A dynamic importance sampling method for quick simulation of rare events

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1993.Thesis (Master's) -- Bilkent University, 1993.Includes bibliographical references leaves 38-39.Simulation of low-probability events may take extremely long times since they occur very rarely. There are various variance reduction methods used to speed up simulations in such cases. In this thesis, a new variance reduction technique is proposed, which is based on expressing the desired probability as the product of a number of greater probabilities and estimating each term in the product in a recursive manner. It turns out that the resulting estimator, when feasible, uses an importance sampling distribution at each step to constrain the samples into a sequence of larger sets which shrink towards the rare set gradually. Moreover, the important samples used in each step are obtained automatically from the outcomes of the experiments in the previous steps. The method is applied to the estimation of overflow probability in a network of queues and remarkable speed-ups with respect to standard simulation are obtained.Erdoğan, AlperM.S

Applications of POD studies and robust design to electromagnetic NDE

Numerical techniques, such as finite element methods (FEM), have been widely used in predicting defect signatures in nondestructive evaluation (NDE). The test conditions in the numerical models are deterministic in nature. However, signals generated by identical flaws are usually different under practical testing conditions. This affects the reliability of NDE methods. A considerable amount of attention has been focused towards quantifying the reliability of a variety of NDE methods, which has led to development of models for evaluating probability of detection (POD). Sources of variabilities that influence POD in NDE systems vary due to different testing modalities. POD models not only help in improving accuracy in flaw detection but also help in optimizing operational parameters. The Taguchi method, also called robust design in literature, is a well-established technique for optimizing the design parameters in an experiment.;This dissertation presents a comprehensive POD model for quasi-static electromagnetic NDE. Applications of Taguchi methods as well as POD models in magnetic flux leakage (MFL) and magneto-optic/eddy current imaging inspections are investigated in this research

Efficient Importance sampling Simulations for Digital Communication Systems

Importance sampling is a- modified. Monte Carlo simulation technique which can dramatically reduce the computational cost of the Monte Carlo method. A complete development is presented for its use in the estimation of bit error rates /V for digital communication systems with small Gaussian noise inputs. Emphasis is on the optimal mean-translation Gaussian simulation density function design and the event simulation method as applied to systems which employ quasi-regular trellis codes. These codes include the convolutional codes and many TCM (Ungerboeck) codes. Euclidean distance information of a code is utilized to facilitate the simulation. Also, the conditional importance sampling technique is presented which can handle many non-Gaussian system inputs. Theories as well as numerical examples are given. In particular, we study the simulations of an uncoded MSK and a trellis-coded 8- PSK transmissions over a general bandlimited nonlinear satellite channel model. Our algorithms are shown to be very efficient at low Pb compared to the ordinary Monte Carlo method. Many techniques we have developed are applicable to other system simulations as building blocks for their particular system configurations and channels