Coupling and Lumping Finite-Size Linear System Realizations of Componentized Neural Networks

We present here a system morphism methodology to give insight into the lumping process of networks of linear systems. Lumping networks allows reducing the number of components and states to obtain simulatable models. Such lumped networks can be connected together through their input/output interfaces, using an engineering approach componentizing and lumping the network. This opens interesting perspectives for analyzing real networks at computational level (computing units of computers, simulations running on these computing units, models of neural networks based on a finite number of recording electrodes, etc.). In particular, the transposition of our results to brain modeling and simulation is discussed.