Mitter, S. K. (Sanjoy K.) 1933
Overview
Works:  124 works in 288 publications in 4 languages and 1,707 library holdings 

Genres:  Conference papers and proceedings 
Roles:  Editor, Author, Honoree, Translator 
Classifications:  QA402, 003 
Publication Timeline
.
Most widely held works about
S. K Mitter
 Agency history record by Massachusetts Institute of Technology( )
Most widely held works by
S. K Mitter
Nonlinear filtering and stochastic control : proceedings of the 3rd 1981 session of the Centro internazionale matematico estivo
(C.I.M.E.), held at Cortona, July 110, 1981 by
S. K Mitter(
Book
)
33 editions published between 1982 and 2008 in 3 languages and held by 464 WorldCat member libraries worldwide
33 editions published between 1982 and 2008 in 3 languages and held by 464 WorldCat member libraries worldwide
Mathematical systems theory : proceedings of the international symposium held in Udine, Italy, June 1627, 1975 by
Giovanni Marchesini(
Book
)
25 editions published between 1975 and 1976 in English and German and held by 268 WorldCat member libraries worldwide
25 editions published between 1975 and 1976 in English and German and held by 268 WorldCat member libraries worldwide
Directions in largescale systems : manyperson optimization, and decentralized control : [proceedings] by
Y. C Ho(
Book
)
14 editions published between 1975 and 2012 in English and held by 243 WorldCat member libraries worldwide
Information Flow in Decentralized Systems. Decentralized Control and Large Scale Systems. Comparison of Information Structures in Decentralized Dynamic Systems. On Fluctuations in Microscopic States of a Large System. Flow Systems. Some Remarks on the Concept of State. On Multicriteria Optimization. Dynamic Games with Coalitions and Diplomacies. Three Methods for Determining ParetoOptimal Solutions of MultipleObjective Problems. Stackelberg Strategies for Multilevel Systems. Incentive Compatible Control of Decentralized Organizations. Some Thoughts About Simple Advertising Models
14 editions published between 1975 and 2012 in English and held by 243 WorldCat member libraries worldwide
Information Flow in Decentralized Systems. Decentralized Control and Large Scale Systems. Comparison of Information Structures in Decentralized Dynamic Systems. On Fluctuations in Microscopic States of a Large System. Flow Systems. Some Remarks on the Concept of State. On Multicriteria Optimization. Dynamic Games with Coalitions and Diplomacies. Three Methods for Determining ParetoOptimal Solutions of MultipleObjective Problems. Stackelberg Strategies for Multilevel Systems. Incentive Compatible Control of Decentralized Organizations. Some Thoughts About Simple Advertising Models
Signal processing(
Book
)
1 edition published in 1990 in English and held by 226 WorldCat member libraries worldwide
1 edition published in 1990 in English and held by 226 WorldCat member libraries worldwide
Signal processing by
Louis Auslander(
Book
)
3 editions published in 1990 in English and held by 11 WorldCat member libraries worldwide
3 editions published in 1990 in English and held by 11 WorldCat member libraries worldwide
Probabilità ed informazione by
Andrea Carlo Giuseppe Mennucci(
Book
)
5 editions published between 2000 and 2008 in Italian and held by 9 WorldCat member libraries worldwide
5 editions published between 2000 and 2008 in Italian and held by 9 WorldCat member libraries worldwide
Representation and control of infinite dimensional systems(
Book
)
1 edition published in 1992 in English and held by 8 WorldCat member libraries worldwide
1 edition published in 1992 in English and held by 8 WorldCat member libraries worldwide
Simulated annealing with noisy or imprecise energy measurements by
Saul B Gelfand(
Book
)
5 editions published between 1988 and 1989 in English and held by 7 WorldCat member libraries worldwide
The annealing algorithm (Ref. 1) is modified to allow for noisy or imprecise measurements of the energy cost function. This is important when the energy cannot be measured exactly or when it is computationally expensive to do so. Under suitable conditions on the noise/imprecision, it is shown that the modified algorithm exhibits the same convergence in probability to the globally minimum energy states as the annealing algorithm (Ref. 2). Since the annealing algorithm will typically enter and exit the minimum energy states infinitely often with probability one, the minimum energy state visited by the annealing algorithm is usually tracked. The effect of using noisy or imprecise energy measurements on tracking the minimum energy state visited by the modified algorithms is examined. Keywords: Simulated annealing, Combinatorial optimization, Noisy measurements, Markov chains, computer simulation. (kt)
5 editions published between 1988 and 1989 in English and held by 7 WorldCat member libraries worldwide
The annealing algorithm (Ref. 1) is modified to allow for noisy or imprecise measurements of the energy cost function. This is important when the energy cannot be measured exactly or when it is computationally expensive to do so. Under suitable conditions on the noise/imprecision, it is shown that the modified algorithm exhibits the same convergence in probability to the globally minimum energy states as the annealing algorithm (Ref. 2). Since the annealing algorithm will typically enter and exit the minimum energy states infinitely often with probability one, the minimum energy state visited by the annealing algorithm is usually tracked. The effect of using noisy or imprecise energy measurements on tracking the minimum energy state visited by the modified algorithms is examined. Keywords: Simulated annealing, Combinatorial optimization, Noisy measurements, Markov chains, computer simulation. (kt)
