Biomolecular nonlinear dynamic mechanisms as a foundation for human traits of information processing machine

A pseudo-biological paradigm in information processing launched by McCulloch and Pitts in the early 1940s has been advanced during the last decades. Different attempts were made based on these developments to design operational information processing devices capable of solving problems of high computational complexity.

[1]  Andrew Witkin,et al.  Reaction-diffusion textures , 1991, SIGGRAPH.

[2]  A. Winfree,et al.  Electrical turbulence in three-dimensional heart muscle. , 1994, Science.

[3]  N. Rambidi,et al.  Information-processing capabilities of chemical reaction–diffusion systems. 2: Finding paths in a labyrinth based on reaction–diffusion media , 1999 .

[4]  A. V. Maximychev,et al.  Molecular image-processing devices based on chemical reaction systems. 5: Processing images with several levels of brightness and some application potentialities , 1997 .

[5]  George F. Hepner,et al.  Application of an artificial neural network to landcover classification of thematic mapper imagery , 1990 .

[6]  N. G. Rambidi,et al.  Information‐processing capabilities of chemical reaction–diffusion systems. 1. Belousov–Zhabotinsky media in hydrogel matrices and on solid supports , 1998 .

[7]  M Conrad,et al.  The brain-machine disanalogy. , 1989, Bio Systems.

[8]  Sergei O. Kuznetsov,et al.  Image pre-processing by neuron-like algorithms , 1998 .

[9]  A. V. Maximychev,et al.  Molecular image‐processing devices based on chemical reaction systrems. 3: Some operational characteristics of excitable light‐sensitive media used for image processing , 1995 .

[10]  A. M. Turing,et al.  Computing Machinery and Intelligence , 1950, The Philosophy of Artificial Intelligence.

[11]  Walter C. Merrill,et al.  A real time neural net estimator of fatigue life , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[12]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[13]  A Hjelmfelt,et al.  Pattern Recognition in Coupled Chemical Kinetic Systems , 1993, Science.

[14]  J. Ross,et al.  Experiments on Pattern Recognition by Chemical Kinetics , 1995 .

[15]  N G Rambidi,et al.  Biomolecular computer: roots and promises. , 1997, Bio Systems.

[16]  Thomas Erneux,et al.  Propagation failure and multiple steady states in an array of diffusion coupled flow reactors , 1992 .

[17]  A. V. Maximychev,et al.  Molecular image‐processing devices based on chemical reaction systems. I: General principles for implementation , 1994 .

[18]  A Hjelmfelt,et al.  Pattern recognition, chaos, and multiplicity in neural networks of excitable systems. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[19]  N G Rambidi.  Biomolecular computing: from the brain-machine disanalogy to the brain-machine analogy. , 1994, Bio Systems.

[20]  Greg Turk,et al.  Generating textures on arbitrary surfaces using reaction-diffusion , 1991, SIGGRAPH.

[21]  I. Epstein.  Experimental and theoretical studies of coupled chemical oscillators , 1990 .

[22]  A. V. Maximychev,et al.  Molecular image‐processing devices based on chemical reaction systems. 6: Processing half‐tone images and neural network architecture of excitable media , 1997 .

[23]  Stephen Grossberg,et al.  Nonlinear neural networks: Principles, mechanisms, and architectures , 1988, Neural Networks.

[24]  McCormick,et al.  Breathing Spots in a Reaction-Diffusion System. , 1996, Physical review letters.

[25]  Sergei O. Kuznetsov,et al.  Neural networks with close nonlocal coupling for analyzing composite image , 1991, Neurocomputing.

[26]  A. Oosterlinck,et al.  Image enhancement and analysis with reaction-diffusion paradigm , 1990 .

[27]  L. Watson,et al.  Diffusion and wave propagation in cellular automaton models of excitable media , 1992 .

[28]  Hagberg,et al.  From labyrinthine patterns to spiral turbulence. , 1994, Physical review letters.

[29]  Michael Conrad,et al.  On design principles for a molecular computer , 1985, CACM.

[30]  C. Lin,et al.  Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing , 1989, Other Conferences.