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[Proceedings 1992] IJCNN International Joint Conference on Neural Networks

7-11 June 1992

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Displaying Results 1 - 25 of 138
  • A neural based approach of constraints satisfaction problem

    Publication Year: 1992, Page(s):588 - 593 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (319 KB)

    The authors recall the constraint programming approach to solving a constraint-satisfaction problem, and show that for each problem which can be described by this approach a neural network can be designed which solves the problem. They give an application of this method for solving a task assignment problem and compare the results with those which are obtained by other approaches. Because this net... View full abstract»

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  • High-order attention-shifting networks for relational structure matching

    Publication Year: 1992, Page(s):499 - 506 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB)

    The Hopfield-Tank optimization network has been applied to the model-image matching problem in computer vision using a graph matching formulation. However, the network has been criticized for unreliable convergence to feasible solutions and for poor solution quality, and the graph matching formulation is unable to represent matching problems with multiple object types, and multiple relations, and ... View full abstract»

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  • Optimization methodology of ANN backpropagation nets

    Publication Year: 1992, Page(s):507 - 512 vol.4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (428 KB)

    An optimization methodology for artificial neural networks with backpropagation nets is proposed. The pattern classification capability of backpropagation nets is first employed to identify feasible and infeasible regions (classes) of the optimization problems. The identified class boundaries enclose multi-dimensional spaces within which optimization constraints were satisfied. After adopting diff... View full abstract»

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  • Optimizing neural networks for playing tic-tac-toe

    Publication Year: 1992, Page(s):513 - 518 vol.4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (396 KB)

    A neural network approach for playing the game tic-tac-toe is introduced. The problem is considered as a combinatorial optimization problem aiming to maximize the value of a heuristic evaluation function. The proposed design guarantees a feasible solution, including in the cases where a winning move is never missed and a losing position is always prevented, if possible. The design has been impleme... View full abstract»

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  • Artificial neural networks for distributed adaptive routing on dynamic topology networks

    Publication Year: 1992, Page(s):468 - 473 vol.4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (500 KB)

    In considering distributed adaptive routing schemes for large networks with dynamic topology, the need for an unconventional shortest path algorithm arises from the excessive computation overhead associated with repeated path/distance calculations. The authors provide the design specifics of such an algorithm, and establish its performance characteristics through rigorous analysis and simulation. ... View full abstract»

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  • Neural net model of batch processes and optimization based on an extended genetic algorithm

    Publication Year: 1992, Page(s):519 - 524 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (384 KB)

    The authors investigated the use of neural networks for modeling batch processes. A cascade neural network offered a solution from the experimental data which did not require the detailed knowledge of process kinetics. An extended genetic algorithm was adopted to generate the optimal trajectory for improving the desired process performance. The rule-inducer genetic algorithm is proposed for dynami... View full abstract»

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  • Genetic breeding of control parameters for the Hopfield/Tank neural net

    Publication Year: 1992, Page(s):618 - 623 vol.4
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (356 KB)

    The authors show how genetic algorithms may be used in conjunction with the Hopfield/Tank neural net by breeding an effective set of control parameters in the parameter sub-space to be used by the artificial neural network. They briefly consider the standard Hopfield/Tank neural net followed by a discussion of the genetic algorithm used with this network. Some of the more important operators used ... View full abstract»

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  • An approach to automatic test pattern generation using strictly digital neural networks

    Publication Year: 1992, Page(s):474 - 479 vol.4
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (252 KB)

    The authors present a parallel algorithm for finding a set of diagnostic patterns to test logic circuits using strictly digital neural networks (SDNNs). They use a new logic circuit called neural logic gate (NLG) to provide two logic functions, and obtain a preliminary set of test patterns. A circuit of the NLG is defined as intersecting sets of neurons with the k-out-of-n design... View full abstract»

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  • Optimization of neural network topology and information content using Boltzmann methods

    Publication Year: 1992, Page(s):594 - 599 vol.4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (200 KB)

