On the pivot structure for the weighing matrix W(12,11)

In the present article we concentrate our study on the growth problem for the weighing matrix W(12,11) and show that the unique W(12,11) has three pivot structures. An improved algorithm for extending a k × k (0,+,-) matrix to a W(n,n-1), if possible, has been developed to simplify the proof. For the implementation of the algorithm special emphasis is given to the notions of data structures and parallel processing.     

Lanczos and the Riemannian SVD in information retrieval applications

Variations of the latent semantic indexing (LSI) method in information retrieval (IR) require the computation of singular subspaces associated with the k dominant singular values of a large m × n sparse matrix A, where k?min(m,n). The Riemannian SVD was recently generalized to low‐rank matrices arising in IR and shown to be an effective approach for formulating an enhanced semantic model that captures the latent term‐document structure of the data. However, in terms of storage and computation requirements, its implementation can be much improved for large‐scale applications. We discuss an efficient and reliable algorithm, called SPK‐RSVD‐LSI, as an alternative approach for deriving the enhanced semantic model. The algorithm combines the generalized Riemannian SVD and the Lanczos method with full reorthogonalization and explicit restart strategies. We demonstrate that our approach performs as well as the original low‐rank Riemannian SVD method by comparing their retrieval performance on a well‐known benchmark document collection. Copyright 2004 John Wiley & Sons, Ltd.     

Possible numbers of positive entries of imprimitive nonnegative matrices

Zhan, X., Extremal numbers of positive entries of imprimitive nonnegative matrix, Linear Algebra Appl. (in press) has determined the maximum and minimum numbers of positive entries of imprimitive irreducible nonnegative matrices with a given imprimitivity index. Let σ( A ) denote the number of positive entries of a matrix A. Let M(n,?k) and m(n,?k) denote the maximum and minimum numbers of positive entries of imprimitive irreducible nonnegative matrices of order n with a given imprimitivity index k, respectively. In this article, we prove that for any positive integer d with m(n,k)≤ d?≤?M(n,k), there exists an n?×?n irreducible nonnegative matrix A with imprimitivity index k such that?σ?(A)=d.     

A new look at the doubling algorithm for a structured palindromic quadratic eigenvalue problem

Recently, Guo and Lin [SIAM J. Matrix Anal. Appl., 31 (2010), 2784–2801] proposed an efficient numerical method to solve the palindromic quadratic eigenvalue problem (PQEP) (λ²A^T+λQ + A)z = 0 arising from the vibration analysis of high speed trains, where have special structures: both Q and A are, among others, m × m block matrices with each block being k × k (thus, n = mk), and moreover, Q is block tridiagonal, and A has only one nonzero block in the (1,m)th block position. The key intermediate step of the method is the computation of the so‐called stabilizing solution to the n × n nonlinear matrix equation X + A^TX⁻¹A = Q via the doubling algorithm. The aim of this article is to propose an improvement to this key step through solving a new nonlinear matrix equation having the same form but of only k × k in size. This new and much smaller matrix equation can also be solved by the doubling algorithm. For the same accuracy, it takes the same number of doubling iterations to solve both the larger and the new smaller matrix equations, but each doubling iterative step on the larger equation takes about 4.8 as many flops than the step on the smaller equation. Replacing Guo's and Lin's key intermediate step by our modified one leads to an alternative method for the PQEP. This alternative method is faster, but the improvement in speed is not as dramatic as just for solving the respective nonlinear matrix equations and levels off as m increases. Numerical examples are presented to show the effectiveness of the new method. Copyright © 2014 John Wiley & Sons, Ltd.     

Orthogonal similarity transformation into block‐semiseparable matrices of semiseparability rank k

Very recently, an algorithm, which reduces any symmetric matrix into a semiseparable one of semi‐ separability rank 1 by similar orthogonality transformations, has been proposed by Vandebril, Van Barel and Mastronardi. Partial execution of this algorithm computes a semiseparable matrix whose eigenvalues are the Ritz‐values obtained by the Lanczos' process applied to the original matrix. Also a kind of nested subspace iteration is performed at each step. In this paper, we generalize the above results and propose an algorithm to reduce any symmetric matrix into a similar block‐semiseparable one of semiseparability rank k, with k ∈ ?, by orthogonal similarity transformations. Also in this case partial execution of the algorithm computes a block‐semiseparable matrix whose eigenvalues are the Ritz‐values obtained by the block‐Lanczos' process with k starting vectors, applied to the original matrix. Subspace iteration is performed at each step as well. Copyright © 2005 John Wiley & Sons, Ltd.     

Localisations of non prime e-vh-orders

Abstract

If A is an n × n complex matrix and x ∈ ? ⁿ , the conjecture is that if we take the kth power of each component of Ax, the resulting vector belongs to the range of the matrix obtained by taking the kth power of the entries of AA ^?, where A ^? is the adjoint of A. The conjecture is proved here for any k ≥ 2 when we add assumptions of either low dimension (namely, n ≤ 4) or low corank (0, 1, and, with some technical restrictions, 2). This problem arises in the study of the Jacobian Conjecture.     

