On symmetric differences of NP-hard sets with weakly P-selective sets

The symmetric differences of NP-hard sets with weakly-P-selective sets are investigated. We show that if there exist a weakly-P-selective set A and an NP-^P_m-hard set H such that H - AεP_btt(sparse) and A — HεP_m(sparse) then P = NP. So no NP-^P_m-hard set has sparse symmetric difference with any weakly-P-selective set unless P = NP. The proof of our main result is an interesting application of the tree prunning techniques (Fortune 1979; Mahaney 1982). In addition, we show that there exists a P-selective set which has exponentially dense symmetric difference with every set in P_btt(sparse).     

Highly reliable symmetric networks

We generalize directed loop networks to loop-symmetric networks in which there are N nodes and in which each node has in-degree and out-degree k, subject to the condition that 2^k does not exceed N. We show that by proper selection of links one can obtain generalized loop networks with optimal or close to optimal diameter and connectivity. The optimized diameter is less than k[N¹k/], where [x] indicates the ceiling of x. We also show that these networks are rather compact in that the diameter is not more than twice the average distance. Roughly 1/2(k-1)N¹k/ nodes can be removed such that the network of remaining nodes is still strongly connected, if all remaining nodes have at least one incoming and one outgoing link left     

Characterizing and approximating eigenvalue sets of symmetric interval matrices

We consider the eigenvalue problem for the case where the input matrix is symmetric and its entries are perturbed, with perturbations belonging to some given intervals. We present a characterization of some of the exact boundary points, which allows us to introduce an inner approximation algorithm, that in many case estimates exact bounds. To our knowledge, this is the first algorithm that is able to guarantee exactness. We illustrate our approach by several examples and numerical experiments.     

Visualizing undirected graphs and symmetric square matrices as overlapping sets

Multimedia Tools and Applications - Undirected graphs and symmetric square matrices are frequently found in various domains. An example is character co-occurrence matrices in digital humanities....     

部分K值逻辑中完满对称函数集的确定和构造

根据部分K值逻辑的完备性理论,对于一般的K,首先确定了保二元完满对称函数集的个数,并给出了这些函数集的构造方法;然后确定了所有的完满对称函数集的个数,并给出了这些函数集的构造方法。     

Dominating sets and neighbor elimination-based broadcastingalgorithms in wireless networks

In a multihop wireless network, each node has a transmission radius and is able to send a message to all of its neighbors that are located within the radius. In a broadcasting task, a source node sends the same message to all the nodes in the network. In this paper, we propose to significantly reduce or eliminate the communication overhead of a broadcasting task by applying the concept of localized dominating sets. Their maintenance does not require any communication overhead in addition to maintaining positions of neighboring nodes. Retransmissions by only internal nodes in a dominating set is sufficient for reliable broadcasting. Existing dominating sets are improved by using node degrees instead of their ids as primary keys. We also propose to eliminate neighbors that already received the message and rebroadcast only if the list of neighbors that might need the message is nonempty. A retransmission after negative acknowledgements scheme is also described. The important features of the proposed algorithms are their reliability (reaching all nodes in the absence of message collisions), significant rebroadcast savings, and their localized and parameterless behavior. The reduction in communication overhead for the broadcasting task is measured experimentally. Dominating set based broadcasting, enhanced by a neighbor elimination scheme and highest degree key, provides reliable broadcast with ⩽53 percent of node retransmissions (on random unit graphs with 100 nodes) for all average degrees d. Critical d is around 4, with <48 percent for ⩽3, ⩽40 percent for d⩾10, and ⩽20 percent for d⩾25. The proposed methods are better than existing ones in all considered aspects: reliability, rebroadcast savings, and maintenance communication overhead. In particular, the cluster structure is inefficient for broadcasting because of considerable communication overhead for maintaining the structure and is also inferior in terms of rebroadcast savings     

Parameterized synthesis of self-stabilizing protocols in symmetric networks

Self-stabilization in distributed systems is a technique to guarantee convergence to a set of legitimate states without external intervention when a transient fault or bad initialization occurs. Recently, there has been a surge of efforts in designing techniques for automated synthesis of self-stabilizing algorithms that are correct by construction. Most of these techniques, however, are not parameterized, meaning that they can only synthesize a solution for a fixed and predetermined number of processes. In this paper, we report a breakthrough in parameterized synthesis of self-stabilizing algorithms in symmetric networks, including ring, line, mesh, and torus. First, we develop cutoffs that guarantee (1) closure in legitimate states, and (2) deadlock-freedom outside the legitimate states. We also develop a sufficient condition for convergence in self-stabilizing systems. Since some of our cutoffs grow with the size of the local state space of processes, scalability of the synthesis procedure is still a problem. We address this problem by introducing a novel SMT-based technique for counterexample-guided synthesis of self-stabilizing algorithms in symmetric networks. We have fully implemented our technique and successfully synthesized solutions to maximal matching, three coloring, and maximal independent set problems for ring and line topologies.     

Optimal conclusive sets for comparator networks

A set of input vectors S$S$ is conclusive for a certain functionality if, for every comparator network, correct functionality for all input vectors is implied by correct functionality for all vectors in S$S$. We consider four functionalities of comparator networks: sorting, merging, sorting of bitonic vectors, and halving. For each of these functionalities, we present two conclusive sets of minimal cardinality. The members of the first set are restricted to be binary, while the members of the second set are unrestricted. For all the above functionalities, except halving, the unrestricted conclusive set is much smaller than the binary one.     

