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Systems Science and Cybernetics, IEEE Transactions on

Issue 2 • Date April 1969

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Displaying Results 1 - 17 of 17
  • [Table of contents]

    Page(s): c1
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  • IEEE Systems Science and Cybernetics Group

    Page(s): c2
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  • SSC Group ADCOM Members

    Page(s): 105 - 108
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  • Unsupervised Learning Minimum Risk Pattern Classification for Dependent Hypotheses and Dependent Measurements

    Page(s): 109 - 115
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    A recursive Bayes optimal solution is found for the problem of sequential multicategory pattern recognition when unsupervised learning is required. An unknown parameter model is developed which, for the pattern classification problem, allows for 1) both constant and time-varying unknown parameters, 2) partially unknown probability laws of the hypotheses and time-varying parameter sequences, 3) dependence of the observations on past as well as present hypotheses and parameters, and most significantly, 4) sequential dependencies in the observations arising from either (or both) dependency in the pattern or information source (context dependence) or in the observation medium (sequential measurement correlation), these dependencies being up to any finite Markov orders. For finite parameter spaces, the solution which is Bayes optimal (minimum risk) at each step is found and shown to be realizable in recursive form with fixed memory requirements. The asymptotic properties of the optimal solution are studied and conditions established for the solution (in addition to making best use of available data at each step) to converge in performance to operation with knowledge of the (unobservable) constant unknown parameters. View full abstract»

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  • Open-Hearth and Basic-Oxygen Furnaces: An Allocation Model for Production Planning

    Page(s): 115 - 124
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    In a steelworks where both open-hearth and basic-oxygen furnaces are available, there is a genuine problem of allocation of total steel production between the two processes. After briefly explaining the two processes, an attempt is made to develop a linear programming model for obtaining optimum allocation of total steel production between the two processes for production planning purposes. Equations and inequations describing the various technological constraints for the furnaces have been incorporated in the model. A linear cost function is minimized. Procedures for evaluating various technological and cost coefficients (used in the model) have been explained indicating the nature of the difficulties that are encountered in such evaluations under normal operational conditions. The model can also predict the required operation levels of blast furnaces and lime burning plants at different levels of total steel production. View full abstract»

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  • A Technique for On-Line Steady-State Optimizing Control

    Page(s): 125 - 132
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    A technique for on-line steady-state optimizing control is developed for systems subject to disturbance inputs. The parameters of the control algorithm are updated so as to maximize the expected system performance, based on a prediction of the frequency distribution of the disturbance inputs over the next time interval of operation. The statistical parameters of the distribution are assumed to be slowly time-varying and the adaptation procedure includes their updating, based on past observations of the disturbance variables. Some of the advantages and limitations of the technique are demonstrated by application to the control of a simulated stirred-tank reactor. View full abstract»

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  • Constraint Theory, Part II: Model Graphs and Regular Relations

    Page(s): 132 - 140
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    The foundations of a "constraint theory" whose goal is the systematic analysis of consistency and computability in heterogeneous mathematical models of very high dimension were established in a previous paper [1]. The eventual objective of this theory is to automate the automatic determination of whether a complex mathematical model and its required computations are "well posed." This part concentrates on the topological properties of the bipartite model graph defined in [1] and the application of these properties to the location of intrinsic constraint in large mathematical models composed of "regular" relations. In particular, the model graph concepts of connected components, trees, circuits, circuit rank, circuit index, and constraint potential are defined with sufficient precision to allow automatic computation. Regular relations, the most commonly employed for scientific models, are defined and the sources of constraint are identified with the "basic nodal square," a special subgraph embedded within the total model graph. A procedure is then developed which uses the topological properties developed earlier to locate the basic nodal squares within a large complex model graph. The ultimate use of the sources of intrinsic constraint is to check the consistency of the model and the allowability of the computations put to it. View full abstract»

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  • Some Novel Properties of Wiener's Canonical Expansion

