Mason.m uses mason's rule to simplify signal flow graphs. It takes a file describing the network and produces a symbolic equation relating a dependent output node to an independent input node.
The directory contains a comprehensive readme file and an example network file to experiment with. Mason's rule is traditionally used for control system analysis but has applications in microwave circuit design, filter design and many other areas.
(If you want to develop this code further, please find it here: https://github.com/robwalton/mason)
Thanks a lot for sharing. Very useful.
Very nice, thank you!
Hi, thanks for this submission. It's really great job.
Yet, I have a question. I'm using it to calculate gains for the graphs with positive feedback loops. at the calculation step I feed network with numeric coefficients (via num2str) and the call eval(Num)/eval(Den) to obtain numerical gain. But with positive feedback loops I always get negative denumerator. Is there a way how to handle positive feedback loop properly using Masons formula?
Very nice and clean code, thanks for making it accessible to anyone, it is a powerful tool!
The program is good, but too complex to understand.
We developed a simple way to solve this peoblem in our new submitted file signal_flow_graphz. Where the network description file is replaced by a connection matrix Q and an input Matrix P. The simultaneous equations of the linear system are expressed in a matrix form:
The solution is expressed by a simple MATLAB inversion command line:
Thus the calculation process is completely transparent to the user and eazier to debug or to modify. In signal_flos_graphz this command line is replaced by a function sigflow.m just for doing some check to matrices Q and P. Moreover, this method is valid to MIMO systems.
Simple to use, but very useful
Very nice. Just wondering if possible to contrustruct paths automatically by readling a state-flow diagram?
Added link to github copy
Update file in order to add BSD license and Mathwork's request.
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