Boolean function

Abstract: The use of error-correcting codes for tight control of the peak-to-mean envelope power ratio (PMEPR) in orthogonal frequency-division multiplexing (OFDM) transmission is considered in this correspondence. By generalizing a result by Paterson, it is shown that each q-phase (q is even) sequence of length 2m lies in a complementary set of size 2k+1, where k is a nonnegative integer that can be easily determined from the generalized Boolean function associated with the sequence. For small k this result provides a reasonably tight bound for the PMEPR of q-phase sequences of length 2 m. A new 2h-ary generalization of the classical Reed-Muller code is then used together with the result on complementary sets to derive flexible OFDM coding schemes with low PMEPR. These codes include the codes developed by Davis and Jedwab as a special case. In certain situations the codes in the present correspondence are similar to Paterson's code constructions and often outperform them

Abstract: A multilevel logic optimization technique is presented that is a generalization of redundancy removal and Boolean resubstitution. The network is optimized through iterative addition and deletion of redundant connections. With the use of the connection fault model, the problem of identifying connections that can be made without affecting the network's functionality is converted into the problem of identifying redundant connection faults. Efficient test generation algorithms can thus be applied directly. Techniques that can efficiently locate redundant wires and/or nodes after adding a redundant wire are also proposed. Experiment results on MCNC benchmark circuits show that, on average, a 16% reduction in gate count and a 20% reduction in connection count can be achieved at a low computational cost. The suggested technique can also be applied for timing optimization. >

Abstract: A coterie under a ground set U consists of subsets (called quorums) of U such that any pair of quorums intersect with each other. Nondominated (ND) coteries are of particular interest, since they are optimal in some sense. By assigning a Boolean variable to each element in U, a family of subsets of U is represented by a Boolean function of these variables. The authors characterize the ND coteries as exactly those families which can be represented by positive, self-dual functions. In this Boolean framework, it is proved that any function representing an ND coterie can be decomposed into copies of the three-majority function, and this decomposition is representable as a binary tree. It is also shown that the class of ND coteries proposed by D. Agrawal and A. El Abbadi (1989) is related to a special case of the above binary decomposition, and that the composition proposed by M.L. Neilsen and M. Mizuno (1992) is closely related to the classical Ashenhurst decomposition of Boolean functions. A number of other results are also obtained. The compactness of the proofs of most of these results indicates the suitability of Boolean algebra for the analysis of coteries. >

Abstract: We investigate the possibility of finding satisfying assignments to Boolean formulae and testing validity of quantified Boolean formulae (QBF) asymptotically faster than a brute force search. Our first main result is a simple deterministic algorithm running in time $2^{n - \Omega(n)}$ for satisfiability of formulae of linear size in $n$, where $n$ is the number of variables in the formula. This algorithm extends to exactly counting the number of satisfying assignments, within the same time bound. Our second main result is a deterministic algorithm running in time $2^{n - \Omega(n/\log(n))}$ for solving QBFs in which the number of occurrences of any variable is bounded by a constant. For instances which are ``structured'', in a certain precise sense, the algorithm can be modified to run in time $2^{n - \Omega(n)}$. To the best of our knowledge, no non-trivial algorithms were known for these problems before. As a byproduct of the technique used to establish our first main result, we show that every function computable by linear-size formulae can be represented by decision trees of size $2^{n - \Omega(n)}$. As a consequence, we get strong super linear {\it average-case} formula size lower bounds for the Parity function.