For most large underdetermined systems of equations,the minimal 𝓁1‐norm near‐solution approximates the sparsest near‐solution

We consider inexact linear equations y ≈ Φx where y is a given vector in ?ⁿ, Φ is a given n × m matrix, and we wish to find x_0,? as sparse as possible while obeying ‖y ? Φx_0,?‖₂ ≤ ?. In general, this requires combinatorial optimization and so is considered intractable. On the other hand, the ??₁‐minimization problem is convex and is considered tractable. We show that for most Φ, if the optimally sparse approximation x_0,? is sufficiently sparse, then the solution x_1,? of the ??₁‐minimization problem is a good approximation to x_0,?. We suppose that the columns of Φ are normalized to the unit ??₂‐norm, and we place uniform measure on such Φ. We study the underdetermined case where m ～ τn and τ > 1, and prove the existence of ρ = ρ(τ) > 0 and C = C(ρ, τ) so that for large n and for all Φ's except a negligible fraction, the following approximate sparse solution property of Φ holds: for every y having an approximation ‖y ? Φx₀‖₂ ≤ ? by a coefficient vector x₀ ∈ ?^m with fewer than ρ · n nonzeros, This has two implications. First, for most Φ, whenever the combinatorial optimization result x_0,? would be very sparse, x_1,? is a good approximation to x_0,?. Second, suppose we are given noisy data obeying y = Φx₀ + z where the unknown x₀ is known to be sparse and the noise ‖z‖₂ ≤ ?. For most Φ, noise‐tolerant ??₁‐minimization will stably recover x₀ from y in the presence of noise z. We also study the barely determined case m = n and reach parallel conclusions by slightly different arguments. Proof techniques include the use of almost‐spherical sections in Banach space theory and concentration of measure for eigenvalues of random matrices. © 2006 Wiley Periodicals, Inc.     

A note on ℝ‐linear GMRES for solving a class of ℝ‐linear systems

We prove that ?‐linear GMRES for solving a class of ?‐linear systems is faster than GMRES applied to the related ?‐linear systems in terms of matrix–vector products. Numerical examples are given to demonstrate the theoretical result. Copyright © 2011 John Wiley & Sons, Ltd.     

Iteratively weighted thresholding homotopy method for the sparse solution of underdetermined linear equations

Recently, iteratively reweighted methods have attracted much interest in compressed sensing, outperforming their unweighted counterparts in most cases. In these methods, decision variables and weights are optimized alternatingly, or decision variables are optimized under heuristically chosen weights. In this paper,we present a novel weighted l1-norm minimization problem for the sparsest solution of underdetermined linear equations. We propose an iteratively weighted thresholding method for this problem, wherein decision variables and weights are optimized simultaneously. Furthermore, we prove that the iteration process will converge eventually. Using the homotopy technique, we enhance the performance of the iteratively weighted thresholding method. Finally, extensive computational experiments show that our method performs better in terms of both running time and recovery accuracy compared with some state-of-the-art methods.     

On solution of large systems of linear equations with block-Toeplitz banded matrices

A novel numerical algorithm is proposed for solving systems of linear equations with block-Toeplitz narrow-banded matrices. Its arithmetical cost is about double of that of the block cyclic reduction. The backward roundoff error stability of the method guarantees its reliability for the matrices that are not symmetric positive definite or diagonally dominant.     

A note on the filtered least squares minimal norm solution of first kind equations

A convergence theorem for J. W. Lee and P. M. Prenter's filtered least squares method for solving the Fredholm first kind equation Kf = g is corrected. Under suitable restrictions the filtered least squares method is shown to be well posed under compact perturbations in K and arbitrary perturbations in g.     

Global solution of the 3‐D incompressible Navier‐Stokes equations in the Besov spaces B˙r1,r2,r3σ,1

In this paper, we construct a more general Besov spaces ${\dot{B}}_{r_1,r_2,r_3}^{\sigma ,q}$ and consider the global well‐posedness of incompressible Navier‐Stokes equations with small data in ${\dot{B}}_{r_1,r_2,r_3}^{\sigma ,\infty }$ for $\frac{1}{r_1}+\frac{1}{r_2}+\frac{1}{r_3}?\sigma =1,1?r_i<\infty$. In particular, we show that for any $\frac{2}{\gamma }+\frac{1}{p_1}+\frac{1}{p_2}+\frac{1}{p_3}?s=1,1<\gamma <\infty$ and $r_i?p_i<\infty$, the solution with initial data in ${\dot{B}}_{r_1,r_2,r_3}^{\sigma ,\infty }$ belong to , which, as far as we know, has not been discussed in other papers. Moreover, the smoothing effect of the solution to Navier‐Stokes equations is proved, which may have its own interest.     

