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ICNN'97 FINAL PAPER LIST


LM: LEARNING & MEMORY

Oral Sessions: LM1, LM2, LM3, LM4, LM5 Poster Session: LMP2


Session Chairs:

LM1 Mon (AM) Jianchiang Mao, IBM Almaden Research Center

LM2 Mon (PM) Irwin Sandberg, University of Texas Austin

LM3 Tues (AM) Francesco Palmieri, Univ. Degli Studi Federico II di Napoli

LM4 Tues (PM) Joachim Utans, London Business School

LM5 Wed (AM) Anthony Zaknich, Univ. of Western Australia


SESSION LM1: Monday, June 9, 1997; 10:50 - 12:30 (Return to Top)


ICNN97 Learning & Memory Session: LM1A Paper Number: 169 Oral

Uniform approximation and gamma networks

Irwin W. Sandberg and Lilian Xu

Keywords: gamma network Uniform approximation nonlinear input-output maps

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ICNN97 Learning & Memory Session: LM1B Paper Number: 419 Oral

Asymptotical analysis of modular neural network

Lin-Cheng Wang, Nasser M. Nasrabadi and Sandor Der

Keywords: modular neural network data representation asymptotical performance

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ICNN97 Learning & Memory Session: LM1C Paper Number: 422 Oral

Recognition algorithm using evolutionary learning on the random neural networks

Jose Aguilar and Adriana Colmenares

Keywords: evolutionary learning random neural networks pattern recognition

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ICNN97 Learning & Memory Session: LM1D Paper Number: 141 Oral

Dynamics of distance between patterns for higher order random neural networks

Hiromi Miyajima and Shuji Yatsuki

Keywords: hugher order random neural network dynamical properties dynamics of distance

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ICNN97 Learning & Memory Session: LM1E Paper Number: 414 Oral

Principal components via cascades of block-layers

Francesco Palmieri and Michele Corvino

Keywords: principal components cascades of block-layers constarained connectivity

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SESSION LM2: Monday, June 9, 1997; 13:50 - 15:50 PM (Return to Top)


ICNN97 Learning & Memory Session: LM2A Paper Number: 383 Oral

Bayesian geometric theory of learning algorithms

Huaiyu Zhu

Keywords: bayesian geometric theory learning algorithms objective evaluation

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ICNN97 Learning & Memory Session: LM2B Paper Number: 251 Oral

Note on effective number of parameters in nonlinear learning systems

Jianchang Mao and Anil Jain

Keywords: nonlinear learning system effective number of parameters feedforward neural network

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ICNN97 Learning & Memory Session: LM2C Paper Number: 413 Oral

New bounds for correct generalization

D. Mattera and F. Palmieri

Keywords: correct generalization number of training examples neural network architecture

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ICNN97 Learning & Memory Session: LM2D Paper Number: 48 Oral

D-Entropy minimization

Ryotaro Kamimura

Keywords: D-entropy information maximization Renyi entropy Shannon entropy

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ICNN97 Learning & Memory Session: LM2E Paper Number: 438 Oral

Projection pursuit and the solvability condition applied to constructive learning

Fernando J. Von Zuben and Marcio L. de Andrade Netto

Keywords: projection pursuit solvability condition constructive learning

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ICNN97 Learning & Memory Session: LM2F Paper Number: 569 Oral

The generalization capabilities of ARTMAP

Gregory L. Heileman, Michael Georgiopoulos, Michael J. Healy and Stephen J. Verzi

Keywords: generalization capability ARTMAP number of training examples

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SESSION LM3: Tuesday, June 10, 1997; 10:00 - 12:00 (Return to Top)


ICNN97 Learning & Memory Session: LM3A Paper Number: 167 Oral

Automatic learning rate optimization by higher-order derivatives

Xiao-Hu Yu and Li-Qun Xu

Keywords: learning rate optimization higher-order derivatives backpropagation learning

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ICNN97 Learning & Memory Session: LM3B Paper Number: 406 Oral

Improved back propagation training algorithm using conic section functions

Tulay Yildirim and John S. Marsland

Keywords: back propagation conic section functions Radial basis funtion

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ICNN97 Learning & Memory Session: LM3C Paper Number: 96 Oral

Comparing parameterless learning rate adaptation methods

M. Moreira and E. Fiesler

Keywords: parematerless learning rate backpropagation adaptive learning rate

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ICNN97 Learning & Memory Session: LM3D Paper Number: 339 Oral

Optimal stopped training via algebraic on-line estimation of the expected test-set error

Joachim Utans

Keywords: optimal stopped training algebraic on-line estimation expected test-set error