Markov random fields, stochastic quantization and image analysis by
S. K Mitter(
Book
)
5 editions published between 1990 and 1992 in English and held by 7 WorldCat member libraries worldwide
Markov random fields based on the lattice Z2 have been extensively used in image analysis in a Bayesian framework as apriori models for the intensity field and on the dual lattice (Z2)* as models for boundaries. The choice of these models has usually been based on algorithmic considerations in order to exploit the local structure inherent in Markov fields. No fundamental justification has been offered for the use of Markov random fields. It is well known that there is a oneone correspondence between Markov fields and Gibbs fields on a lattice and the Markov Field is simulated by creating a Markov chain whose invariant measure is precisely the Gibbs measure. There are many ways to perform this simulation and one such way is the celebrated Metropolis Algorithm. This is also the basic idea behind Stochastic Quantization. We thus see that if the use of Markov Random fields in the context of Image Analysis can be given some fundamental justification then there is a remarkable connection between Probabilistic Image Analysis, Statistical Mechanics and Latticebased Euclidean Quantum Field Theory
5 editions published between 1990 and 1992 in English and held by 7 WorldCat member libraries worldwide
Markov random fields based on the lattice Z2 have been extensively used in image analysis in a Bayesian framework as apriori models for the intensity field and on the dual lattice (Z2)* as models for boundaries. The choice of these models has usually been based on algorithmic considerations in order to exploit the local structure inherent in Markov fields. No fundamental justification has been offered for the use of Markov random fields. It is well known that there is a oneone correspondence between Markov fields and Gibbs fields on a lattice and the Markov Field is simulated by creating a Markov chain whose invariant measure is precisely the Gibbs measure. There are many ways to perform this simulation and one such way is the celebrated Metropolis Algorithm. This is also the basic idea behind Stochastic Quantization. We thus see that if the use of Markov Random fields in the context of Image Analysis can be given some fundamental justification then there is a remarkable connection between Probabilistic Image Analysis, Statistical Mechanics and Latticebased Euclidean Quantum Field Theory
System theory : modeling, analysis, and control by
Theodore Euclid Djaferis(
Book
)
3 editions published between 1999 and 2000 in English and held by 5 WorldCat member libraries worldwide
System Theory: Modeling, Analysis and Control contains thirtythree scientific papers covering a wide range of topics in systems and control. These papers have been contributed to a symposium organized to celebrate Sanjoy K. Mitter's 65th birthday. The following research topics are addressed: distributed parameter systems, stochastic control, filtering and estimation, optimization and optimal control, image processing and vision, hierarchical systems and hybrid control, nonlinear systems, and linear systems. Also included are three survey papers on optimization, nonlinear filtering, and nonlinear systems. Recent advances are reported on the behavioral approach to systems, the relationship between differential games and robust control, estimation of diffusion processes, Markov processes, optimal control, hybrid control, stochastic control, spectral estimation, nonconvex quadratic programming, robust control, control algorithms and quantized linear systems. Innovative explorations are carried out on quantum systems from a control theory perspective, option valuation and hedging, threedimensional medical visualization, computational structure biology image processing, and hierarchical approaches to complex systems, flow control, scheduling and force feedback in fluid mechanics. The contents reflect on past research accomplishments, current research activity, and future research directions in systems and control theory
3 editions published between 1999 and 2000 in English and held by 5 WorldCat member libraries worldwide
System Theory: Modeling, Analysis and Control contains thirtythree scientific papers covering a wide range of topics in systems and control. These papers have been contributed to a symposium organized to celebrate Sanjoy K. Mitter's 65th birthday. The following research topics are addressed: distributed parameter systems, stochastic control, filtering and estimation, optimization and optimal control, image processing and vision, hierarchical systems and hybrid control, nonlinear systems, and linear systems. Also included are three survey papers on optimization, nonlinear filtering, and nonlinear systems. Recent advances are reported on the behavioral approach to systems, the relationship between differential games and robust control, estimation of diffusion processes, Markov processes, optimal control, hybrid control, stochastic control, spectral estimation, nonconvex quadratic programming, robust control, control algorithms and quantized linear systems. Innovative explorations are carried out on quantum systems from a control theory perspective, option valuation and hedging, threedimensional medical visualization, computational structure biology image processing, and hierarchical approaches to complex systems, flow control, scheduling and force feedback in fluid mechanics. The contents reflect on past research accomplishments, current research activity, and future research directions in systems and control theory