Lanczos,Householder transformations,and implicit deflation for fast and reliable dominant singular subspace computation

Many applications, such as subspace‐based models in information retrieval and signal processing, require the computation of singular subspaces associated with the k dominant, or largest, singular values of an m×n data matrix A, where k?min(m,n). Frequently, A is sparse or structured, which usually means matrix–vector multiplications involving A and its transpose can be done with much less than ??(mn) flops, and A and its transpose can be stored with much less than ??(mn) storage locations. Many Lanczos‐based algorithms have been proposed through the years because the underlying Lanczos method only accesses A and its transpose through matrix–vector multiplications. We implement a new algorithm, called KSVD, in the Matlab environment for computing approximations to the singular subspaces associated with the k dominant singular values of a real or complex matrix A. KSVD is based upon the Lanczos tridiagonalization method, the WY representation for storing products of Householder transformations, implicit deflation, and the QR factorization. Our Matlab simulations suggest it is a fast and reliable strategy for handling troublesome singular‐value spectra. Copyright © 2001 John Wiley & Sons, Ltd.     

Faster algorithms for computing longest common increasing subsequences

We present algorithms for finding a longest common increasing subsequence of two or more input sequences. For two sequences of lengths n and m, where m?n, we present an algorithm with an output-dependent expected running time of and O(m) space, where ? is the length of an LCIS, σ is the size of the alphabet, and Sort is the time to sort each input sequence. For k?3 length-n sequences we present an algorithm which improves the previous best bound by more than a factor k for many inputs. In both cases, our algorithms are conceptually quite simple but rely on existing sophisticated data structures. Finally, we introduce the problem of longest common weakly-increasing (or non-decreasing) subsequences (LCWIS), for which we present an -time algorithm for the 3-letter alphabet case. For the extensively studied longest common subsequence problem, comparable speedups have not been achieved for small alphabets.     

Traversing Layered Graphs Using the Work Function Algorithm

The work function algorithm (WFA) is an on-line algorithm that has been studied mostly in connection with thek-server problem, but can actually be used on a wide variety of on-line problems. Despite being a simple algorithm, WFA has proven to be difficult to analyze, and until recently few interesting results were known. We analyze the performance of the generalized work function algorithm, denoted α-WFA, for on-line traversal of layered graphs. We show that for layered graphs of widthkand any α>1, α-WFA achieves competitive ratio (α+1)(2α/(α−1))^k−1−α. This gives anO(k2^k)-competitive ratio for appropriate choice of α, improving the previous upper bound ofO(k³2^k).     

A fast algorithm for computing the smallest eigenvalue of a symmetric positive‐definite Toeplitz matrix

Recent progress in signal processing and estimation has generated considerable interest in the problem of computing the smallest eigenvalue of a symmetric positive‐definite (SPD) Toeplitz matrix. An algorithm for computing upper and lower bounds to the smallest eigenvalue of a SPD Toeplitz matrix has been recently derived (Linear Algebra Appl. 2007; DOI: 10.1016/j.laa.2007.05.008 ). The algorithm relies on the computation of the R factor of the QR factorization of the Toeplitz matrix and the inverse of R. The simultaneous computation of R and R^?1 is efficiently accomplished by the generalized Schur algorithm. In this paper, exploiting the properties of the latter algorithm, a numerical method to compute the smallest eigenvalue and the corresponding eigenvector of SPD Toeplitz matrices in an accurate way is proposed. Copyright © 2008 John Wiley & Sons, Ltd.     

A characterisation of common diagonal stability over cones

In this article, a general notion of common diagonal Lyapunov matrix is formulated for a collection of n?×?n matrices A ₁,?…?,?A _s , and cones k ₁,?…?,?k _s in ? ⁿ . Necessary and sufficient conditions are derived for the existence of a common diagonal Lyapunov matrix in this setting. The conditions are similar to and extend the well-known criteria for the case s?=?1, k ₁?=?? ⁿ .     

A tabu search algorithm for the covering design problem

A (v,k,t)-covering design is a collection of k-subsets (called blocks) of a v-set V{\mathcal{V}} such that every t-subset of V{\mathcal{V}} is contained in at least one block. Given v, k and t, the goal of the covering design problem is to find a covering made of a minimum number of blocks. In this paper, we present a new tabu algorithm for tackling this problem. Our algorithm exploits a new implementation designed in order to evaluate efficiently the performance of the neighbors of the current configuration. The new implementation is much less space-consuming than the currently used technique, making it possible to tackle much larger problem instances. It is also significantly faster. Thanks to these improved data structures, our tabu algorithm was able to improve the upper bound of more than 50 problem instances.     

Minimum k-hamiltonian graphs,II

We consider in this paper graphs which remain hamiltonian after the removal of k edges (k-edge hamiltonian) or k vertices (k-hamiltonian). These classes of graphs arise from reliability considerations in network design. In a previous paper, W. W. Wong and C. K. Wong presented families of minimum k-hamiltonian graphs and minimum k-edge hamiltonian graphs for k even. Here, we complete this study in the case where k is odd.     

