Communicating sequential processes
Communicating sequential processes
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The concurrent C programming language
The concurrent C programming language
Analog VLSI and neural systems
Analog VLSI and neural systems
Concurrent object-oriented programming
Communications of the ACM
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Advances in neural information processing systems 2
C++ primer (2nd ed.)
The C++ programming language (2nd ed.)
The C++ programming language (2nd ed.)
Distributed processes: a concurrent programming concept
Communications of the ACM
Object-Oriented Software Construction
Object-Oriented Software Construction
DARPA Neural Network Stdy
An object-relational neural network database type
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
NeuroOracle: Integration of Neural Networks into an Object-Relational Database System
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
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The analysis of complex neural network models via analytical techniques is often quite difficult due to the large numbers of components involved and the nonlinearities associated with these components. The authors present a framework for simulating neural networks as discrete event nonlinear dynamical systems. This includes neural network models whose components are described by continuous-time differential equations or by discrete-time difference equations. Specifically, the authors consider the design and construction of a concurrent object-oriented discrete event simulation environment for neural networks. The use of an object-oriented language provides the data abstraction facilities necessary to support modification and extension of the simulation system at a high level of abstraction. Furthermore, the ability to specify concurrent processing supports execution on parallel architectures. The use of this system is demonstrated by simulating a specific neural network model on a general-purpose parallel computer.