    A method for optimizing networks that focuses on network topology and information content is presented. The authors have studied change in the network topology and its effects on information content dynamically during the optimization of the network. The changes in the network topology were achieved by altering the number of weights. The primary optimization was scaled by the conjugate gradient me... View full abstract»

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  • Convergence and stability study of Hopfield's neural network for linear programming

    Publication Year: 1992, Page(s):525 - 531 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (224 KB)

    Parameters that affect stability and convergence of the Hopfield model were identified by simulation. The Hopfield model used to solve optimization problems was defined by an analog electrical circuit. The authors illustrate that by introducing one additional amplifier a convergence with a good stability can be obtained. It is shown that convergence and stability can be obtained without oscillatio... View full abstract»

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  • Hopfield-type neural networks with fuzzy sets to gather the convergent speed

    Publication Year: 1992, Page(s):624 - 629 vol.4
    Cited by:  Papers (1)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (308 KB)

    To solve combinatorial optimization problems with Hopfield-type neural networks, the slope of the sigmoid function must be adjusted to a desirable narrow range. It was reported that the desirable range could be widened by changing the parameters of the energy function and the sigmoid function dynamically. Fuzzy parameters are introduced to perform scheduling of the networks. A fuzzy rule is propos... View full abstract»

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  • Learning 3D-shape perception with local linear maps

    Publication Year: 1992, Page(s):432 - 437 vol.4
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (436 KB)

    The authors consider the task of learning to extract 3D shape information about complex objects from monocular gray level pixel images. It is shown that this task can be efficiently solved by a network architecture of local linear maps. Very little preprocessing is necessary. No prior identification of salient object features or their image coordinates is required. The approach was demonstrated by... View full abstract»

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  • An estimation of parameters in an energy function used in a simulated annealing method

    Publication Year: 1992, Page(s):480 - 485 vol.4
    Cited by:  Papers (2)  |  Patents (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (368 KB)

    When a combinatorial optimization problem such as the traveling salesman problem is solved by a simulated annealing method, it is common to use an energy function that consists of two kinds of terms: a cost term which should be minimized and a constraint term which expresses constraints imposed on solutions. The author proposes a method for determining appropriate values of weights of constraint t... View full abstract»

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  • On the training strategies of neural networks for speech recognition

    Publication Year: 1992, Page(s):749 - 754 vol.4
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (408 KB)

    The authors investigate how to introduce invariant features to speech recognition neural networks using conventional back propagation (BP), K-neighbor interpolation training (KNIT) with a number of time-shifted examples (TSEs) of the same training sample. The TSEs are employed for training of a multilayer perceptron (MLP) and a time-delay neural network (TDNN) structure to enrich the training samp... View full abstract»

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  • Autogenerative nodal memory model (ANM)-an analysis of growth metrics

    Publication Year: 1992, Page(s):826 - 831 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (248 KB)

    The autogenerative nodal memory model (ANM) has been described in detail in the literature, and various experiments have been conducted to test the validity of the model. The authors describe how such a system evolves under certain input conditions. This analysis is part of the results obtained from the mathematical analysis that is currently being published. It gives insight on how the ANM system... View full abstract»

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  • Regression analysis of spectroscopic process data using a combined architecture of linear and nonlinear artificial neural networks

    Publication Year: 1992, Page(s):549 - 554 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (476 KB)

    The authors demonstrate that a combined architecture of linear and nonlinear artificial neural networks offers many advantages over the conventional multilayer feedforward networks and the conventional biased regression methods for the modeling of spectroscopic process data. This direct linear feedthrough (DLF) network is an especially useful tool for modeling process data when the true linear or ... View full abstract»

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  • Weight-space probability densities and convergence times for stochastic learning

    Publication Year: 1992, Page(s):158 - 164 vol.4
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (452 KB)

