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This paper addresses the problem of finding attractors in synchronous Boolean networks. The existing Boolean decision diagram-based algorithms have limited capacity due to the excessive memory requirements of decision diagrams. The simulation-based algorithms can be applied to larger networks, however, they are incomplete. We present an algorithm, which(More)
Conventional nonlinear feedback shift registers (NLFSRs) use the Fibonacci configuration in which the feedback is applied to the last bit only. In this paper, we show how to transform a Fibonacci NLFSR into an equivalent NLFSR in the Galois configuration, in which the feedback can be applied to every bit. Such a transformation can potentially reduce the(More)
A Kauffman network is an abstract model of gene regulatory networks. Each gene is represented by a vertex. An edge from one vertex to another implies that the former gene regulates the latter. Statistical features of Kauffman networks match the characteristics of living cells. The number of cycles in the network's state space, called attractors, corresponds(More)
Non-Linear Feedback Shift Registers (NLFSRs) have been proposed as an alternative to Linear Feedback Shift Registers (LFSRs) for generating pseudo-random sequences for stream ciphers. In this paper, we introduce (<i>n, k</i>)-NLFSRs which can be considered a generalization of the Galois type of LFSR. In an (<i>n, k</i>)-NLFSR, the feedback can be taken from(More)