Format allows interchanging neural models as well as documentation, store and manipulating them independently from the simulation system that produced it. We propose to use XML notation for full description of neural models, including data dictionary, properties of training sample, preprocessing methods, details of network structure and parameters, method for network output interpretation. The first version of DTD for neural model description language is developed. A model description structure, contents of main issues in XML document and example of software structure for handling files with neural model description are presented. Within the last decade artificial neural networks became a wide used technique for solving variety pattern recognition problems.
Today there is known huge amount of software concerning with neural networks simulation.
But in our opinion there is the problem of low integration between simulation systems that have such consequence as absence of unified form to describe of an arbitrary neural network model independently from system that produced it. The reason for this is that the field of artificial neural networks is evolved independently in and among many scientific communities such as neurobiology, mathematics and applied statistics, artificial intelligent and pattern recognition. As a result, a variegated terminology and synonymic nomenclature was developed. One of possible ways to raise effectiveness of neural network application is introducing a unified format for description of neural network models. The problem of development of unified format is closely connected to the investigation of standards for the description of various neural network model components.