Some discrete approximations to a variational method for image segmentation by
Sanjeev Kulkarni(
Book
)
4 editions published in 1991 in English and held by 5 WorldCat member libraries worldwide
Variational formulations have been proposed for a number of tasks in early vision. Discrete versions of these problems are closely related to Markov random field models and are typically used in implementing such methods. In particular, discrete and continuous versions for the problem of image segmentation have received considerable attention from both theoretical and algorithmic perspectives. It has been previously pointed out that the usual discrete version of the segmentation problem does not properly approximate the continuous formulation in the sense that the discrete solutions may not converge to a solution of the continuous problem as the lattice spacing tends to zero. One method for modifying the discrete formulations to ensure such convergence has been previously discussed. Here we consider two other partially discrete formulations which also satisfy desirable convergence properties in the continuum limit, and we discuss some general ideas about digitized versions of the variational formulation of the segmentation problem
4 editions published in 1991 in English and held by 5 WorldCat member libraries worldwide
Variational formulations have been proposed for a number of tasks in early vision. Discrete versions of these problems are closely related to Markov random field models and are typically used in implementing such methods. In particular, discrete and continuous versions for the problem of image segmentation have received considerable attention from both theoretical and algorithmic perspectives. It has been previously pointed out that the usual discrete version of the segmentation problem does not properly approximate the continuous formulation in the sense that the discrete solutions may not converge to a solution of the continuous problem as the lattice spacing tends to zero. One method for modifying the discrete formulations to ensure such convergence has been previously discussed. Here we consider two other partially discrete formulations which also satisfy desirable convergence properties in the continuum limit, and we discuss some general ideas about digitized versions of the variational formulation of the segmentation problem
Scaling results for the variational approach to edge detection by
Thomas J Richardson(
Book
)
4 editions published in 1991 in English and held by 5 WorldCat member libraries worldwide
In another paper the first author presented an asymptotic result concerning the MumfordShah functional. In this paper an algorithm is presented which implements the scaling suggested by the asymptotic results to obtain accurate localization of edges even when only large scale edges are being detected. An approximation to E is also considered and the implications of the asymptotic results to this functional are also examined
4 editions published in 1991 in English and held by 5 WorldCat member libraries worldwide
In another paper the first author presented an asymptotic result concerning the MumfordShah functional. In this paper an algorithm is presented which implements the scaling suggested by the asymptotic results to obtain accurate localization of edges even when only large scale edges are being detected. An approximation to E is also considered and the implications of the asymptotic results to this functional are also examined
Stochastic and Adaptive Systems by
Michael Athans(
Book
)
6 editions published between 1977 and 1982 in English and held by 5 WorldCat member libraries worldwide
This research is concerned with various aspects of stochastic and adaptive systems. Topics covered include: nonlinear filtering, stochastic control, reliable and robust control system design and implementation of control laws by finitestate sequential machines. (Author)
6 editions published between 1977 and 1982 in English and held by 5 WorldCat member libraries worldwide
This research is concerned with various aspects of stochastic and adaptive systems. Topics covered include: nonlinear filtering, stochastic control, reliable and robust control system design and implementation of control laws by finitestate sequential machines. (Author)
Representation and control of infinite dimensional systems by
Alain Bensoussan(
)
8 editions published in 2007 in English and held by 5 WorldCat member libraries worldwide