    The authors extend the theory of search dynamics for stochastic learning algorithms, address the time evolution of the weight-space probability density and the distribution of convergence times, with particular attention given to escape from local optima, and develop a theoretical framework that describes the evolution of the weight-space probability density. The primary results are exact predicti... View full abstract»

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  • A new approach to global optimization and its applications to neural networks

    Publication Year: 1992, Page(s):600 - 605 vol.4
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB)

    A new approach to global optimization that alternately rocks the landscape of the objective function and rolls the ball representing the current state of the variable down to the bottom of the nearest valley is presented. The degree of perturbation is determined by a parameter called rock level. The rock level decreases in the process. The ball gets rocked out of local minima and eventually settle... View full abstract»

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  • Parallel mean field annealing neural network for solving traveling salesman problem

    Publication Year: 1992, Page(s):532 - 536 vol.4
    Cited by:  Papers (1)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (220 KB)

    The authors propose a parallel mean field annealing (MFA) algorithm and a new energy function for finding traveling salesman optimal tours. The proposed parallel MFA neural network has the advantages of a simplified energy function, and that it converges more rapidly to an optimal solution. The experimental results showed that the parallel MFA and the new energy function can generate the optimal s... View full abstract»

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  • System optimization with artificial neural networks: parallel implementation using transputers

    Publication Year: 1992, Page(s):630 - 635 vol.4
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (340 KB)

    A neural network with a three-layer feedback topology for solving continuous optimization problems has been proposed. A parallel implementation of the proposed neural network is presented. The implementation described here uses a transputer system, which enables solving problems with several variables. Results from this implementation and comparisons with sequential implementation results are also... View full abstract»

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  • Multiresolution edge detection

    Publication Year: 1992, Page(s):438 - 443 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (496 KB)

    The neural network implementation of some commonly used edge detectors is reviewed and compared. Edge detection is scale-dependent. Edges are visible only over a range of scales. Multiple scale analysis of the input image is required to have a complete description of the edges. The authors propose a compact pyramidal multi-level neural net architecture for image representation at multiple spatial ... View full abstract»

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  • Neural network development for noise reduction in robust speech recognition

    Publication Year: 1992, Page(s):722 - 727 vol.4
    Cited by:  Papers (7)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (472 KB)

    Speech recognition systems with small and medium vocabulary are used as natural human interfaces in a variety of applications. To make such a system more robust, the development of a neural network based noise reduction module is described. Using standard feedforward networks, several topologies have been tested to learn about the properties of neural noise reduction. For the development of a suff... View full abstract»

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  • Neurodynamical model of collective brain

    Publication Year: 1992, Page(s):115 - 121 vol.4
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (388 KB)

    A dynamical system which mimics collective purposeful activities of a set of units of intelligence is introduced and discussed. A global control of the unit activities is replaced by the probabilistic correlations between them. These correlations are learned during a long term period of performing collective tasks, and are stored in the synaptic interconnections. The model is represented by a syst... View full abstract»

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  • Back propagation and forward propagation

    Publication Year: 1992, Page(s):486 - 491 vol.4
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (288 KB)

    The authors analyze the validity of the pessimistic views of M.L. Minsky and S.A. Papert (Perceptrons: An Intro. to Comput. Geom., MIT Press, Cambridge, MA, 1969) on the possibility of training multi-layer perceptrons. In particular, they show that it was possible, using the simplex algorithm of J.A. Nelder and R. Mead (Comput. Journ., vol.8, pp.308-13, 1965), to train these networks at the time o... View full abstract»

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  • A genetic approach to the truck backer upper problem and the inter-twined spiral problem

    Publication Year: 1992, Page(s):310 - 318 vol.4
    Cited by:  Papers (18)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (840 KB)

    The author describes a biologically motivated paradigm, genetic programming, which can solve a variety of problems. When genetic programming solves a problem, it produces a computer program that takes the state variables of the system as input and produces the actions required to solve the problem as output. Genetic programming is explained and applied to two well-known benchmark problems from the... View full abstract»

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