The 0—1 Integer Programming Problem in a finite ring with identity

We define the 0—1 Integer Programming Problem in a finite field or finite ring with identity as: given an m × n matrix A and an n × 1 vector b with entries in the ring R, find or determine the non-existence of a 0—1 vector x such that Ax = b. We give an easily implemented enumerative algorithm for solving this problem, along with conditions that spurious solutions occur with probability as small as desired. Finally, we show that the problem is NP-complete if R is the ring of integers modulo r for r ≥ 3. This result suggests that it will be difficult to improve on our algorithm.     

Linear rotation based algorithm and systolic architecture for solving linear system equations

A linear rotation based algorithm is proposed for solving linear system equations, Ax = b. This algorithm modified the conventional Gaussian elimination method and can avoid the problems of numerical singularity and ill condition. In this study, the implementation of a trapezoidal systolic array of n²/2 + n −2 processors as well as a linear array of n processors are accomplished for this algorithm. The trapezoidal systolic array performs the triangularization of a matrix A by using the modified linear rotation algorithm; while the linear array performs the backward substitution for evaluating the solution of x. The computing time for solving a linear equation system will be O(5n) time units. Also an implicit representation of the elimination factor by means of the sign parameter sequence instead of an numerical value is introduced for simplifying the hardware complexity. It is clear that this systolic architecture is simple, uniform, and regular, and therefore well suitable for the implementation of a VLSI chip.     

Optimal and nearly optimal algorithms for approximating polynomial zeros

We substantially improve the known algorithms for approximating all the complex zeros of an n^th degree polynomial p(x). Our new algorithms save both Boolean and arithmetic sequential time, versus the previous best algorithms of Schönhage [1], Pan [2], and Neff and Reif [3]. In parallel (NC) implementation, we dramatically decrease the number of processors, versus the parallel algorithm of Neff [4], which was the only NC algorithm known for this problem so far. Specifically, under the simple normalization assumption that the variable x has been scaled so as to confine the zeros of p(x) to the unit disc x : |x| ≤ 1, our algorithms (which promise to be practically effective) approximate all the zeros of p(x) within the absolute error bound 2^−b, by using order of n arithmetic operations and order of (b + n)n² Boolean (bitwise) operations (in both cases up to within polylogarithmic factors). The algorithms allow their optimal (work preserving) NC parallelization, so that they can be implemented by using polylogarithmic time and the orders of n arithmetic processors or (b + n)n² Boolean processors. All the cited bounds on the computational complexity are within polylogarithmic factors from the optimum (in terms of n and b) under both arithmetic and Boolean models of computation (in the Boolean case, under the additional (realistic) assumption that n = O(b)).     

Resolvability and the upper dimension of graphs

For an ordered set W = {w₁, w₂,…, w_k} of vertices and a vertex v in a connected graph G, the (metric) representation of v with respect to W is the k-vector r(v | W) = (d(v, w₁), d(v, w₂),…, d(v, w_k)), where d(x, y) represents the distance between the vertices x and y. The set W is a resolving set for G if distinct vertices of G have distinct representations. A new sharp lower bound for the dimension of a graph G in terms of its maximum degree is presented.

A resolving set of minimum cardinality is a basis for G and the number of vertices in a basis is its (metric) dimension dim(G). A resolving set S of G is a minimal resolving set if no proper subset of S is a resolving set. The maximum cardinality of a minimal resolving set is the upper dimension dim⁺(G). The resolving number res(G) of a connected graph G is the minimum k such that every k-set W of vertices of G is also a resolving set of G. Then 1 ≤ dim(G) ≤ dim⁺(G) ≤ res(G) ≤ n − 1 for every nontrivial connected graph G of order n. It is shown that dim⁺(G) = res(G) = n − 1 if and only if G = K_n, while dim⁺(G) = res(G) = 2 if and only if G is a path of order at least 4 or an odd cycle.

The resolving numbers and upper dimensions of some well-known graphs are determined. It is shown that for every pair a, b of integers with 2 ≤ a ≤ b, there exists a connected graph G with dim(G) = dim⁺(G) = a and res(G) = b. Also, for every positive integer N, there exists a connected graph G with res(G) − dim⁺(G) ≥ N and dim⁺(G) − dim(G) ≥ N.     

Distribution of black nodes at various levels in a linear quadtree

The distribution of black leaf nodes at each level of a linear quadtree is of significant interest in the context of estimation of time and space complexities of linear quadtree based algorithms. The maximum number of black nodes of a given level that can be fitted in a square grid of size 2ⁿ × 2ⁿ can readily be estimated from the ratio of areas. We show that the actual value of the maximum number of nodes of a level is much less than the maximum obtained from the ratio of the areas. This is due to the fact that the number of nodes possible at a level k, 0≤k≤n − 1, should consider the sum of areas occupied by the actual number of nodes present at levels k + 1, k + 2, …, n − 1.     

Spacetime-minimal systolic arrays for Gaussian elimination and the Algebraic path problem

In this paper, we derive time-minimal systolic arrays for Gaussian elimination and the Algebraic Path Problem (APP) that use a minimal number of processors. For a problem of size n, we obtain an execution time T(n) = 3n −1 using A(n) = n²/4+O(n) processors for Gaussian elimination, and T(n) = 5n −2 and A(n) = n³/+O(n) for the APP.     

