by Michael Athans and Sanjoy K. Mitter. / Research supported by Air Force Office of Scientific Research (AFSC) Research Grant AF-AFOSR 72-2273. Report for 1975/76 distributed through Industrial Liaison Program.

The observability measure based on the mutual information between the last state and the measurement sequence originally proposed by Mohler and Hwang (1988) is analyzed in detail and improved further for linear time invariant discrete-time Gaussian stochastic systems by extending the definition to the observability measure of a state sequence. By using the new observability measure it is shown that the unobservable states of the deterministic system have no effect on this measure and any observable part with no measurement uncertainty makes it infinite. Other distance measures i.e., Bhattacharyya and Hellinger distances are also investigated to be used as observability measures. The relationships between the observability measures and the covariance matrices of Kalman filter and the state sequence conditioned on the measurement sequence are derived. Steady state characteristics of the observability measure based on the last state is examined. The observability measures of a subspace of the state space, an individual state, the modes of the system are investigated. One of the results obtained in this part is that the deterministically unobservable states may have nonzero observability measures. The observability measures based on the mutual information are represented recursively and calculated for nonlinear stochastic systems. Then the measures are applied to a nonlinear stochastic system by using the particle filter methods. The arguments given for the LTI case are also observed for nonlinear stochastic systems. The second moment approximation deviates from the actual values when the nonlinearity in the system increases.

Diss. Uppsala : Univ., 2004.

Thesis (M.Sc. (Hons.)) -- University of Western Sydney, 2001. / "A thesis presented to the University of Western Sydney in partial fulfilment of the requirements for the degree of Master of Science" Bibliography : leaves 65-69.

Thesis (Ph. D.)--Rijksuniversiteit te Groningen. / At head of title: Rijksuniversiteit te Groninge. Summary in Dutch. Parts of this thesis are based on material originally appearing in Statistica Neerlandica, 1978, Automatica, 1981 and the proceedings of Dynamic Modelling and Control of National Economics 1981 ... Includes index. Bibliography: p. 153-159.

The stochasticity of cellular processes and the small number of molecules in a cell make deterministic models inappropriate for modelling chemical reactions at the single cell level. The Chemical Master Equation (CME) is widely used to describe the evolution of biochemical reactions inside cells stochastically but is computationally expensive. The Linear Noise Approximation (LNA) is a popular method for approximating the CME in order to carry out inference and parameter estimation in stochastic models. Data from stochastic systems is often aggregated over time. One such example is in luminescence bioimaging, where a luciferase reporter gene allows us to quantify the activity of proteins inside a cell. The luminescence intensity emitted from the luciferase experiments is collected from single cells and is integrated over a time period (usually 15 to 30 minutes), which is then collected as a single data point. In this work we consider stochastic systems that we approximate using the Linear Noise Approximation (LNA). We demonstrate our method by learning the parameters of three different models from which aggregated data was simulated, an Ornstein-Uhlenbeck model, a Lotka-Voltera model and a gene transcription model. We have additionally compared our approach to the existing approach and find that our method is outperforming the existing one. Finally, we apply our method in microscopy data from a translation inhibition experiment.

abstract: Resource allocation in communication networks aims to assign various resources such as power, bandwidth and load in a fair and economic fashion so that the networks can be better utilized and shared by the communicating entities. The design of efficient resource-allocation algorithms is, however, becoming more and more challenging due to the precipitously increasing scale of the networks. This thesis strives to understand how to design such low-complexity algorithms with performance guarantees. In the first part, the link scheduling problem in wireless ad hoc networks is considered. The scheduler is charge of finding a set of wireless data links to activate at each time slot with the considerations of wireless interference, traffic dynamics, network topology and quality-of-service (QoS) requirements. Two different yet essential scenarios are investigated: the first one is when each packet has a specific deadline after which it will be discarded; the second is when each packet traverses the network in multiple hops instead of leaving the network after a one-hop transmission. In both scenarios the links need to be carefully scheduled to avoid starvation of users and congestion on links. One greedy algorithm is analyzed in each of the two scenarios and performance guarantees in terms of throughput of the networks are derived. In the second part, the load-balancing problem in parallel computing is studied. Tasks arrive in batches and the duty of the load balancer is to place the tasks on the machines such that minimum queueing delay is incurred. Due to the huge size of modern data centers, sampling the status of all machines may result in significant overhead. Consequently, an algorithm based on limited queue information at the machines is examined and its asymptotic delay performance is characterized and it is shown that the proposed algorithm achieves the same delay with remarkably less sampling overhead compared to the well-known power-of-two-choices algorithm. Two messages of the thesis are the following: greedy algorithms can work well in a stochastic setting; the fluid model can be useful in "derandomizing" the system and reveal the nature of the algorithm. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2015