The most storage economical Runge-Kutta methods for the solution of large systems of coupled first-order differential equations

It is shown how the attainable minimum for the memory requirements of Runge-Kutta methods can be realised for methods of the third order. These economisable third order methods belong to a one parameter sub-family from which two particular members with low error bound are selected.     

Bipolar fuzzy relation equations systems based on the product t‐norm

Bipolar fuzzy relation equations arise as a generalization of fuzzy relation equations considering unknown variables together with their logical connective negations. The occurrence of a variable and the occurrence of its negation simultaneously can give very useful information for certain frameworks where the human reasoning plays a key role. Hence, the resolution of bipolar fuzzy relation equations systems is a research topic of great interest. This paper focuses on the study of bipolar fuzzy relation equations systems based on the max‐product t‐norm composition. Specifically, the solvability and the algebraic structure of the set of solutions of these bipolar equations systems will be studied, including the case in which such systems are composed of equations whose independent term be equal to 0. As a consequence, this paper complements the contribution carried out by the authors on the solvability of bipolar max‐product fuzzy relation equations.     

On the mini-computer solution of large systems of linear equations arising from the finite element method

The efficiency of the application of mini-computers to the solution of many problems by means of the finite element method is well recognized, and the importance of the percentage of time devoted to the solution of the resultant systems of linear equations is also noteworthy.Here, we present a comparative study of six programs of the solution of systems of linear equations, implemented in a 64-Kbyte mini-computer (HP1000F). The methods and algorithms on which the programs are based are described.Then, six finite element problems are presented with various degrees of discretization, giving rise to 19 different cases. In each case computation times, the number of disk input-output transfers and the number of arithmetic operations carried out are compared. It is concluded that the programs based on algorithms of variable bandwidth are always superior to those of constant bandwidth. In some cases, the optimum results are obtained with the algorithm of hypermatrices.     

Thermoelasticity with second sound—exponential stability in linear and non‐linear 1‐d

We consider linear and non‐linear thermoelastic systems in one space dimension where thermal disturbances are modelled propagating as wave‐like pulses travelling at finite speed. This removal of the physical paradox of infinite propagation speed in the classical theory of thermoelasticity within Fourier's law is achieved using Cattaneo's law for heat conduction. For different boundary conditions, in particular for those arising in pulsed laser heating of solids, the exponential stability of the now purely, but slightly damped, hyperbolic linear system is proved. A comparison with classical hyperbolic–parabolic thermoelasticity is given. For Dirichlet type boundary conditions—rigidly clamped, constant temperature—the global existence of small, smooth solutions and the exponential stability are proved for a non‐linear system. Copyright © 2002 John Wiley & Sons, Ltd.     

Optimization in “self‐modeling” complex adaptive systems

When a dynamical system with multiple point attractors is released from an arbitrary initial condition, it will relax into a configuration that locally resolves the constraints or opposing forces between interdependent state variables. However, when there are many conflicting interdependencies between variables, finding a configuration that globally optimizes these constraints by this method is unlikely or may take many attempts. Here, we show that a simple distributed mechanism can incrementally alter a dynamical system such that it finds lower energy configurations, more reliably and more quickly. Specifically, when Hebbian learning is applied to the connections of a simple dynamical system undergoing repeated relaxation, the system will develop an associative memory that amplifies a subset of its own attractor states. This modifies the dynamics of the system such that its ability to find configurations that minimize total system energy, and globally resolve conflicts between interdependent variables, is enhanced. Moreover, we show that the system is not merely “recalling” low energy states that have been previously visited but “predicting” their location by generalizing over local attractor states that have already been visited. This “self‐modeling” framework, i.e., a system that augments its behavior with an associative memory of its own attractors, helps us better understand the conditions under which a simple locally mediated mechanism of self‐organization can promote significantly enhanced global resolution of conflicts between the components of a complex adaptive system. We illustrate this process in random and modular network constraint problems equivalent to graph coloring and distributed task allocation problems. © 2010 Wiley Periodicals, Inc. Complexity 16: 17–26, 2011     

