This paper shows that sum-of-product expression (SOP) minimization produces the generalization ability. We show this in three steps. First, various classes of SOPs are generated. Second, minterms of SOP are randomly selected to generate partially defined functions. And, third, from the partially defined functions, original functions are reconstructed by SOP minimization. We consider Achilles heel functions, majority functions, monotone increasing cascade functions, functions generated from random SOPs, monotone increasing random SOPs, circle functions, and globe functions. As for the generalization ability, the presented method is compared with Naive Bayes, multi-level perceptron, support vector machine, JRIP, J48, and random forest. For these functions, in many cases, only 10% of the input combinations are sufficient to reconstruct more than 90% of the truth tables of the original functions.

We present a time-efficient lower bound κ on the number of gates in Toffoli-based reversible circuits that represent a given reversible logic function. For the characteristic vector s of a reversible logic function, κ(s) closely approximates σ-lb(s), which is known as a relatively efficient lower bound in respect of evaluation time and tightness. The primary contribution of this paper is that κ enables fast computation while maintaining a tightness of the lower bound, approximately equal to σ-lb. We prove that the discrepancy between κ(s) and σ-lb(s) is at most one only, by providing upper and lower bounds on σ-lb in terms of κ. Subsequently, we show that κ can be calculated more efficiently than σ-lb. An algorithm for κ(s) with a complexity of 𝓞(n) is presented, where n is the dimension of s. Experimental results comparing κ and σ-lb are also given. The results demonstrate that the two lower bounds are equal for most reversible functions, and that the calculation of κ is significantly faster than σ-lb by several orders of magnitude.

This paper shows a method to find a linear transformation that reduces the number of variables to represent a given incompletely specified index generation function. It first generates the difference matrix, and then finds a minimal set of variables using a covering table. Linear transformations are used to modify the covering table to produce a smaller solution. Reduction of the difference matrix is also considered.

We present a new lower bound on the number of gates in reversible logic circuits that represent a given reversible logic function, in which the circuits are assumed to consist of general Toffoli gates and have no redundant input/output lines. We make a theoretical comparison of lower bounds, and prove that the proposed bound is better than the previous one. Moreover, experimental results for lower bounds on randomly-generated reversible logic functions and reversible benchmarks are given. The results also demonstrate that the proposed lower bound is better than the former one.

This paper presents a design method for AND-OR-EXOR three-level networks, where a single two-input exclusive-OR (EXOR) gate is used. The network realizes an EXOR of two sum-of-products expressions (EX-SOPs). The problem is to minimize the total number of products in the two sum-of-products expressions (SOPs). We introduce the notion of µ-equivalence of logic functions to develop exact minimization algorithms for EX-SOPs with up to five variables. We minimized all the NP-representative functions for up to five variables and showed that five-variable functions require 9 or fewer products in minimum EX-SOPs. For n-variable functions, minimum EX-SOPs require at most 9·2n-5 (n ≤ 6) products. This upper bound is smaller than 2n-1, which is the upper bound for SOPs. We also found that, for five-variable functions, on the average, minimum EX-SOPs require about 40% fewer literals than minimum SOPs.

This paper presents a design method for three-level programmable logic arrays (PLAs), which have input decoders and two-input EXOR gates at the outputs. The PLA realizes an EXOR of two sum-of-products expressions (EX-SOP) for multiple-valued input two-valued output functions. We developed an output phase optimization method for EX-SOPs where some outputs of the function are minimized in the complemented form and presented techniques to minimize EX-SOPs for adders by using an extension of Dubrova-Miller-Muzio's AOXMIN algorithm. The proposed algorithm produces solutions with a half products of AOXMIN-like algorithm in 250 times shorter time for large adders with two-valued inputs. We also proved that an n-bit adder with two-valued inputs requires at most 32n-2+7n-5 products in an EX-SOP while it is known that a sum-of-products expression (SOP) requires 62n-4n-5 products.

