each source node's C6713 digital signal processor. Experimental results for two-source and three-source realizations of the wired-channel and acoustic-channel distributed beamforming system are presented. The results show that near-ideal beamforming performance can be consistently achieved at acoustic wavelengths equivalent to common radio frequency wavelengths."

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND AERONAUTICS. / Includes bibliographical references. / by Sean Kevin Collins. / Ph.D.

Nous avons étudié un système différentiel régi par deux dynamiques : l'une de type variété centrale et l'autre de type oscillation rapide périodique. Nous avons cherché à obtenir des informations sur le comportement qualitatif du système et à l'approcher. Nous avons démontré l'existence d'une dynamique asymptotique rapidement oscillante et nous l'avons utilisée pour approcher le système. Ensuite, nous avons appliqué ces résultats à l'étude d'un système écologique d'interaction proie-prédateur. De plus, nous avons utilisé la théorie des B-séries pour obtenir des développements formels à tout ordre des quantités liées à la dynamique asymptotique. Enfin, nous avons approché le système pour tout temps par la composée d'un changement de variable et de la solution d'un système différentiel partiellement découplé. / We have studied a differential system ruled by two dynamics : a center manifold dynamics and a periodic highly oscillating dynamics. We wanted to find informations about the qualitative behaviour of the system, and to approximate it. We have proved the existence of a highly oscillating asymptotic dynamics, and we have used it approximate the system. Then, we have applied this results to an ecological system of prey-predator interaction. Moreover, we have used the B-series theory to obtain formal expansions of the quantities related to the center manifold. Lastly, we have approximated the system for all time by the composition of a change of variable and of the solution of a partially decoupled differential system.

<p>This master’s thesis work was performed at Volvo Powertrain in Köping, Sweden, which manufactures gearboxes and integrated transmission systems for heavy vehicles. The thesis is a continuation of a previous master’s thesis performed at the Köping factory in 2009. After manufacturing and assembly, each gearbox is manually validated to ensure the gearbox quality and functionality. When validating the gearbox gears, the operator shifts the gearbox in a predefined manner and listens for irregularities. If an error sound is heard the operator must then locate the source of error. With numerous of cog wheels rotating at the same time this task requires extensive knowledge and experience of the operator. The main objective is to develop an automatic diagnostic system for detection of cog errors and assist the operator in the process of locating the faulty component.</p><p>The work consists of two parts. In the first part the automatic diagnostic system is developed and a database of gearbox recordings is stored. The amounts of logged non-faulty gearboxes are significantly much larger (50) than the logged faulty gearboxes (1). Therefore, when determining thresholds needed for the diagnosis, the data obtained from the non-faulty gearboxes are used. Two statistical methods are presented to extract the thresholds. The first method uses an extremevalue distribution and the other method a Gaussian distribution. When validated, both methods did successfully detect on cog faults. In the second part an investigation is made of how shaft imbalance can be detected and implemented in the developed system.</p><p>Volvo Powertrain continually follows-up all faults found at the validation station to ensure the quality of their work and eliminate the sources of error. During system testing one logged gearbox was found faulty. The automatic diagnostic system did successfully detect and locate the faulty component which later also was confirmed when the gearbox was dismounted. With only one detected error it is difficult to conclude the system performance and further testing is required. However, during the testing no false detections were made.</p>

The expected equity premium is an important parameter in many financial models, especially within portfolio optimization. A good forecast of the future equity premium is therefore of great interest. In this thesis we seek to forecast the equity premium, use it in portfolio optimization and then give evidence on how sensitive the results are to estimation errors and how the impact of these can be minimized. Linear prediction models are commonly used by practitioners to forecast the expected equity premium, this with mixed results. To only choose the model that performs the best in-sample for forecasting, does not take model uncertainty into account. Our approach is to still use linear prediction models, but also taking model uncertainty into consideration by applying Bayesian model averaging. The predictions are used in the optimization of a portfolio with risky assets to investigate how sensitive portfolio optimization is to estimation errors in the mean vector and covariance matrix. This is performed by using a Monte Carlo based heuristic called portfolio resampling. The results show that the predictive ability of linear models is not substantially improved by taking model uncertainty into consideration. This could mean that the main problem with linear models is not model uncertainty, but rather too low predictive ability. However, we find that our approach gives better forecasts than just using the historical average as an estimate. Furthermore, we find some predictive ability in the the GDP, the short term spread and the volatility for the five years to come. Portfolio resampling proves to be useful when the input parameters in a portfolio optimization problem is suffering from vast uncertainty.

