Polynomial cellular neural networks for implementing the game of life

被引：0
|
作者：
Pazienza, Giovanni Egidio [1 ]
Gomez-Ramirez, Eduardo [2 ]
Vilasis-Cardona, Xavier [3 ]
机构：
[1] Univ Ramon Llull, GRSI, Quatre Camins 2, Barcelona 08022, Spain
[2] La Salle Univ, Posgrad Invest, LIDETEA, Mexico City 06140, DF, Mexico
[3] Univ Ramon Lull, Engn & Arquitect La Salle, LIFAELS, Barcelona 08022, Spain
来源：
ARTIFICIAL NEURAL NETWORKS - ICANN 2007, PT 1, PROCEEDINGS | 2007年 / 4668卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
One-layer space-invariant Cellular Neural Networks (CNNs) are widely appreciated for their simplicity and versatility; however, such structures are not able to solve non-linearly separable problems. In this paper we show that a polynomial CNN - that has with a direct VLSI implementation - is capable of dealing with the 'Game of Life', a Cellular Automaton with the same computational complexity as a Turing machine. Furthermore, we describe a simple design algorithm that allows to convert the rules of a Cellular Automaton into the weights of a polynomial CNN.
引用
收藏
页码：914 / +
页数：3
相关论文
共 50 条
  • [1] The game of life using polynomial discrete time cellular neural networks
    Gornez-Ramirez, Eduardo
    Pazienza, Giovanni Egidio
    ANALYSIS AND DESIGN OF INTELLIGENT SYSTEMS USING SOFT COMPUTING TECHNIQUES, 2007, 41 : 719 - +
  • [2] On stability of cellular neural networks with polynomial interactions
    Corinto, Fernando
    Gilli, Marco
    International Journal of Neural Systems, 2003, 13 (06) : 379 - 385
  • [3] Automatic Implementation of Totalistic Cellular Automata Through Polynomial Cellular Neural Networks
    Arista-Jalife, Antonio
    Gomez-Ramirez, Eduardo
    Pazienza, Giovanni E.
    PROCEEDINGS OF THE 2013 IEEE WORKSHOP ON HYBRID INTELLIGENT MODELS AND APPLICATIONS (HIMA), 2013, : 19 - 26
  • [4] Application of polynomial cellular neural networks in diagnosis of astrometric chromaticity
    Cancelliere, R.
    Gai, M.
    Slavova, A.
    APPLIED MATHEMATICAL MODELLING, 2010, 34 (12) : 4243 - 4252
  • [5] Learning in Polynomial Cellular Neural Networks using Quadratic Programming
    Gomez-Ramirez, E.
    Rubi-Velez, A.
    Pazienza, G. E.
    2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010, 2010,
  • [6] IMPLEMENTING POLYNOMIAL EXPRESSIONS BY MEANS OF RECIPROCAL-FUNCTION-BASED NEURAL NETWORKS
    Majewski, Jaroslaw
    Wojtyna, Ryszard
    SPA 2011: SIGNAL PROCESSING ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS CONFERENCE PROCEEDINGS, 2011, : 22 - 26
  • [7] It's Hard for Neural Networks to Learn the Game of Life
    Springer, Jacob M.
    Kenyon, Garrett T.
    2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2021,
  • [8] Computing the Weights of Polynomial Cellular Neural Networks Using Quadratic Programming
    Rubi-Velez, Anna
    Gomez-Ramirez, Eduardo
    Pazienza, Giovanni E.
    PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, PROCEEDINGS, 2009, 5856 : 645 - +
  • [9] Polynomial Discrete Time Cellular Neural Networks to solve the XOR problem
    Gomez-Ramirez, Eduardo
    Pazienza, Giovanni Egidio
    Vilasis-Cardona, Xavier
    PROCEEDINGS OF THE 2006 10TH IEEE INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS, 2006, : 23 - +
  • [10] Doubly periodic traveling waves in cellular neural networks with polynomial reactions
    Lin, Jian Jhong
    Cheng, Sui Sun
    NEUROCOMPUTING, 2011, 74 (07) : 1083 - 1094
12345