It has been considered difficult to obtain the minimum AND-EXOR expression of a given function with six variables in a practical computing time. In this paper, a faster algorithm of minimizing AND-EXOR expressions is proposed. We believe that our algorithm can compute the minimum AND-EXOR expressions of any six-variable and some seven-variable functions practically. In this paper, we first present a naive algorithm that searches the space of expansions of a given n-variable function f for a minimum expression of f. The space of expansions are generated by using all combinations of (n-1)-variable product terms. Then, how to prune the branches in the search process and how to restrict the search space to obtain the minimum solutions are discussed as the key point of reduction of the computing time. Finally a faster algorithm is constructed by using the methods discussed. Experimental results to demonstrate the effectiveness of these methods are also presented.

This paper presents a novel implication-based method for logic minimization in large-scale, multi-level networks. It significantly reduces network size through repeated addition and removal of redundant subnetworks, utilizing multi-signal implications and relationships among these implications. These are handled on a transitive implication graph, proposed in this paper, which offers the practical use of implications for logic minimization. The proposed method holds great promise for the achievement of an interactive logic design environment for large-scale networks.

In several design methods for Pass-transistor Logic (PTL) circuits, Boolean functions are expressed as OBDDs in decomposed form and then the component OBDDs are directly mapped to PTL cells. The total size of OBDDs (number of nodes) corresponds to the circuit size. In this paper, we investigate a method for PTL synthesis based on exact minimization of Free BDDs (FBDDs). FBDDs are well-studied extension of OBDDs with free variable ordering on each path. We present statistics showing that more than 56% of 616126 NPN-equivalence classes of 5-variable Boolean functions have minimum FBDDs with less size than their OBDDs. This result can be used for PTL synthesis as libraries. We also applied the exact minimization algorithm of FBDDs to the minimization of subcircuits in the synthesis for MCNC benchmarks and found up to 5% size reduction.

This paper presents a technique to determine prime implicants in multi-level combinational networks. The method is based on a graph representation of Boolean functions called AND/OR reasoning graphs. This representation follows from a search strategy to solve the satisfiability problem that is radically different from conventional search for this purpose (such as exhaustive simulation, backtracking, BDDs). The paper shows how to build AND/OR reasoning graphs for arbitrary combinational circuits and proves basic theoretical properties of the graphs. It will be demonstrated that AND/OR reasoning graphs allow us to naturally extend basic notions of two-level switching circuit theory to multi-level circuits. In particular, the notions of prime implicants and permissible prime implicants are defined for multi-level circuits and it is proved that AND/OR reasoning graphs represent all these implicants. Experimental results are shown for PLA factorization.

The FPGA logic synthesis consists of logic minimization step and technology mapping step. These two steps are usually performed separately to reduce the complexity of the problem. Conventional logic minimization methods try to minimize the number of literals of a given Boolean network, while FPGA technology mapping techniques attempt to minimize the number of basic blocks. However, minimizing the number of literals, which is target architecture-independent feature, does not always lead to minimization of basic block count, which is a FPGA architecture specific feature. Therefore, most of the existing technology mapping systems take into account reorganization of its input circuits to get better mapping results. Such a loosely coupled logic synthesis paradigm may cause difficulties in finding the optimal solution. In this paper, we propose a new logic synthesis approach where logic minimization and technology mapping steps are performed tightly coupled. Our system takes into account FPGA specific features in logic minimization step and thus our technology mapping step does not need to resynthesize the Boolean network. We formulate the technology mapping problem as a graph covering problem. Such formulation provides more global view to optimality and supports versatile cost functions. in addition, a fast and exact library management technique is devised for efficient FPGA cell matching which is one of the most frequently used operations in the FPGA logic synthesis.

This paper presents an exact minimization algorithm for AND-OR-EXOR three-level networks, where a single two-input exclusive-OR (EXOR) gate is used. The network realizes an EXOR of two sum-of-products expressions (EX-SOP), where the two sum-of-products expressions (SOP) can share products. The objective is to minimize the total number of different products in the two SOPs. An algorithm for the exact minimization of EX-SOPs with up to five variables are shown. Up to five variables, EX-SOPs for all the representative functions of NP-equivalence classes were minimized. For five-variable functions, we confirmed that minimum EX-SOPs require up to 9 products. For n-variable functions, minimum EX-SOPs require at most 92n-5 (n6) products.

This paper deals with minimization of ESOPs (exclusive-or sum-of-products) which represent symmetric functions. Se propose an efficient simplification algorithm for symmetric functions, which guarantees the minimality for some subclass of symmetric functions, and present the minimum ESOPs for all 6-variable symmetric functions.

