This paper proposes new designs of double modular redundancy (DMR) when time-continuous data is provided as inputs. As this type of data tends slightly change over adjacent time periods, the proposed designs exploit this property by comparing consecutive outputs for reliable computing. The proposed designs are based on the difference between the two consecutive inputs/outputs, referred to as factor. These new designs are four one-factor and a single two-factor scheme. They overcome the negative feature of a previous design (referred to as self-voting) by which an uncontrollable output is encountered when input data is time-continuous and both primary inputs are not equal, i.e. in the presence of an error, the output remains at the same value prior to the occurrence of the error, so making it unsuitable for these types of applications. The proposed designs are evaluated in terms of the required decision hardware (to generate the output) and its accuracy using Cadence Genus Synthesis Solution on a 32 nm library; it is shown that the decision hardware of the two-factor scheme is more complex than for the one-factor schemes, yielding to a longer delay and higher power dissipation/area. Different data sets as well as a randomly generated data set are utilized in the evaluation. Simulation results show that the two-factor scheme provides the highest level of accuracy at the output as this is directly related to the complexity of the decision hardware:
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