Newsgroups: comp.parallel From: Pulin Subject: fifth neural network conference proceedings... Organization: Clemson University Date: Mon, 29 Nov 1993 12:47:51 EST 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: Tutorials 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 System 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 Applications 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