This book is a most welcome addition to the literature of this field, where it serves the need for a modern treatment on topics that only very recently have found a satisfactory solution ... Many readers will appreciate the concise exposition." "Presents, or refers to, the most recent and updated results in the field. For this reason, it should serve as an excellent asset to anyone pursuing a research career in the field." "Mathematical Reviews (reviews of Volumes I and II of the First Edition) The quadratic cost optimal control problem for systems described by linear ordinary differential equations occupies a central role in the study of control systems both from a theoretical and design point of view. The study of this problem over an infinite time horizon shows the beautiful interplay between optimality and the qualitative properties of systems such as controllability, observability, stabilizability, and detectability. This theory is far more difficult for infinite dimensional systems such as those with time delays and distributed parameter systems. This reorganized, revised, and expanded edition of a twovolume set is a selfcontained account of quadratic cost optimal control for a large class of infinite dimensional systems. The book is structured into five parts. Part I reviews basic optimal control and game theory of finite dimensional systems, which serves as an introduction to the book. Part II deals with time evolution of some generic controlled infinite dimensional systems and contains a fairly complete account of semigroup theory. It incorporates interpolation theory and exhibits the role of semigroup theory in delay differential and partial differential equations. Part III studies the generic qualitative properties of controlled systems. Parts IV and V examine the optimal control of systems when performance is measured via a quadratic cost. Boundary control of parabolic and hyperbolic systems and exact controllability are also covered. New material and original features of the Second Edition: @* Part I on finite dimensional controlled dynamical systems contains new material: an expanded chapter on the control of linear systems including a glimpse into Hinfinity theory and dissipative systems, and a new chapter on linear quadratic twoperson zerosum differential games. @* A unique chapter on semigroup theory and interpolation of linear operators brings together advanced concepts and techniques that are usually treated independently. @* The material on delay systems and structural operators is not available elsewhere in book form. Control of infinite dimensional systems has a wide range and growing number of challenging applications. This book is a key reference for anyone working on these applications, which arise from new phenomenological studies, new technological developments, and more stringent design requirements. It will be useful for mathematicians, graduate students, and engineers interested in the field and in the underlying conceptual ideas of systems and control
8 editions published in 2007 in English and held by 5 WorldCat member libraries worldwide
This book is a most welcome addition to the literature of this field, where it serves the need for a modern treatment on topics that only very recently have found a satisfactory solution ... Many readers will appreciate the concise exposition." "Presents, or refers to, the most recent and updated results in the field. For this reason, it should serve as an excellent asset to anyone pursuing a research career in the field." "Mathematical Reviews (reviews of Volumes I and II of the First Edition) The quadratic cost optimal control problem for systems described by linear ordinary differential equations occupies a central role in the study of control systems both from a theoretical and design point of view. The study of this problem over an infinite time horizon shows the beautiful interplay between optimality and the qualitative properties of systems such as controllability, observability, stabilizability, and detectability. This theory is far more difficult for infinite dimensional systems such as those with time delays and distributed parameter systems. This reorganized, revised, and expanded edition of a twovolume set is a selfcontained account of quadratic cost optimal control for a large class of infinite dimensional systems. The book is structured into five parts. Part I reviews basic optimal control and game theory of finite dimensional systems, which serves as an introduction to the book. Part II deals with time evolution of some generic controlled infinite dimensional systems and contains a fairly complete account of semigroup theory. It incorporates interpolation theory and exhibits the role of semigroup theory in delay differential and partial differential equations. Part III studies the generic qualitative properties of controlled systems. Parts IV and V examine the optimal control of systems when performance is measured via a quadratic cost. Boundary control of parabolic and hyperbolic systems and exact controllability are also covered. New material and original features of the Second Edition: @* Part I on finite dimensional controlled dynamical systems contains new material: an expanded chapter on the control of linear systems including a glimpse into Hinfinity theory and dissipative systems, and a new chapter on linear quadratic twoperson zerosum differential games. @* A unique chapter on semigroup theory and interpolation of linear operators brings together advanced concepts and techniques that are usually treated independently. @* The material on delay systems and structural operators is not available elsewhere in book form. Control of infinite dimensional systems has a wide range and growing number of challenging applications. This book is a key reference for anyone working on these applications, which arise from new phenomenological studies, new technological developments, and more stringent design requirements. It will be useful for mathematicians, graduate students, and engineers interested in the field and in the underlying conceptual ideas of systems and control
