Abstract
Diagnosability and syndrome decoding of a self-diagnosis model is studied with a conditional fault set. The conditional fault set is a fault set which is induced under such a condition that some subset of units are faulty (or fault-free).
The diagnosability defined on the model is generalized to include such information as (1) the maximum number of units to be identified as faulty; (2) the maximum number of units to be identified as fault-free; and (3) the maximum number of units whose states are definitely identified, when the upper bound on the number of faulty units is assumed.
Furthermore, we discuss the problem of finding minimal fault set. This problem is formulated in mathematical programming with the conditional fault set. A syndrome decoding algorithm is also presented which uses the conditional fault set in a similar manner to Hamming distance used in syndrome decoding of error-correcting codes.
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Ishida, Y., Adachi, N. & Tokumaru, H. An analysis of self-diagnosis model by conditional fault set. International Journal of Computer and Information Sciences 14, 243–259 (1985). https://doi.org/10.1007/BF00987037
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DOI: https://doi.org/10.1007/BF00987037