We define the class of conjunctive queries in relational data bases, and the generalized join operator on relations.The generalized join plays an important part in answering conjunctive queries, and it can be implemented using matrix multiplication.It is shown that while answering conjunctive queries is NP complete (general queries are PSPACE complete), one can find an implementation that is within a constant of optimal.The main lemma used to show this is that each conjunctive query has a unique minimal equivalent query (much like minimal finite automata).

F m i n ( x ) = 1 -exp [-exp [a1(~ -~1 ) l I where 1 n F(u1) =andSince, in general, the underlying initial distribution is unknown, the parameters u,, a,, u1, and a1 have to be estimated from sample values. This usually proceeds as follows. A total of k = nN samples from a given distribution are taken and divided into 'N groups of n samples per group.If it is desired to estimate u, and a,, in each of the N groups the largest of the n samples is chosen. From these N largest values, it can be shown that a variety of procedures exist from which u, and a, can be estimated. A method for obtaining maximun-likelihood estimates of u, and a, is described in [9] , along with various other estimation techniques.If it is desired t o estimate u1 and a1, a similar procedure using minimum instead of maximum values can be performed. REFERENCESD. J. Gooding, "Performance monitor techniques for digital receivers based on extrapolation of error rate," ZEEE Trans.

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