By Topic

Systems, Man and Cybernetics, IEEE Transactions on

Issue 1 • Date Jan. 1971

Filter Results

Displaying Results 1 - 24 of 24
  • [Table of contents]

    Save to Project icon | Request Permissions | PDF file iconPDF (1732 KB)  
    Freely Available from IEEE
  • IEEE Systems, Man, and Cybernetics Group

    Page(s): nil1
    Save to Project icon | Request Permissions | PDF file iconPDF (145 KB)  
    Freely Available from IEEE
  • [Breaker page]

    Page(s): nil1
    Save to Project icon | Request Permissions | PDF file iconPDF (145 KB)  
    Freely Available from IEEE
  • Editorial

    Page(s): 1
    Save to Project icon | Request Permissions | PDF file iconPDF (73 KB)  
    Freely Available from IEEE
  • A Model of Predictive Control in Visual Target Tracking

    Page(s): 2 - 7
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1622 KB)  

    In tracking repetitive square waves, the latency of saccadic eye movement to a change in target position decreases as the tracking run progresses. The latency in the steady state takes its minimum value for frequencies between 0.5 and 1.0 Hz. A model is proposed to predict this behavior of the saccadic eye movement system. Forming an estimate of target motion and carrying out the optimal control based on the estimation are the main features of the model. The estimate, in particular that of the period of square waves, is assumed to be performed with some inevitable variance depending on the input frequency because of the sampled data nature of the system and the memory mechanism becoming more uncertain with increasing time. In relation to sinusoidal target motions, a similar model is suggested to explain the reduction of latency to the steady-state value soon after the onset of target motion. Further, the transfer characteristics in the steady state are obtained for both the open-loop and closed-loop systems. It turns out that in both cases the predictive controller can be approximated by a serial connection of a high-gain element and a predictive element. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Cybernetics of Economic Systems

    Page(s): 8 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1842 KB)  

    Techniques and concepts from cybernetics and engineering are used to combine partial models from economic literature into a more comprehensive macroeconomic model. The resulting linear model is capable of exhibiting short-period inventory cycles and long-period fixed capital investment cycles around a long-term constant growth rate trend. The rate of growth of total production is controlled by a monetary mechanism which links innovative investment to the level of unemployment. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Full text access may be available. Click article title to sign in or learn about subscription options.
  • Empirical Bayesian Learning

    Page(s): 19 - 23
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (726 KB)  

    It is shown that a certain weighted average of the prior distribution and the empirical distribution yields an estimate of the posterior distribution that is consistent with Bayes' theorem. A comparison of this approach and conventional parametric Bayesian estimation is made for some specific cases. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Context Algorithm for Pattern Recognition and Image Interpretation

    Page(s): 24 - 30
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1315 KB)  

    One method of interpreting aerial photographs is to divide a frame of imagery into square cells, to extract recognition data from each cell, and to classify one cell at a time according to statistical decision theory. An algorithm for extracting contextual information from neighboring cells to improve cell recognition performance in such a system is presented. The algorithm was tested with a Monte Carlo technique which drew contextual information from real imagery but which simulated the as much as one half by the addition of context, and the amount of improvement was found to be largely independent of the parameters of the simulation. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Simulation of Nigerian Development: Northern Region Model

    Page(s): 31 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3101 KB)  

    A multidisciplinary team is currently studying the applicability of computer simulation to problems of agricultural sector development in Nigeria. The program has as one of its major objectives the exploration of simulation as a tool for aiding policy makers of that country concerned with meeting the nutritional needs of the population, generation of foreign exchange earnings and raw material inputs for industrialization, and other important questions relating to long-run development of the agricultural sector and its interaction with nonagricultural development. While the project is localized in a particular country, models are being developed with adaptability to other developing areas of the world as a major objective. To date, a model of the northern region of the country has been developed which will be linked to a southern model currently under construction. The structure of the northern model is described in some detail as an example of the application of simulation to a macroeconomic system. Preliminary tests of this model are discussed and an assessment of the capabilities and limitations of this approach to planning development in emerging countries is given. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Logical Networks for Feature Extraction

    Page(s): 43 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2676 KB)  

    The extraction of features for the purpose of reconstituting a pattern set may be particularly useful in those cases where a large number of patterns can be decomposed into a relatively small set of sub-patterns. By the representation of pattern and feature sets as matrices, the concept of feature determination has been extended to multilevel features and the hierarchical organization of logical networks employing these features. An algorithm is presented to sequentially generate features by an adaptive process of altering weights in a network of thresholdlike logical elements. Experimental results indicate the potential of the algorithm in organizing a recognition network to correspond to the information structure of the pattern set. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Markov Decisions on a Partitioned State Space

    Page(s): 55 - 60
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1073 KB)  

    An important practical constraint on admissible control policies is defined for the Markov decision process. The framework of an algorithm based on the infinite return optimization algorithms of Howard and Jewell is suggested to compute the optimal policy under this constraint. Iterative convergence to the optimal policy cannot be guaranteed, but techniques proposed for state-space reduction and rapid resolution of undetermined policies should render many problems tractable. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Pattern Classification Based on Fuzzy Relations

    Page(s): 61 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (729 KB)  

