Abstract
The expected values of the binary within a digital network have a number of uses in the design of these networks. These expected value signals may be obtained by computationally expensive Monte Carlo methods. Alternately, probabilistic models of digital network elements may be constructed to allow the calculation of expected value information far more efficiently. The treatment of combinational logic networks was carried out in [1]. Here we probabilistically model flip flops and develop an expected value analysis for simple digital feedback networks.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