    Page(s): 140 - 144
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    An expression of Wiener's orthogonal functionals {Fn} for an arbitrary variance parameter is presented along with some of its salient properties. A necessary and sufficient condition for the convergence of the corresponding Wiener series is given. Introduction of the variance parameter enables us to discuss some interesting algebraic properties of Wiener's canonical networks also. It is shown that they form a Boolean algebra, each element of which represents a whole family of Wiener's canonical networks for a fixed variance parameter. Applicability of the Wiener theory to time-variable systems and to non-Gaussian processes is briefly discussed. View full abstract»

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  • Stochastic Automata Games

    Page(s): 145 - 149
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    The collective behavior of finite state stochastic automata is considered, which is of interest in view of the possibility of modeling group behavior of subjects in terms of these automata. The natural language for considering the collective behavior is that of game theory. After a brief introduction to a class of deterministic automata, the stochastic automaton is formulated and a nonlinear reinforcement specified. The finite state stochastic automaton is first considered in a game with nature, and conditions under which the automaton's winnings reach the Von Neumann value of the game are established. Next, two stochastic automata with an arbitrary number of states for each are considered in a game, the game matrix being specified. Performance of the automata for various conditions on the elements of the game matrix is considered. In a comparison of performance with deterministic automata, it is established that, for performance comparable to that of the finite state stochastic automaton, the deterministic automaton needs an infinite number of states. Finally, some games are simulated on a computer which verifies the general analysis and further sheds light on the details of the game. View full abstract»

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  • Calamity Detection Using Nonparametric Statistics

    Page(s): 150 - 155
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    The problem of detecting a sudden change or calamity in the normal operation of a control system is investigated for the case of a deterministic system with measurements corrupted by unknown stationary noise. The basic technique concerns the use of nonparametric two-sample tests. As a consequence, the system under observation does not need to be known in detail; all that is required is a set of observations corresponding to the normal operation of the system. View full abstract»

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  • Three-Dimensional Morphology of Systems Engineering

    Page(s): 156 - 160
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    A study of the structure and form of systems engineering using the technique of morphological analysis is presented. The result is a model of the field of systems engineering that may be rich in applications. Three uses given for illustration are in taxonomy, discovery of new sets of activities, and systems science curriculum design. View full abstract»

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  • Hypercorrelation: A Concept for System Characterization

    Page(s): 161 - 166
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    The concept of "hypercorrelation" is introduced as a method for the statistical characterization of systems. It is shown that there exists a minimal set of hypercorrelation coefficients which uniquely characterizes a system for a given transfer function. The method of hypercorrelation is applied to management models and it is shown that certain useful economic conclusions can be drawn from the analysis. Also, a brief mention is made of its application to the characterization of simple multiport systems. View full abstract»

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  • Sequential Algorithm for the Design of Piecewise Linear Classifiers

    Page(s): 166 - 168
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    A sequential algorithm for designing piecewise linear classification functions without a priori knowledge of pattern class distributions is described. The algorithm combines adaptive error correcting linear classifier design procedures and clustering techniques under control of a performance criterion. The classification function structure is constrained to minimize design calculations and increase recognition through-put for many classification problems. Examples from the literature are used to evaluate this approach relative to other classification algorithms. View full abstract»

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  • Increased Efficiency of Neighborhood Storage

    Page(s): 168 - 170
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    A technique called neighborhood storage has been developed previously to store and regenerate extensive lists of sequential steps of a decision process such as all the shortest routes in a transportation system. The original formulation can reduce the required storage by more than an order of magnitude over classical techniques. The purpose of this correspondence is to provide a more efficient technique through a modification of the means of selecting feasible intermediate vertices. The revisions for the more efficient storage technique are presented along with comparisons in terms of the original formulation as well as a classical technique. View full abstract»

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  • Book Reviews

    Page(s): 170 - 171
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  • Contributors

    Page(s): 171 - 172
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  • Information for authors

    Page(s): 172b
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