Numerical solution of parameter‐dependent linear systems

We are interested in the numerical solution of the complex large linear system, (σ²A+σB+C)x=f(σ), for many, possibly a few hundreds, values of the complex parameter σ in a wide range. We assume that A, B and C are large, sparse, symmetric matrices, as is the case in several application problems. In particular, we focus on the following structured right‐hand side, f(σ)=FΦ(σ), where F is a (tall) rectangular matrix whose entries are independent of σ. We propose to approximate the solution x=x(σ) by means of a projection onto a single vector subspace, and a subsequent solution of the reduced dimension problem, for all values of interest of the parameter σ. Numerical experiments report the effectiveness of our approach on real application problems. Copyright © 2005 John Wiley & Sons, Ltd.     

1‐rotationally resolvable 4‐cycle systems of 2Kv

In this article, it is shown that there exists a 1‐rotationally resolvable 4‐cycle system of 2K_υ if and only if υ ≡ 0 (mod 4). To prove that, some special sequences of integers are utilized. © 2002 Wiley Periodicals, Inc. J Combin Designs 10: 116–125, 2002; DOI 10.1002/jcd.10006     

ω‐categorical weakly o‐minimal expansions of Boolean lattices

We study ω‐categorical weakly o‐minimal expansions of Boolean lattices. We show that a structure ?? = (A,≤, ?) expanding a Boolean lattice (A,≤) by a finite sequence I of ideals of A closed under the usual Heyting algebra operations is weakly o‐minimal if and only if it is ω‐categorical, and hence if and only if A/I has only finitely many atoms for every I ∈ ?. We propose other related examples of weakly o‐minimal ω‐categorical models in this framework, and we examine the internal structure of these models.     

四元数体上一类矩阵方程的极小范数最小二乘解

借助于四元数体上自共轭矩阵的奇异值分解,给出了四元数矩阵方程AX＋XB＋CXD=F的极小范数最小二乘解.同时,在有解的条件下给出了Hermite最小二乘解及其通解的表达形式.     

Self‐Intersection Local Time for 𝒮′(ℝd)‐Ornstein‐Uhlenbeck Processes Arising from Immigration Systems

Fluctuation limits of an immigration branching particle system and an immigration branching measure‐valued process yield different types of 𝒮′(ℝ^d)‐valued Ornstein‐Uhlenbeck processes whose covariances are given in terms of an excessive measure for the underlying motion in Rd, which is taken to be a symmetric α‐stable process. In this paper we prove existence and path continuity results for the self‐intersection local time of these Ornstein‐Uhlenbeck processes. The results depend on relationships between the dimension d and the parameter α.     

Holomorphic liftings and Bergman kernel estimates for 𝒟ℱ𝒩‐domains

Let E be a 𝒟ℱ𝒩‐space and let U ⊂ E be open. By applying the nuclearity of the Fréchet space ℋ︁(U) of holomorphic functions on U we show that there are finite measures μ on U leading to Bergman spaces of μ ‐square integrable holomorphic functions. We give an explicit construction for μ by using infinite dimensional Gaussian measures. Moreover, we prove boundary estimates for the corresponding Bergman kernels K_μ on the diagonal and we give an application of our results to liftings of μ ‐square integrable Banach space valued holomorphic functions over U. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Time-periodic solutions of wave equations on ℝ1 and ℝ3

The classical Paiey-Wiener theorem and Hilbert space methods are used to show the existence of time-periodic solutions of the wave equation w_tt?w_rr+λw=h, 0 < r < + ∞, which are radially symmetric and have exponential decay as r → + ∞. This problem is obtained when considering a one-dimensional or three-dimensional problem, and should be thought of as a linearization of a semilinear problem in which the associated linear operator has point spectrum (? ∞, λ). When λ ? 0 there is uniqueness, otherwise there is a non-trivial finite-dimensional null space. Estimates on w, w_t, w_r are obtained, which show that in either case there is a continuous correspondence h → w, where w is a uniquely characterized solution.