An artificial neural network (ANN) for change detection from multi-temporal satellite images, which was reported in I. Feldberg (2001), has been further developed and tested, as part of a study of an area of high spat...
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An artificial neural network (ANN) for change detection from multi-temporal satellite images, which was reported in I. Feldberg (2001), has been further developed and tested, as part of a study of an area of high spatio-temporal heterogeneity along a climatic gradient between humid and and climate regions. Four recognition classes, "positive change", "negative change", "false change", and "no change" were learned by a backpropagation feedforward ANN and then applied to Landsat images that were acquired over the study area in 1992 and 1997. A comparison with existing classification techniques indicates, in many instances, significantly improved performance due to the ANN developed.
We consider a generalization of replicator dynamics as a non-cooperative evolutionary game-theoretic model of a community of N agents. All agents update their individual mixed strategy profiles to increase their total...
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We consider a generalization of replicator dynamics as a non-cooperative evolutionary game-theoretic model of a community of N agents. All agents update their individual mixed strategy profiles to increase their total payoff from the rest of the community. The properties of attractors in this dynamics are studied. Evidence is presented that under certain conditions the typical attractors of the system are corners of state space where each agent has specialized to a pure strategy, and/or the community exhibits diversity, i.e., all strategies are represented in the final states. The model suggests that new pure strategies whose payoff matrix elements satisfy suitable inequalities with respect to the existing ones can destabilize existing attractors if N is sufficiently large, and be regarded as innovations that enhance the diversity of the community.
The fact that the reception of optical information by the retinal photoreceptor and the process of its transformation to the membrane voltage response are due to an interaction between the photocurrent from the outer ...
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The fact that the reception of optical information by the retinal photoreceptor and the process of its transformation to the membrane voltage response are due to an interaction between the photocurrent from the outer segment and each ionic current in the inner segment has been confirmed by many physiological experiments. However, the properties of each ionic current in the photoreceptor have not been clear since no physiologically reliable model of the retinal photoreceptor has been constructed. This paper proposes a model of a retinal photoreceptor, which is a combination of the outer segment model (devised by Torre et al.) and the inner segment model (devised by the present authors). It has been confirmed that this model can accurately represent the electron physiological properties of a retinal photoreceptor. Using this model simulation, the relationship between the photocurrent and the photoresponse dynamics, and an oscillatory phenomena caused by a strong light flash have been analyzed. The results show that the dynamic and nonlinear response characteristics of a retinal photoreceptor are due to the interactions between the nonlinear ionic current in the inner segment and the mechanism of the intracellular calcium.
The interaction of parameter uncertainity and control performance will be considered in the case of a class of adaptive minimum-variance stochastic control algorithm. The main result of the paper is the computation of...
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The interaction of parameter uncertainity and control performance will be considered in the case of a class of adaptive minimum-variance stochastic control algorithm. The main result of the paper is the computation of the dominant term of what is called the regret. The concept of the normalized error of adaptation is introduced and fairly explicit expressions of the latter are obtained in the case of so-called quasi-Newton methods. A rigourous definition of optimality, based on the theory of stochastic complexity for adaptive minimum variance control, will also be introduced.
作者：
DUNIETZ, ISHSU, JLCMCEACHERN, MTSTOCKING, JHSWARTZ, MATROMBLY, RMThe authors
Irwin S. Dunietz John L.C. Hsu Michael T. McEachern James H. Stocking Mark A. Swartz andRodney M. Tromblyare responsible for design and development of the Manufacturing Process Control System. Mr. Dunietz joined AT&T in 1980. He is a member of the technical staff in the Manufacturing Information Automation department at AT&T Engineering Research Center Princeton New Jersey. He received an A.B. in mathematics from Cornell University and an M.S.E. in computer science from Princeton University. Mr. Hsu who joined AT&T in 1970 is a department head in the Manufacturing Information Automation department at the Engineering Research Center. He received an M.S. in electrical engineering from the University of Missouri. Mr. McEachern joined AT&T in 1962 and is a supervisor in the 5ESS™ Line Unit Manufacturing department at AT&T Technologies in Oklahoma City Oklahoma. He is responsible for the manufacturing process control center in Oklahoma City which provides computerized support for all circuit pack manufacturing. Mr. Stocking who joined AT&T in 1975 is a supervisor in the Manufacturing Information Automation department at the Engineering Research Center. He received a B.S. in chemical engineering from Rensselaer Polytechnic Institute and a Ph.D. in chemical engineering from the University of California Berkeley. Mr. Swartz joined AT&T in 1980 and is a member of the technical staff in the Manufacturing Information Automation department at the Engineering Research Center. He received an A.B. in computer science from Cornell University and an M.S. in computer science from Rutgers—The State University. Mr. Trombly who joined AT&T in 19 78 is an assistant manager at the AT&T Merrimack Valley Works in Massachusetts. Previously he was a supervisor at the Engineering Research Center. He holds a B.S. in computers and systems engineering and an M.S.E.E. from Rensselaer Polytechnic Institute.
The central challenge of all manufacturing is making products to the right standards and delivering them at the right time. AT&T is upgrading its corporate and factory resource planning systems to improve control ...
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The central challenge of all manufacturing is making products to the right standards and delivering them at the right time. AT&T is upgrading its corporate and factory resource planning systems to improve control of day-to-day manufacturing. The Manufacturing Process Control System (MPCS), developed at the AT&T Engineering research Center (ERC), provides this support. MPCS connects the shop floor with production scheduling, accounting, product data archive, and engineering support systems.
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