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Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals, such as sound, images, and scientific measurements. Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted signals, subjective video quality and to also detect or pinpoint components of interest in a measured signal.
Geostatistics is a branch of statistics focusing on spatial or spatiotemporal datasets. Developed originally to predict probability distributions of ore grades for mining operations, it is currently applied in diverse disciplines including petroleum geology, hydrogeology, hydrology, meteorology, oceanography, geochemistry, geometallurgy, geography, forestry, environmental control, landscape ecology, soil science, and agriculture. Geostatistics is applied in varied branches of geography, particularly those involving the spread of diseases (epidemiology), the practice of commerce and military planning (logistics), and the development of efficient spatial networks. Geostatistical algorithms are incorporated in many places, including geographic information systems (GIS).
In optimal control theory, the Hamilton-Jacobi-Bellman (HJB) equation gives a necessary and sufficient condition for optimality of a control with respect to a loss function. It is, in general, a nonlinear partial differential equation in the value function, which means its solution is the value function itself. Once this solution is known, it can be used to obtain the optimal control by taking the maximizer of the Hamiltonian involved in the HJB equation.
In probability theory, fractional Brownian motion (fBm), also called a fractal Brownian motion, is a generalization of Brownian motion. Unlike classical Brownian motion, the increments of fBm need not be independent. fBm is a continuous-time Gaussian process BH(t) on [0, T], that starts at zero, has expectation zero for all t in [0, T], and has the following covariance function:
In control theory, the linear–quadratic–Gaussian (LQG) control problem is one of the most fundamental optimal control problems, and it can also be operated repeatedly for model predictive control. It concerns linear systems driven by additive white Gaussian noise. The problem is to determine an output feedback law that is optimal in the sense of minimizing the expected value of a quadratic cost criterion. Output measurements are assumed to be corrupted by Gaussian noise and the initial state, likewise, is assumed to be a Gaussian random vector.
Discrete tomography focuses on the problem of reconstruction of binary images from a small number of their projections.
In the theory of stochastic processes, filtering describes the problem of determining the state of a system from an incomplete and potentially noisy set of observations. While originally motivated by problems in engineering, filtering found applications in many fields from signal processing to finance.
David John Aldous FRS is a mathematician known for his research on probability theory and its applications, in particular in topics such as exchangeability, weak convergence, Markov chain mixing times, the continuum random tree and stochastic coalescence. He entered St. John's College, Cambridge, in 1970 and received his Ph.D. at the University of Cambridge in 1977 under his advisor, D. J. H. Garling. Since 1979 Aldous has been on the faculty at University of California, Berkeley.
Stochastic control or stochastic optimal control is a sub field of control theory that deals with the existence of uncertainty either in observations or in the noise that drives the evolution of the system. The system designer assumes, in a Bayesian probability-driven fashion, that random noise with known probability distribution affects the evolution and observation of the state variables. Stochastic control aims to design the time path of the controlled variables that performs the desired control task with minimum cost, somehow defined, despite the presence of this noise. The context may be either discrete time or continuous time.
Anders Gunnar Lindquist is a Swedish applied mathematician and control theorist. He has made contributions to the theory of partial realization, stochastic modeling, estimation and control, and moment problems in systems and control. In particular, he is known for the discovery of the fast filtering algorithms for (discrete-time) Kalman filtering in the early 1970s, and his seminal work on the separation principle of stochastic optimal control and, in collaborations with Giorgio Picci, the Geometric Theory for Stochastic Realization. Together with late Christopher I. Byrnes and Tryphon T. Georgiou, he is one of the founder of the so-called Byrnes-Georgiou-Lindquist school. They pioneered a new moment-based approach for the solution of control and estimation problems with complexity constraints.
Darinka Dentcheva is a Bulgarian-American mathematician, noted for her contributions to convex analysis, stochastic programming, and risk-averse optimization.
Stochastic cellular automata or probabilistic cellular automata (PCA) or random cellular automata or locally interacting Markov chains are an important extension of cellular automaton. Cellular automata are a discrete-time dynamical system of interacting entities, whose state is discrete.
System identification is a method of identifying or measuring the mathematical model of a system from measurements of the system inputs and outputs. The applications of system identification include any system where the inputs and outputs can be measured and include industrial processes, control systems, economic data, biology and the life sciences, medicine, social systems and many more.
Christiaan Heij is a Dutch mathematician, Assistant Professor in statistics and econometrics at the Econometric Institute at the Erasmus University Rotterdam, known for his work in the field of mathematical systems theory, and econometrics.
Ji-Feng Zhang was born in Shandong, China. He is currently the vice-chair of the technical board of the International Federation of Automatic Control (IFAC), the vice-president of the Systems Engineering Society of China (SESC), the vice-president of the Chinese Association of Automation (CAA), the chair of the technical committee on Control Theory (CAA), and the editor-in-chief for both All About Systems and Control and the Journal of Systems Science and Mathematical Sciences.
Vivek Shripad Borkar is an Indian electrical engineer, mathematician and an Institute chair professor at the Indian Institute of Technology, Mumbai. He is known for introducing analytical paradigm in stochastic optimal control processes and is an elected fellow of all the three major Indian science academies viz. the Indian Academy of Sciences, Indian National Science Academy and the National Academy of Sciences, India. He also holds elected fellowships of The World Academy of Sciences, Institute of Electrical and Electronics Engineers, Indian National Academy of Engineering and the American Mathematical Society. The Council of Scientific and Industrial Research, the apex agency of the Government of India for scientific research, awarded him the Shanti Swarup Bhatnagar Prize for Science and Technology, one of the highest Indian science awards for his contributions to Engineering Sciences in 1992. He received the TWAS Prize of the World Academy of Sciences in 2009.
In mathematics, specifically in control theory, subspace identification (SID) aims at identifying linear time invariant (LTI) state space models from input-output data. SID does not require that the user parametrizes the system matrices before solving a parametric optimization problem and, as a consequence, SID methods do not suffer from problems related to local minima that often lead to unsatisfactory identification results.
Uri Shaked is an Israeli professor of Electrical Engineering in the Engineering Faculty at Tel Aviv University, specializing in control theory of uncertain systems. In 2017 he was awarded the Israel Prize for engineering research.
Walter Murray Wonham is a Canadian control theorist and professor at the University of Toronto. He dealt with multi-variable geometric control theory, stochastic control and stochastic filters, and more recently the control of discrete event systems from the standpoint of mathematical logic and formal languages.
JinqiaoDuan is a professor of mathematics at Illinois Institute of Technology, Chicago, USA.
References
- ↑ "Ph.D. Dissertations - Eugene Wong". UC Berkeley. Retrieved 19 May 2014.
- ↑ Jan H. van Schuppen at the Mathematics Genealogy Project
