Though striking progress is occuring in the extraction of networks using a range of experimental data[8], [9], knowledge of signaling networks remains predominantly at the level of topology rather than detailed knowledge of the rate constants and non-linear message passing which occurs in the networks.
The latter is a technique for speeding up the standard belief propagation combining three techniques: the linear time message updates, the bipartite graph message passing schedule by computing messages "in place", and the multigrid method for performing BP in a coarse-to-fine manner.
What's in is the process of creation and it starts with an invocation grown from that audience suggestion, without a stated, linear, "on message" end point.
We can mark these no linear correlation messages as Gi,j = (x1, x2, …, x l ) N (shown in Figure 3d).
Case 2. in(i) = 1, out(i) > 1, the outgoing messages are linear correlation of incoming message (shown in Figure 3b).
Historically, communication theorists have described the concept of communication as the linear journey a message takes from its source to its destination [ 14].
With a sufficient number of linear combinations of messages, it is possible to recover all the messages.
Case 4. in(i) > 1, out(i) > 1, the outgoing messages are not linear correlation of incoming messages.
Each BS then performs linear combinations of messages intended for users applying the same pilot sequence.
In phase 1, based on the idea of computation coding [40], we recover a linear combination of messages.
