Expecting a wide use of neural network algorithms in the near future, our objective is to get a complete software development environment for programming and testing new applications. We intend to produce a high level language for neural network specification, as a part of such an environment.
The language we propose is characterized by a high degree of modularity, based on parameterizable data structures, with functionalities in the form of update methods attached to them. Composition rules of structures and methods enable to build, step by step, more complex structures from smaller ones previously defined. Objects are viewed as autonomous modules which are linked through plugs for communications. We particularly cared for the parallelization of methods running concurrently on different objects of the network. The syntax is largely related to those of the C and C++ languages.
This research work takes place in the Pygmalion ESPRIT II project 2059.
- Neural Network
- Hide Layer
- Neural Network Algorithm
- Composition Rule
- Autonomous Module
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Angéniol, B., Le Texier, J. Y., Mateu J. B. : SLOGAN : an object-oriented language for neural network specification. To appear in the Acts of the nEuro ’88 Conference at ESPCI Paris, June 1988
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© 1990 Springer-Verlag Berlin Heidelberg
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de La Croix Vaubois, G., Moulinoux, C., Derot, B. (1990). The N Programming Language. In: Soulié, F.F., Hérault, J. (eds) Neurocomputing. NATO ASI Series, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76153-9_10
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