A Neural Abstract Machine
Egon Börger, Diego Sona · Zenodo (CERN European Organization for Nuclear Research) · 2001
Abstract: In an attempt to capture the fundamental features that are common to neural networks, we define a parameterized Neural Abstract Machine (NAM) in such a way that the major neural networks in the literature can be described as natural extensions or refinements of the NAM. We illustrate the refinement for feedforward networks with back-propagation training. The NAM provides a platform and programming language independent basis for a comparative mathematical and experimental analysis and evaluation of different implementations of neural networks. We concentrate our interfaces for the other NAM components.