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  • fifth neural network conference proceedings...

    The Proceedings of the Fifth Conference on Neural Networks and Parallel
    Distributed Processing at Indiana University-Purdue University at Fort Wayne,
    held April 9-11, 1992 are now available. They can be ordered ($9 + $1 U.S.
    mail cost; make checks payable to IPFW) from:

    Secretary, Department of Physics FAX: (219)481-6880
    Voice: (219)481-6306 OR 481-6157
    Indiana University Purdue University Fort Wayne
    email: proceedings@ipfwcvax.bitnet
    Fort Wayne, IN 46805-1499

    The following papers are included in the Proceedings of the Fifth Conference:


    Phil Best, Miami University, Processing of Spatial Information in the Brain
    William Frederick, Indiana-Purdue University, Introduction to Fuzzy Logic
    Helmut Heller and K. Schulten, University of Illinois, Parallel Distributed
    Computing for Molecular Dynamics: Simulation of Large Hetrogenous
    Systems on a Systolic Ring of Transputer
    Krzysztof J. Cios, University Of Toledo, An Algorithm Which Self-Generates
    Neural Network Architecture - Summary of Tutorial

    Biological and Cooperative Phenomena Optimization

    Ljubomir T. Citkusev & Ljubomir J. Buturovic, Boston University, Non-
    Derivative Network for Early Vision
    M.B. Khatri & P.G. Madhavan, Indiana-Purdue University, Indianapolis, ANN
    Simulation of the Place Cell Phenomenon Using Cue Size Ratio
    J. Wu, M. Penna, P.G. Madhavan, & L. Zheng, Purdue University at
    Indianapolis, Cognitive Map Building and Navigation
    J. Wu, C. Zhu, Michael A. Penna & S. Ochs, Purdue University at
    Indianapolis, Using the NADEL to Solve the Correspondence Problem
    Arun Jagota, SUNY-Buffalo, On the Computational Complexity of Analyzing
    a Hopfield-Clique Network

    Network Analysis

    M.R. Banan & K.D. Hjelmstad, University of Illinois at Urbana-Champaign,
    A Supervised Training Environment Based on Local Adaptation,
    Fuzzyness, and Simulation
    Pranab K. Das II & W.C. Schieve, University of Texas at Austin, Memory in
    Small Hopfield Neural Networks: Fixed Points, Limit Cycles and Chaos
    Arun Maskara & Andrew Noetzel, Polytechnic University, Forced Learning in
    Simple Recurrent Neural Networks
    Samir I. Sayegh, Indiana-Purdue University, Neural Networks Sequential vs
    Cumulative Update: An * Expansion
    D.A. Brown, P.L.N. Murthy, & L. Berke, The College of Wooster, Self-
    Adaptation in Backpropagation Networks Through Variable
    Decomposition and Output Set Decomposition
    Sandip Sen, University of Michigan, Noise Sensitivity in a Simple Classifier
    Xin Wang, University of Southern California, Complex Dynamics of Discrete-
    Time Neural Networks
    Zhenni Wang and Christine di Massimo, University of Newcastle, A Procedure
    for Determining the Canonical Structure of Multilayer Feedforward
    Neural Networks
    Srikanth Radhakrishnan and C, Koutsougeras, Tulane University, Pattern
    Classification Using the Hybrid Coulomb Energy Network


    K.D. Hooks, A. Malkani, & L. C. Rabelo, Ohio University, Application of
    Artificial Neural Networks in Quality Control Charts
    B.E. Stephens & P.G. Madhavan, Purdue University at Indianapolis, Simple
    Nonlinear Curve Fitting Using the Artificial Neural Network
    Nasser Ansari & Janusz A. Starzyk, Ohio University, Distance Field Approach
    to Handwritten Character Recognition
    Thomas L. Hemminger & Yoh-Han Pao, Case Western Reserve University, A
    Real-Time Neural-Net Computing Approach to the Detection and
    Classification of Underwater Acoustic Transients
    Seibert L. Murphy & Samir I. Sayegh, Indiana-Purdue University, Analysis of
    the Classification Performance of a Back Propagation Neural Network
    Designed for Acoustic Screening
    S. Keyvan, L. C. Rabelo, & A. Malkani, Ohio University, Nuclear Diagnostic
    Monitoring System Using Adaptive Resonance Theory