MONNET: a software system for modular neural networks based on object passing

摘要

Modular neural networks integrate several neural networks and possibly standard processing methods. Tackling such models is a challenge, since various modules have to be combined, either sequentially or in parallel, and the simulations are time critical in many cases. For this, specific tools are prerequisite that are both flexible and efficient. We have developed the MONNET software system that supports the investigation of complex modular models. The design of MONNET is based on the object oriented paradigm, the environment is C$PLU$PLU@/UNIX. The basic concepts are dynamic modularity, object passing, scalability, reusability, and extensibility. MONNET features flexible and compact definition of complex simulations, and minimal overhead in order to run computationally demanding simulations efficiently.