Group Testing with Multiple Inhibitor Sets and Error-Tolerant and Its Decoding Algorithms

In this article, we advance a new group testing model [Formula: see text] with multiple inhibitor sets and error-tolerant and propose decoding algorithms for it to identify all its positives by using [Formula: see text]-disjunct matrix. The decoding complexity for it is [Formula: see text], where [Formula: see text]. Moreover, we extend this new group testing to threshold group testing and give the threshold group testing model [Formula: see text] with multiple inhibitor sets and error-tolerant. By using [Formula: see text]-disjunct matrix, we propose its decoding algorithms for gap g = 0 and g > 0, respectively. Finally, we point out that the new group testing is the natural generalization for the clone model.