Orientador: Jose Claudio Geromel / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-06T08:10:58Z (GMT). No. of bitstreams: 1 Goncalves_AlimPedrodeCastro_M.pdf: 293253 bytes, checksum: 4365f5ae19ae33e8d97053c2c57ad15d (MD5) Previous issue date: 2006 / Resumo: Este trabalho aborda alguns dos aspectos mais relevantes relacionados à estabilidade e norma H2 de sistemas lineares discretos sujeitos a saltos markovianos, bem como as estratégias para a síntese de controle por realimentação de estado. A maior contribuição apresentada é um método para calcular os ganhos de realimentação de estado sem a necessidade de observar, em cada instante, todos os estados da cadeia de Markov / Abstract: This work discusses some of the most relevant aspects of stability and H2 norm of discrete-time markov jump linear systems, as well as a method for state feedback contraI design. Our major contribution is on the definition of a procedure to determine the state feedback gains without the complete knowledge, at each instant of time, of the Markov chain state / Mestrado / Automação / Mestre em Engenharia Elétrica

Orientador: João Bosco Ribeiro do Val / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-06T12:35:26Z (GMT). No. of bitstreams: 1 Moises_GustavoViniciusLourenco_M.pdf: 6246087 bytes, checksum: c9946249f751bda598372a7979e3a189 (MD5) Previous issue date: 2005 / Resumo: Esta dissertação possui como tema a filtragem via Métodos de Monte Carlo para Cadeia de Markov. Através do estudo e da análise dos algoritmos de amostragem estocástica aliados às implementações numéricas, foi desenvolvida uma metodologia para avaliar e comparar as diversas técnicas de filtragem encontrados na literatura. Aplicações associando a filtragem recursiva ao controle via horizonte retrocedente também foram utilizadas para verificar o desempenho e a estabilidade do conjunto filtro/controle / Abstract: The dissertation's theme is the filtering problem via Markov Chain Monte Carlo methods. Combining the estudy and the analysis of the stochastic sampling algorithms with numerical implementations, we developted a methodology to evaluate and compare several filters in literature. Aplications of recursive filtering in association with receding horizon control tecniques were used to verify the finality and stability of the filter/control combination / Mestrado / Automação / Mestre em Engenharia Elétrica

Orientador: Jose Claudio Geromel / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-13T22:17:12Z (GMT). No. of bitstreams: 1 Goncalves_AlimPedrodeCastro_D.pdf: 1252972 bytes, checksum: 74f7eb667115d725da9b80029974a03f (MD5) Previous issue date: 2009 / Resumo: Este trabalho tem por objetivo o estudo do projeto de controladores dinâmicos H2 e H? por realimentação de saída para sistemas discretos com parâmetros sujeitos a saltos markovianos. Inicialmente, estudamos o caso de filtragem e propomos diferentes técnicas de projeto para casos especiais relacionados à disponibilidade do estado da cadeia de Markov, também chamado modo, ou a matriz de probabilidades de transição parcialmente conhecida. O resultado principal é a caracterização de todos os controladores dinâmicos lineares tais que a norma da saída controlada é limitada, levando a solução do problema de projeto do controlador linear ótimo H2 ou H?, sob a hipótese de conhecimento do modo por parte do controlador. Todos os projetos são expressos em termos de desigualdades matriciais lineares. Para ilustrar possíveis aplicações dos resultados teóricos, consideramos o projeto de um controlador cuja entrada é transmitida por um canal markoviano, além da modelagem estatística de falhas em sensores/atuadores / Abstract: This work addresses the H2 and H? output feedback design problem for discrete-time Markov jump linear systems. Initially, we study the filtering problem and propose different design techniques to deal with the Markov parameter, often called mode, availability and/or partly known transition probability. The main result is the characterization of all linear controllers such that the controlled output norm remains bounded by a given level, yielding the complete solution of the mode-dependent H2 and H? linear control design problem. All controllers are designed by solving linear matrix inequalities. The theory is illustrated by means of practical examples, consisting of control over data communication through a markovian channel and of statistical modelling of sensors/actuators failures / Doutorado / Automação / Doutor em Engenharia Elétrica