Minimum feedback vertex sets in shuffle-based interconnection networks

Given a graph G, the problem is to construct a smallest subset S of vertices whose deletion results in an acyclic subgraph. The set S is called a minimum feedback vertex set for G.Tight upper and lower bounds on the cardinality of minimum feedback vertex sets have been previously obtained for some hypercube-like networks, such as meshes, tori, butterflies, cube-connected cycles and hypercubes. In this paper we construct minimum feedback vertex sets and determine their cardinalities in certain shuffle-based interconnection networks, such as shuffle-exchange, de Bruijn and Kautz networks.     

网络泛化能力与随机扩展训练集

针对神经网络的过拟合和泛化能力差的问题, 研究了样本数据的输入输出混合概率密度函数的局部最大熵密度估计, 提出了运用Chebyshev不等式的样本参数按类分批自校正方法, 以此估计拉伸样本集, 得到新的随机扩充训练集. 使估计质量更高, 效果更好. 仿真结果证明用这种方法训练的前馈神经网络具有较好的泛化性能.     

Approximating minimum independent dominating sets in wireless networks

We present the first polynomial-time approximation scheme (PTAS) for the Minimum Independent Dominating Set problem in graphs of polynomially bounded growth which are used to model wireless communication networks.The approach presented yields a robust algorithm, that is, it accepts any undirected graph as input, and returns a (1+ε)-approximate minimum independent dominating set, or a certificate showing that the input graph does not satisfy the bounded growth property.     

On positive influence dominating sets in social networks

In this paper, we investigate the positive influence dominating set (PIDS) which has applications in social networks. We prove that PIDS is APX-hard and propose a greedy algorithm with an approximation ratio of H(δ) where H is the harmonic function and δ is the maximum vertex degree of the graph representing a social network.     

Delay optimal coteries on regular symmetric networks

Coteries, introduced by Garcia-Molina and Barbara [Journal for the Association for Computing Machinery, 32 (4) (1985) 841], are an important and effective tool for enforcing mutual exclusion in distributed systems. Communication delay is an important performance measure for a coterie. Fu et al. [IEEE Transactions on Parallel and Distributed Systems, 8 (1) (1997) 59] emphasize that while calculating communication delay, the actual distances between different sites in a network must be taken into account and using this idea, obtain delay optimal coteries for trees, rings and hypercubes. Also, topology of an interconnection network plays an important role in the performance of a distributed system. For certain applications, it is desirable that the degree of each node in the interconnection network is the same. Constant Degree Four Cayley Graphs introduced by Vadapalli and Srimani [IEEE Transactions on Parallel and Distributed Systems 7(2) (1996) 26] provide an ideal topology for such applications. They are regular, have a logarithmic diameter and a node connectivity of four. In this paper, we prove that no coterie on an arbitrary network can have a delay of less than half the diameter of the network and use this result to obtain delay optimal coteries on regular symmetric networks with special reference to constant degree four Cayley interconnection-network.     

Maximal selection in tandem networks with symmetric hearing range

We consider an infinite tandem network in which every node is capable of hearing its neighbors up to a given distancen. At any moment of time every node may contain in the top of its queue a message destined to one of its neighbors. This network can be used as a model for a microwave or optic link with many users. For small and largen we investigate the maximal selection of nodes in the network, for which their transmissions are collision-free. For a large hearing range we show that the upper bound on the maximal selection, which is found herein, is asymptotically achievable. For small hearing ranges we show that a greedy selection is better but not asymptotically optimal. We also specify a sequence of upper bounds which converge to the maximal throughput.     

Maximal selection in tandem networks with symmetric hearing range

We consider an infinite tandem network in which every node is capable of hearing its neighbors up to a given distancen. At any moment of time every node may contain in the top of its queue a message destined to one of its neighbors. This network can be used as a model for a microwave or optic link with many users. For small and largen we investigate the maximal selection of nodes in the network, for which their transmissions are collision-free. For a large hearing range we show that the upper bound on the maximal selection, which is found herein, is asymptotically achievable. For small hearing ranges we show that a greedy selection is better but not asymptotically optimal. We also specify a sequence of upper bounds which converge to the maximal throughput.This research was done while J. M. Jaffe was on leave at the IBM Israel Scientific Center.     

Searching sets of properties with neural networks

In this paper we develop an algorithm in the framework of neural networks. Specifically we consider the problem of detecting a subset of elements of a set Ω which possess a given property.     

On the computational efficiency of symmetric neural networks

An open problem concerning the computational power of neural networks with symmetric weights is solved. It is shown that these networks possess the same computational power as general networks with asymmetric weights; i.e., these networks can compute any recursive function. The computations of these networks can be described as a minimmization process of a certain energy function; it is shown that for uninitialized symmetric neural networks this process presents a Σ₂-complete problem.     

Alien attractors and memory annihilation of structured sets inHopfield networks

This paper considers the encoding of structured sets into Hopfield associative memories. A structured set is a set of vectors with equal Hamming distance h from one another, and its centroid is an external vector that has distance h/2 from every vector of the set. Structured sets having centroids are not infrequent. When such a set is encoded into a noiseless Hopfield associative memory using a bipolar outer-product connection matrix, and the network operates with synchronous neuronal update, the memory of all encoded vectors is annihilated even for sets with as few as three vectors in dimension n>5 (four for n=5). In such self-annihilating structured sets, the centroid emerges as a stable attractor. We call it an alien attractor. For canonical structured sets, self-annihilation takes place only if h相似文献   

Invariant and attracting sets of Hopfield neural networks with delay

This paper studies invariant and attracting sets of Hopfield neural networks system with delay. Sufficient criteria are given for the invariant and attracting sets. In particular, we provide an estimate of the existence range of attractors by using invariant and attracting sets. Moreover, when the system has an equilibrium point, we obtain the sufficient conditions of global asymptotic stability of the equilibrium point. Several examples are also worked out to demonstrate the advantages of our results.