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ICNN97 Learning & Memory Session: LM3E Paper Number: 97 Oral

Weight evolution algorithm with dynamic offset range

S. C. Ng, S. H. Leung and A. Luk

Keywords: multi-layered neural network back propagation weight evolution

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ICNN97 Learning & Memory Session: LM3F Paper Number: 400 Oral

Incorporating state space constraints into a neural network

Daryl H. Graf

Keywords: state space constraints continuous neural network manifold learning

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SESSION LM4: Tuesday, June 10, 1997; 14:40 - 16:00 PM (Return to Top)


ICNN97 Learning & Memory Session: LM4A Paper Number: 551 Oral

A structural learning algorithm for multi-layered neural networks

Manabu Kotani, Akihiro Kajiki and Kenzo Akazawa

Keywords: structural learning multi-layered neural network pruning algorithm

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ICNN97 Learning & Memory Session: LM4B Paper Number: 618 Oral

An improved expand-and-truncate learning

A. Yamamoto and T. Saito

Keywords: expand-and-truncate learning binary-to-binary mapping number of hidden units

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ICNN97 Learning & Memory Session: LM4C Paper Number: 336 Oral

a vector quantisation reduction method for the probabilistic neural network

Anthony Zaknich

Keywords: vector quantisation probabilistic neural network regression

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SESSION LM5: Wednesday, June 11, 1997; 10:00 - 12:00 AM (Return to Top)


ICNN97 Learning & Memory Session: LM5A Paper Number: 636 Oral

Robust adaptive identification of dynamic systems by neural networks

James Ting-Ho Lo

Keywords: dynamic systems adaptive identification on-line weight adjustment

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ICNN97 Learning & Memory Session: LM5B Paper Number: 521 Oral

Fibre bundles and receptive neural fields

S. Puechmorel

Keywords: fiber bundles receptive neural fields membership function

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ICNN97 Learning & Memory Session: LM5C Paper Number: 105 Oral

Fast binary cellular neural networks

Iztok Fajfar

Keywords: cellular neural network analog transient parameter optimization

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ICNN97 Learning & Memory Session: LM5D Paper Number: 316 Oral

Associative memory of weakly connected oscillators

Frank Hoppensteadt and Eugene Izhikevich

Keywords: multiple andronov-hopf bifurcations weakly connected neural networks Cohen-Grossberg convergence limit cycle attractors

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ICNN97 Learning & Memory Session: LM5E Paper Number: 372 Oral

Input-to-state (ISS) analysis for dynamic neural networks

Edgar N. Sanchez and Jose P. Perez

Keywords: neural network dynamics intelligent control stability ISS analysis

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SESSION LMP2: Wednesday, June 11, 1997; 16:00 - 18:20 PM (Return to Top)


ICNN97 Learning & Memory Session: LMP2 Paper Number: 110 Poster

Simultaneous information maximization and minimization

Ryotaro Kamimura

Keywords: information maximization information minimization internal representation

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ICNN97 Learning & Memory Session: LMP2 Paper Number: 535 Poster

Hybrid learning algorithm with low input-to-output mapping sensitivity for iterated time-series prediction

So-Young Jeong, Minho Lee and Soo-Young Lee

Keywords: hybrid learning input-to-output mapping sensitivity iterated time-series prediction

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ICNN97 Learning & Memory Session: LMP2 Paper Number: 23 Poster

On viewing the transform performed by a hidden layer in a feedforward ANN as a complex mobius mapping

Adriana Dumitras and Vasile Lazarescu

Keywords: hidden layer feedforward network mobius mapping Hinton diagram

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ICNN97 Learning & Memory Session: LMP2 Paper Number: 21 Poster

An upper bound on the node complexity of depth-2 multilayer perceptrons

Masahiko Arai

Keywords: node complexity multilayer perceptron hidden units

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ICNN97 Learning & Memory Session: LMP2 Paper Number: 548 Poster

Improved sufficient convergence condition for the discrete-time cellular neural networks

Sungjun Park and Soo-Ik Chae

Keywords: convergence condition discrete-time cellular neural network positive semi-definite constraint

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ICNN97 Learning & Memory Session: LMP2 Paper Number: 455 Poster

Beyond weights adaptation: a new neuron model with trainable activation function and its supervised learning

Youshou Wu, Mingsheng Zhao and Xiaoqing Ding

Keywords: weights adaptation trainable activation functions supervised learning


Web Site Author: Mary Lou Padgett (m.padgett@ieee.org) (Return to Top)
URL: http://www.mindspring.com/~pci-inc/ICNN97/paperlm.htm
(Last Modified: 15-May-1997)