AN ANALYSIS OF NEURAL NETWORKS AS SIMULATORS AND EMULATORS

Recent advances in artificial neural networks (ANNs) have led to the design and construction of neuroarchitectures as simulator and emulators of a variety of problems in science and engineering. Such problems include pattern recognition, prediction, optimization, associative memory, and control of dynamic systems. This paper offers an analytical overview of the most successful design, implementation, and application of neuroarchitectures as neurosimulators and neuroemulators. It also outlines historical notes on the formulation of basic biological neuron, artificial computational models, network architectures, and learning processes of the most common ANN; describes and analyzes neurosimulation on parallel architecture both in software and hardware (neurohardware); presents the simulation of ANNs on parallel architectures; gives a brief introduction of ANNs in vector microprocessor systems; and presents ANNs in terms of the "new technologies". Specifically, it discusses cellular computing, cellular neural networks (CNNs), a new proposition for unsupervised neural networks (UNNs), and pulse coupled neural networks (PCNNs).

[1]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Brian Kingsbury,et al.  Spert-II: A Vector Microprocessor System , 1996, Computer.

[3]  Lance M. Optican,et al.  Temporal Codes for Colors, Patterns, and Memories , 1994 .

[4]  Reinhard Eckhorn,et al.  A Model for Feature Linking via Correlated Neural Activity , 1990 .

[5]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[6]  Fausto Sargeni,et al.  An improved architecture for the interconnections in a multi-chip CNN system , 1998, ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187).

[7]  EckhornR.,et al.  Feature linking via synchronization among distributed assemblies , 1990 .

[8]  W S McCulloch,et al.  A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.

[9]  B. Mirzai,et al.  Robust CNN templates: theory and simulations , 1996, 1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96).

[10]  John L. Johnson,et al.  Globally stable saturable learning laws , 1991, Neural Networks.

[11]  J. L. Johnson.  Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images. , 1994, Applied optics.

[12]  Idan Segev,et al.  Compartmental models of complex neurons , 1989 .

[13]  Moshe Sipper.  Computing with cellular automata: Three cases for nonuniformity , 1998 .

[14]  Gerald Sommer,et al.  Pattern Recognition by Self-Organizing Neural Networks , 1994 .

[15]  Moshe Sipper,et al.  Evolution of Parallel Cellular Machines: The Cellular Programming Approach , 1997 .

[16]  R. Palmer,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[17]  L. Fortuna,et al.  Autowaves for motion control: a CNN approach , 1998, ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187).

[18]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[19]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[20]  Christof Koch,et al.  Modeling the mammalian visual system , 1989 .

[21]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[22]  George S. Moschytz,et al.  Learning algorithms for cellular neural networks , 1998, ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187).

[23]  Benjamin W. Wah,et al.  Global Optimization for Neural Network Training , 1996, Computer.

[24]  Jeffery Johnson,et al.  Pulse coupled neural networks for image processing , 1995, Proceedings IEEE Southeastcon '95. Visualize the Future.

[25]  John L. Johnson.  Pulse-coupled neural networks , 1994, Defense + Commercial Sensing.

[26]  J. L. Johnson,et al.  Observation of periodic waves in a pulse-coupled neural network. , 1993, Optics letters.