We consider an SDE driven by a Lévy noise on a foliated manifold, whose trajectories stay on compact leaves. We determine the effective behavior of the system subject to a small smooth transversal perturbation of positive order epsilon. More precisely, we show that the average of the transversal component of the SDE converges to the solution of a deterministic ODE, according to the average of the perturbing vector field with respect to the invariant measures on the leaves (of the unpertubed system) as epsilon goes to 0. In particular we give upper bounds for the rates of convergence. The main results which are proved for pure jump Lévy processes complement the result by Gargate and Ruffino for Stratonovich SDEs to Lévy driven SDEs of Marcus type.

Artificial neural networks are widely used for parallel processing of data analysis and visual information. The most prominent example of artificial neural networks is a cellular neural network (CNN), composed from two-dimensional arrays of simple first-order dynamical systems (“cells”) that are interconnected by wires. The information, to be processed by a CNN, represents the initial state of the network, and the parallel information processing is performed by converging to one of the stable spatial equilibrium states of the multi-stable CNN. This thesis studies a specific type of CNNs designed to perform the winner-take-all function of finding the largest among the n numbers, using the network dynamics. In a wider context, this amounts to automatically detecting a target spot in the given visual picture. The research, reported in this thesis, demonstrates that the addition of fast on-off switching (blinking) connections significantly improves the functionality of winner-take-all CNNs. Numerical calculations are performed to reveal the dependence of the probability, that the CNN correctly classifies the largest number, on the switching frequency.

This master’s thesis work was performed at Volvo Powertrain in Köping, Sweden, which manufactures gearboxes and integrated transmission systems for heavy vehicles. The thesis is a continuation of a previous master’s thesis performed at the Köping factory in 2009. After manufacturing and assembly, each gearbox is manually validated to ensure the gearbox quality and functionality. When validating the gearbox gears, the operator shifts the gearbox in a predefined manner and listens for irregularities. If an error sound is heard the operator must then locate the source of error. With numerous of cog wheels rotating at the same time this task requires extensive knowledge and experience of the operator. The main objective is to develop an automatic diagnostic system for detection of cog errors and assist the operator in the process of locating the faulty component. The work consists of two parts. In the first part the automatic diagnostic system is developed and a database of gearbox recordings is stored. The amounts of logged non-faulty gearboxes are significantly much larger (50) than the logged faulty gearboxes (1). Therefore, when determining thresholds needed for the diagnosis, the data obtained from the non-faulty gearboxes are used. Two statistical methods are presented to extract the thresholds. The first method uses an extremevalue distribution and the other method a Gaussian distribution. When validated, both methods did successfully detect on cog faults. In the second part an investigation is made of how shaft imbalance can be detected and implemented in the developed system. Volvo Powertrain continually follows-up all faults found at the validation station to ensure the quality of their work and eliminate the sources of error. During system testing one logged gearbox was found faulty. The automatic diagnostic system did successfully detect and locate the faulty component which later also was confirmed when the gearbox was dismounted. With only one detected error it is difficult to conclude the system performance and further testing is required. However, during the testing no false detections were made.

Modern communication systems require higher data rates which have increased thedemand for high speed transceivers. For a system to work efficiently, all blocks ofthat system should be fast. It can be seen that analog interfaces are the main bottleneckin whole system in terms of speed and power. This fact has led researchersto develop high speed analog to digital converters (ADCs) with low power consumption.Among all the ADCs, flash ADC is the best choice for faster data conversion becauseof its parallel structure. This thesis work describes the design of such a highspeed and low power flash ADC for analog front end (AFE) of a transceiver. Ahigh speed highly linear track and hold (TnH) circuit is needed in front of ADCwhich gives a stable signal at the input of ADC for accurate conversion. Twodifferent track and hold architectures are implemented, one is bootstrap TnH andother is switched source follower TnH. Simulations show that high speed with highlinearity can be achieved from bootstrap TnH circuit which is selected for the ADCdesign.Averaging technique is employed in the preamplifier array of ADC to reduce thestatic offsets of preamplifiers. The averaging technique can be made more efficientby using the smaller number of amplifiers. This can be done by using the interpolationtechnique which reduces the number of amplifiers at the input of ADC. Thereduced number of amplifiers is also advantageous for getting higher bandwidthsince the input capacitance at the first stage of preamplifier array is reduced.The flash ADC is designed and implemented in 150 nm CMOS technology for thesampling rate of 1.6 GSamples/sec. The bootstrap TnH consumes power of 27.95mW from a 1.8 V supply and achieves the signal to noise and distortion ratio(SNDR) of 37.38 dB for an input signal frequency of 195.3 MHz. The ADC withideal TnH and comparator consumes power of 78.2 mW and achieves 4.8 effectivenumber of bits (ENOB).