On sampling methods and annealing algorithms by
Saul B Gelfand(
Book
)
4 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide
Discrete Markov random fields (MRF's) defined on a finite lattice have seen significant application as stochastic models for images [1], [2]. There are two fundamental problems associated with image processing based on such random field models. First, we want to generate realizations of the random fields to determine their suitability as models of our prior knowledge. Second, we want to collect statistics and perform optimizations associated with the random fields to solve modelbased estimation problems, e.g., image restoration and segmentation. According to the HammersleyClifford Theorem [3], MRF's which are defined on a lattice are in onetoone correspondence with Gibbs distributions. Starting with [4] there have been various constructions of Markov chains which possess a Gibbs invariant distribution, and whose common characteristic is that their transition probabilities depend only on the ratio of the Gibbs probabilities (and not on the normalization constant). These chains can be used via Monte Carlo simulation for sampling from Gibbs distributions at a fixed temperature, and for finding globally minimum energy states by slowly decreasing the temperature as in the simulated annealing (or stochastic relaxation) method [5], [6]. Certain types of diffusion processes which also have a Gibbs invariant distribution can be used for the same purposes when the random fields are continuousvalued [7], [8]
4 editions published in 1990 in English and held by 5 WorldCat member libraries worldwide
Discrete Markov random fields (MRF's) defined on a finite lattice have seen significant application as stochastic models for images [1], [2]. There are two fundamental problems associated with image processing based on such random field models. First, we want to generate realizations of the random fields to determine their suitability as models of our prior knowledge. Second, we want to collect statistics and perform optimizations associated with the random fields to solve modelbased estimation problems, e.g., image restoration and segmentation. According to the HammersleyClifford Theorem [3], MRF's which are defined on a lattice are in onetoone correspondence with Gibbs distributions. Starting with [4] there have been various constructions of Markov chains which possess a Gibbs invariant distribution, and whose common characteristic is that their transition probabilities depend only on the ratio of the Gibbs probabilities (and not on the normalization constant). These chains can be used via Monte Carlo simulation for sampling from Gibbs distributions at a fixed temperature, and for finding globally minimum energy states by slowly decreasing the temperature as in the simulated annealing (or stochastic relaxation) method [5], [6]. Certain types of diffusion processes which also have a Gibbs invariant distribution can be used for the same purposes when the random fields are continuousvalued [7], [8]
Avtomatizacija v proektirovanii(
Book
)
1 edition published in 1972 in Russian and held by 5 WorldCat member libraries worldwide
1 edition published in 1972 in Russian and held by 5 WorldCat member libraries worldwide
Hierarchical image segmentation : part I : detection of regular curves in a vector graph by
Stefano Casadei(
Book
)
3 editions published in 1996 in English and held by 4 WorldCat member libraries worldwide
3 editions published in 1996 in English and held by 4 WorldCat member libraries worldwide
Optimal control and nonlinear filtering for nondegenerate diffusion processes by
Wendell H Fleming(
Book
)
4 editions published between 1981 and 1982 in English and held by 4 WorldCat member libraries worldwide
A linear parabolic partial differential equation describing the pathwise filter for a nondegenerate diffusion is changed, by an expotential substitution, into the dynamic programming equation of an optimal stochastic control problem. This substitution is applied to obtain results about the rate of decay as the numerical value of chi approaches infinity of solutions p(chi, tau) to the pathwise filter equation, and for solutions of the corresponding Zakai equation
4 editions published between 1981 and 1982 in English and held by 4 WorldCat member libraries worldwide
A linear parabolic partial differential equation describing the pathwise filter for a nondegenerate diffusion is changed, by an expotential substitution, into the dynamic programming equation of an optimal stochastic control problem. This substitution is applied to obtain results about the rate of decay as the numerical value of chi approaches infinity of solutions p(chi, tau) to the pathwise filter equation, and for solutions of the corresponding Zakai equation
Active learning using arbitrary binary valued queries by
Sanjeev Kulkarni(
Book
)
4 editions published in 1990 in English and held by 4 WorldCat member libraries worldwide
