CDMA and TDMA based neural nets

One of the main problems in neural nets implementation is how to take the information from the processing units where it is generated to other processing units, in order for the net to carry on the computation and eventually yield a result. This problem is significant enough to influence the whole physical design, thus we find a wide choice of solutions. This paper's two proposals come from the rising field of wireless communications: CDMA and TDMA. The principles were established long ago, but they have acquired a renewed presence due to the rapidly increasing demand for mobile phones. We are going to see how CDMA and TDMA could apply to neural nets, by means of currently available technology, if we give up the concept "connection" between units and grasp the concept "messages" exchanged between them, to open the door to neural nets with higher number of processing units and flexible configuration.