Non-orthogonal Fusion Frames and the Sparsity of Fusion Frame Operators

Fusion frames have become a major tool in the implementation of distributed systems. The effectiveness of fusion frame applications in distributed systems is reflected in the efficiency of the end fusion process. This in turn is reflected in the efficiency of the inversion of the fusion frame operator S_WS_{\mathcal{W}}, which in turn is heavily dependent on the sparsity of S_WS_{\mathcal{W}}. We will show that sparsity of the fusion frame operator naturally exists by introducing a notion of non-orthogonal fusion frames. We show that for a fusion frame {W _i ,v _i } _i∈I , if dim(W _i )=k _i , then the matrix of the non-orthogonal fusion frame operator S_W{\mathcal{S}}_{{\mathcal{W}}} has in its corresponding location at most a k _i ×k _i block matrix. We provide necessary and sufficient conditions for which the new fusion frame operator S_W{\mathcal{S}}_{{\mathcal{W}}} is diagonal and/or a multiple of an identity. A set of other critical questions are also addressed. A scheme of multiple fusion frames whose corresponding fusion frame operator becomes an diagonal operator is also examined.     

A reversal index for tournament matrices *

Given a tournament matrix T, its reversal indexi_R (T), is the minimum k such that the reversal of the orientation of k arcs in the directed graph associated with T results in a reducible matrix. We give a formula for i_R (T) in terms of the score vector of T which generalizes a simple criterion for a tournament matrix to be irreducible. We show that i_R (T)≤[(n?1)/2] for any tournament matrix T of order n, with equality holding if and only if T is regular or almost regular, according as n is odd or even. We construct, for each k between 1 and [(n?1)/2], a tournament matrix of order n whose reversal index is k. Finally, we suggest a few problems.     

The Hadamard-Fischer inequality for a class of matrices defined by eigenvalue monotonicity

The maximum dimension of a space of (k+1)×(k4+s?1) complex matrices of rank k is either s or s+1. Only when s divides k is it possible for the maximum to be s+1. This much is known. In this paper we produce for each k, a multiple of s, an (s+l)-dimensional space of (k+1)×(k+s?1) complex matrices whose non-zero members all have rank k. In the notation introduced by Sylvester l(k,k+1,k+s?1)=s+1 whenever s divides k.     

Aging properties of the residual life length of k‐out‐of‐n systems with independent but non‐identical components

The k‐out‐of‐n structure is a very popular type of redundancy in fault‐tolerant systems, it has founded wide applications in industrial and military systems during the past several decades. This paper will investigate the residual life length of a k‐out‐of‐n system with independent (not necessarily identical) components, given that the (n?k)th failure has occurred at time t?0. Behaviour of PF₂, IFR, DRHR, DMRL, NBU(2) and NBUC classes of life distributions are derived in terms of the monotonicity of the residual life given the time of the (n?k)th failure. Copyright © 2004 John Wiley & Sons, Ltd.     

Hamiltonicity of regular graphs and blocks of consecutive ones in symmetric matrices

We show that the Hamiltonicity of a regular graph G can be fully characterized by the numbers of blocks of consecutive ones in the binary matrix A+I, where A is the adjacency matrix of G, I is the unit matrix, and the blocks can be either linear or circular. Concretely, a k-regular graph G with girth g(G)?5 has a Hamiltonian circuit if and only if the matrix A+I can be permuted on rows such that each column has at most (or exactly) k-1 circular blocks of consecutive ones; and if the graph G is k-regular except for two (k-1)-degree vertices a and b, then there is a Hamiltonian path from a to b if and only if the matrix A+I can be permuted on rows to have at most (or exactly) k-1 linear blocks per column.Then we turn to the problem of determining whether a given matrix can have at most k blocks of consecutive ones per column by some row permutation. For this problem, Booth and Lueker gave a linear algorithm for k=1 [Proceedings of the Seventh Annual ACM Symposium on Theory of Computing, 1975, pp. 255-265]; Flammini et al. showed its NP-completeness for general k [Algorithmica 16 (1996) 549-568]; and Goldberg et al. proved the same for every fixed k?2 [J. Comput. Biol. 2 (1) (1995) 139-152]. In this paper, we strengthen their result by proving that the problem remains NP-complete for every constant k?2 even if the matrix is restricted to (1) symmetric, or (2) having at most three blocks per row.     

On the decomposition of k-noncrossing RNA structures

A k-noncrossing RNA structure can be identified with a k-noncrossing diagram over [n], which in turn corresponds to a vacillating tableau having at most (k−1) rows. In this paper we derive the limit distribution of irreducible substructures via studying their corresponding vacillating tableaux. Our main result proves, that the limit distribution of the numbers of irreducible substructures in k-noncrossing, σ-canonical RNA structures is determined by the density function of a -distribution for some τ_k>1.