Two architectures implementing feed-forward completely connected neural nets

Feedforward completely-connected neural nets represent the most general scheme of loopless ANNs (artificial neural networks). Two architectures are presented. The second one (unfolded) presents a higher throughput (a higher number of shorter W-SRs) but a lower regularity (two different PEs, or processing elements); the first one (folded) presents a lower number of PEs (although more complex) and a higher regularity in the output signals ordered on the same output line from n₀ to n_N