The original and most widely studied PAC model for learning assumes a passive learner in the sense that the learner plays no role in obtaining information about the unknown concept. That is, the samples are simply drawn independently from some probability distribution. Some work has been done on studying more powerful oracles and how they affect learnability. To find bounds on the improvement that can be expected from using oracles, we consider active learning in the sense that the learner has complete choice in the information received. Specifically, we allow the learner to ask arbitrary yes/no questions. We consider both active learning under a fixed distribution and distributionfree active learning. In the case of active learning, the underlying probability distribution is used only to measure distance between concepts. For learnability with respect to a fixed distribution, active learning does not enlarge the set of learnable concept classes, but can improve the sample complexity. For distributionfree learning, it is shown that a concept class is actively learnable iff it is finite, so that active learning is in fact less powerful than the usual passive learning model. We also consider a form of distributionfree learning in which the learner knows the distribution being used, so that 'distributionfree' refers only to the requirement that a bound on the number of queries can be obtained uniformly over all distributions. Even with the side information of the distribution being used, a concept class is actively learnable iff it has finite VC dimension, so that active learning with the side information still does not enlarge the set of learnable concept classes
4 editions published in 1990 in English and held by 4 WorldCat member libraries worldwide
The original and most widely studied PAC model for learning assumes a passive learner in the sense that the learner plays no role in obtaining information about the unknown concept. That is, the samples are simply drawn independently from some probability distribution. Some work has been done on studying more powerful oracles and how they affect learnability. To find bounds on the improvement that can be expected from using oracles, we consider active learning in the sense that the learner has complete choice in the information received. Specifically, we allow the learner to ask arbitrary yes/no questions. We consider both active learning under a fixed distribution and distributionfree active learning. In the case of active learning, the underlying probability distribution is used only to measure distance between concepts. For learnability with respect to a fixed distribution, active learning does not enlarge the set of learnable concept classes, but can improve the sample complexity. For distributionfree learning, it is shown that a concept class is actively learnable iff it is finite, so that active learning is in fact less powerful than the usual passive learning model. We also consider a form of distributionfree learning in which the learner knows the distribution being used, so that 'distributionfree' refers only to the requirement that a bound on the number of queries can be obtained uniformly over all distributions. Even with the side information of the distribution being used, a concept class is actively learnable iff it has finite VC dimension, so that active learning with the side information still does not enlarge the set of learnable concept classes
An existence theorem and lattice approximations for a variational problem arising in computer vision by
Sanjeev Kulkarni(
Book
)
3 editions published in 1989 in English and held by 4 WorldCat member libraries worldwide
3 editions published in 1989 in English and held by 4 WorldCat member libraries worldwide
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Related Identities
 Moro, A. (Antonio) Author Editor
 Centro internazionale matematico estivo Editor
 Marchesini, Giovanni 1936 Author Editor
 Ho, YuChi 1934 Editor
 Kailath, Thomas Editor
 Auslander, Louis Editor
 Khargonekar, P. (Pramod) Editor
 Helton, J. William 1944 Editor
 Grünbaum, F. Alberto Editor
 University of Minnesota Institute for Mathematics and Its Applications
Useful Links
Associated Subjects
Adaptive control systems Algorithms Artificial intelligence Athans, Michael Automatic control Brown, Gordon S Coding theory Computer engineering Computer vision Control theory Curves Differential equations, Parabolic Differential equations, Partial Diffusion processes Distribution (Probability theory) Dynamic programming Engineering Existence theorems Filters (Mathematics) Gallager, Robert G Graph theory Image processing Image processingDigital techniques Lattice theory Learning Markov processes Massachusetts Institute of Technology.Electronic Systems Laboratory Massachusetts Institute of Technology.Laboratory for Information and Decision Systems Massachusetts Institute of Technology.Servomechanisms Laboratory Mathematical optimization Mathematics Mechanical engineering Mitter, S. K.(Sanjoy K.), Operator equations, Nonlinear Operator theory Random fields Reintjes, J. Francis Sequential machine theory Signal processingMathematics Simulated annealing (Mathematics) Stochastic control theory Stochastic differential equations Stochastic processes Structural control (Engineering) System analysis System theory Variational principles