Information theory method for flexible network synthesis

We introduce a novel approach to extend flexibility of combinational multi-level networks synthesis based on information-theoretical measure (ITM). This problem is related to optimization for combinational multi-level networks, artificial evolution and machine learning in circuitry design. Using ITMs, we verify not only that an evolved network achieves the target functionality, but also that this network can be corrected in a simple regular way to achieve it. We demonstrate experimental results by evolutionary strategy on gate-level network design: effectiveness in evolved valid networks increases dozens of times