    A method of classifying patterns using fuzzy relations is described. To start with, we give a suitable value of the measure of subjective similarity to each pair of patterns that is taken from the population of patterns to be classified. Then a similitude between any two patterns is calculated by using the composition of a fuzzy relation. The similitude induces an equivalence relation. Consequently, we can classify the present population of the patterns into some classes by the equivalence relation. An experiment of the classification of portraits has been performed to test the method proposed here. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Information Rate and Capacity in a Crayfish Photoreceptor Nerve Channel

    Page(s): 67 - 77
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1885 KB)  

    The theoretical basis of our experimental approach to information rate and capacity in a crayfish photoreceptor nerve channel is that used by Shannon [16]. Dispersion curves of conduction times were studied for pulses following short, medium, and long intervals. Although the means were equal (2.6 ms), the standard deviation in the case of pulses following short intervals was larger (0.29 ms) than for medium or long intervals (0.18 and 0.21 ms, respectively). A statistical description of nerve-fiber noise was found and used to compute the information rates (¿ = 280, 140, and 80 bit/s) for various light intensities. By maximizing ¿ over all possible input interval distributions, the channel capacity was calculated to be 360 bit/s. Extending the channel to include the entire system defined from light stimulus to probabilistic behavioral output, the overall mutual information rate was estimated to be 0.04 bit/s, the discrepancy between this overall behavioral rate and the capacity of the nerve channel is noted. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Choosing Among Alternative Complex Systems When Input Characteristics Are Uncertain

    Page(s): 77 - 82
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1021 KB)  

    Planning for economic and social purposes often requires choosing among alternative proposed systems to fulfill particular needs. In order to make such choices, planners or decision makers must be able to predict and evaluate the performance of each alternative system. For complex systems, methods are often available for doing this when system inputs, such as system user characteristics, can be specified deterministically. The more general situation, of course, is that input characteristics are not known with certainty, but may be described by probability distributions. It is the latter case that is discussed here. A Bayesian method for choosing among alternative systems when input characteristics are uncertain is presented. The method involves generating ``sample best choices'' among alternative systems. This is accomplished by selecting random input values, converting these to sample outputs for each system, and determining the sample best choice on the basis of the sample output values. The random input values are drawn from a probability distribution that encodes the uncertain state of information on inputs. The sample best choices are viewed as random samples of a multinomial random process whose parameters are also not known with certainty. The generation of random sample choices improves the state of knowledge of the uncertain multinomial parameters and permits a better decision. An optimal sampling policy may be found by executing a dynamic programming computation that balances the cost of sampling against the expected gains from improving the state of information. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Full text access may be available. Click article title to sign in or learn about subscription options.
  • Comments on ``An Adaptive Pattern Classification System''

    Page(s): 83 - 84
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (479 KB)  

    The results of the above paper,1 concerning a simulation study of an adaptive pattern classification procedure using a mean-square error performance criterion and using an estimated Bayes rule procedure, are compared with theoretical solutions obtained by using an exact Bayes rule procedure. An inherent defect of the mean-square error criterion is also pointed out, and a comparison between a system using this criterion and two other systems is made. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On Barron's Self-Organizing Control

    Page(s): 84 - 86
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB)  

    Self-organizing control (SOC) is analyzed as a conventional controller and the evolution of adaptive SOC from a simple linear system is shown. The development intentionally avoids any reference to the bionics concepts which Barron uses to describe his system. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Training Algorithm for Systems Described by Stochastic Transition Matrices

    Page(s): 86 - 87
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (405 KB)  

    Stochastic transition matrices are a convenient means for describing the behavior of adaptive and learning systems. Several systems which utilize these matrices and associated reinforcement (reward and punishment) techniques have been reported. A training algorithm is described which has been applied to a learning system described by stochastic transition matrices in which the environment was unknown a priori and nonstationary. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On Obtaining Separating Hyperplanes via Linear Programming

    Page(s): 87 - 88
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (361 KB)  

    A linear programming method for obtaining separating hyperplanes is discussed. Depending upon the objective function, the algorithm will accept any separating hyperplane or one which satisfies a minimum distance criterion. Application to inconsistent, i.e., linearly nonseparable, systems is considered. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An Iterative Method for Computation of Generalized Inverse and Matrix Rank

    Page(s): 89 - 90
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (332 KB)  

    A method for computing the generalized inverse A+ and the associated projections AA+ and A+A for any matrix A is developed It is also shown that the trace of a sequence of approximations to AA+ (or A+A) converges to the rank of A. Finally, examples are given showing the computation of the generalized inverse and rank. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Two Algorithms for Multiple-View Binary Pattern Reconstruction

    Page(s): 90 - 94
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (845 KB)  

    The problem of reconstructing binary patterns from their shadows or projections is treated. Two algorithms are formulated. For the two-view case, both algorithms give a perfect reconstruction if and only if the pattern is two-view unambiguous. It is also shown that n views are sufficient, but not necessary, to reconstruct any n × n binary pattern. Experimental results for the four-view reconstruction of 25 × 25 binary patterns indicate that one of the algorithms has good convergency behavior. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Book Reviews [8 books reviews]

    Save to Project icon | Request Permissions | PDF file iconPDF (1430 KB)  
    Freely Available from IEEE
  • Contributors

    Page(s): 100 - 103
    Save to Project icon | Request Permissions | PDF file iconPDF (3075 KB)  
    Freely Available from IEEE