A generalized Reed-Muller expression (GRM) is obtained by negating some of the literals in a positive polarity Reed-Muller expression (PPRM). There are at most 2(n2)^(n-1) different GRMs for an n-variable function. A minimum GRM is one with the fewest products. This paper presents certain properties and an exact minimization algorithm for GRMs. The minimization algorithm uses binary decision diagrams. Up to five variables, all the representative functions of NP-equivalence classes were generated and minimized. Tables compare the number of products necessary to represent four-and five-variable functions for four classes of expressions: PPRMs, FPRMs, GRMs and SOPs. GRMs require, on the average, fewer products than sum-of-products expressions (SOPs), and have easily testable realizations.

Recently, various efficient algorithms for solving combinatorial optimization problems using BDD-based set manipulation techniques have been developed. Minato proposed O-suppressed BDDs (ZBDDs) which is suitable for set manipulation, and it is utilized for various search problems. In terms of practical limits of space, however, there are still many search problems which are solved much better by using conventional branch-and-bound techniques than by using BDDs or ZBDDs, while the ability of conventional branch-and-bound approaches is limited by computation time. In this paper, an extension of APPLY operation, named APPRUNE (APply + PRUNE) operation, is proposed, which performs APPLY operation (ZBDD construction) and pruning simultaneously in order to reduce the required space for intermediate ZBDDs. As a prototype, a specific algorithm of APPRUNE operation is shown by assuming that the given condition for pruning is a threshold function, although it is expected that APPRUNE operation will be more effective if more sophisticated condition are considered. To reduce size of ZBDDs in intermediate steps, this paper also pay attention to the number of cared variables. As an application, an exact-minimization algorithm for generalized Reed-Muller expressions (GRMs) is implemented. From experimental results, it is shown that time and memory usage improved 8.8 and 3.4 times, respectively, in the best case using APPRUNE operation. Results on generating GRMs of exact-minimum number of not only product terms but also literals is also shown.

The present paper is concerned with an algorithm for the minimization of multiple-valued input, binary-valued output functions. The algorithm is an extension to muitiple-valued logic of an algorithm for the minimization of ordinary single-output Boolean functions. It is based on a local covering approach. Basically, it uses a "divide and conquer" technique, consisting of two steps called expansion and selection. The present algorithm preserves two important features of the original one. First, a lower bound on the number of prime implicants in the minimum cover of the given function is furnished as a by-product of the minimization. Second, all the essential primes of the function are identified and selected during the expansion process. That usually improves efficiency when handling functions with many essential primes. Results of a comparison of the proposed algorithm with the program ESPRESSO-IIC developed at Berkeley are presented.

This paper deals with the size of switching functions in Exclusive-OR sum-of-products expressions (ESOPs). The size is the number of products in ESOP. There are no good algorithms to find an exact minimum ESOP. Since the exact minimization algorithms take a time in double exponential order, it is almost impossible to minimize ESOPs for an arbitrary n-variable functions with n5. Then,it is necessary to study the size of some concrete functions. These concrete functions are useful for testing heuristic minimization algorithms. In this paper we present the lower bounds on size of periodic functions in ESOPs. A symmetric function is said to be periodic when the vector of weights of inputs X such that f(X)1 is periodic. We show that the size of a 2t+1-periodic function with rank r is proportional to n2t+r, where t0 and 0r2t, i.e., in polynomial order,and thet the size of a (2s+1)2t-periodic function with s0 and t0 is greater than or equal to (3/2)n-(2s+1)2t, i.e., in exponential order. The concrete function the size of which is greater than or equal to 32(3/2)n-8 is presented. This function requires the largest size among the concrete functions the sizes of which are known. Some results for non-periodic symmetric functions are also given.

This paper presents an optimization method for pseudo-Kronecker expressions of p-valued input two-valued output functions by using multi-place decision diagrams for p2 and p4. A conventional method using extended truth tables requires memory of O (3n) to simplify an n-variable expression, and is only practical for functions of up to n14 variables when p2. The method presented here utilizes multi-place decision diagrams, and can optimize considerably larger problems. Experimental results for up to n39 variables are shown.