Analytic numerical solution of coupled semi-infinite diffusion problems

In this paper, we consider coupled semi-infinite diffusion problems of the form u_t(x, t)− A² u_xx(x,t) = 0, x> 0, t> 0, subject to u(0,t)=B and u(x,0)=0, where A is a matrix in , and u(x,t), and B are vectors in . Using the Fourier sine transform, an explicit exact solution of the problem is proposed. Given an admissible error and a domain D(x₀,t₀)={(x,t);0≤x≤x₀, t≥t₀ > 0, an analytic approximate solution is constructed so that the error with respect to the exact solution is uniformly upper bounded by in D(x₀, t₀).     

Nonlinear robust stabilization of multi-parameter families of systems

We show that given any family of asymptotically stabilizable LTI systems depending continuously on a parameter that lies in some subset [a₁,b₁]××[a_p,b_p] of , there exists a C⁰ time-varying state feedback law v(t,x) (resp. a C⁰ time-invariant feedback law v(x)) which robustly globally exponentially stabilizes (resp. which robustly stabilizes, not asymptotically) the family. Further, if these systems are obtained by linearizing some nonlinear systems, then v(t,x) locally exponentially stabilizes these nonlinear systems. Finally, v(t,x) globally exponentially stabilizes any time-varying system which switches “slowly enough” between the given LTI systems.     

Efficient enumeration of all minimal separators in a graph

This paper presents an efficient algorithm for enumerating all minimal a-b separators separating given non-adjacent vertices a and b in an undirected connected simple graph G = (V, E), Our algorithm requires O(n³R_ab) time, which improves the known result of O(n⁴R_ab) time for solving this problem, where ¦V¦= n and R_ab is the number of minimal a-b separators. The algorithm can be generalized for enumerating all minimal A-B separators that separate non-adjacent vertex sets A, B < V, and it requires O(n²(n − n_A − n_b)R_AB) time in this case, where n_a = ¦A¦, n_B = ¦B¦ and r_AB is the number of all minimal A−B separators. Using the algorithm above as a routine, an efficient algorithm for enumerating all minimal separators of G separating G into at least two connected components is constructed. The algorithm runs in time O(n³R⁺_Σ + n⁴R_Σ), which improves the known result of O(n⁶R_Σ) time, where R_σ is the number of all minimal separators of G and R_ΣR⁺_Σ = ∑_1i, v_j) ER_vivj n − 1)/2 − m)R_Σ. Efficient parallelization of these algorithms is also discussed. It is shown that the first algorithm requires at most O((n/log n)R_ab) time and the second one runs in time O((n/log n)R⁺_Σ+n log nR_Σ) on a CREW PRAM with O(n³) processors.     

Constant-time algorithm for computing the Euclidean distance maps of binary images on 2D meshes with reconfigurable buses

The computation of Euclidean distance maps (EDM), also called Euclidean distance transform, is a basic operation in computer vision, pattern recognition, and robotics. Fast computation of the EDM is needed since most of the applications using the EDM require real-time computation. It is shown in L. Chen and H.Y.H. Chuang [Information Processing Letters, 51, pp. 25–29 (1994)] that a lower bound Ω(n²) is required for any sequential EDM algorithm due to the fact that in any EDM algorithm each of the n² pixels has to be scanned at least once. Recently, many parallel EDM algorithms have been proposed to speedup its computation. Chen and Chuang proposed an algorithm for computing the EDM on an n×n mesh in O(n) time [L. Chen and H.Y.H. Chuang Parallel Computing, 21, pp. 841–852 (1995)]. Clearly, the VLSI complexities of both the sequential and the mesh algorithm described in L. Chen and H.Y.H. Chuang [Parallel Computing, 21, pp. 841–852 (1995)] are AT²=O(n⁴), where A is the VLSI layout area of the design and T is the computation time using area A when implemented in VLSI. In this paper, we propose a new and faster parallel algorithm for computing the EDM problem on the reconfigurable VLSI mesh model. For the same problem, our algorithm runs in O(1) time on a two-dimensional n²×n² reconfigurable mesh. We show that the VLSI complexity of our algorithm is the same as those of the above sequential algorithm and the mesh algorithm, while it uses much less time. To our best knowledge, this is the first constant-time EDM algorithm on any parallel computational model.     

Discontinuous quasivariational-like inequalities

In this note, we deal with the following problem: given X Rⁿ, a multification gG : X → 2^X, two (single-valued) maps f : X → Rⁿ, η : X × X → Rⁿ, find a point x* X such that x* Γ (x*) and f(x*), η(x,x*) ≥ 0 for all x Γ(x*). We prove an existence theorem in which, in particular, the function f is not supposed to be continuous.     

Solution of dense linear systems on an optimal systolic architecture

The paper presents an optimal systolic array architecture for rapid solution of dense systems of linear equations. The array solves a system of size n×n in 4n + 1 time units including I/0 time. Data communications are strictly local and the processing elements (PEs) are simple. The complete three-phase solution algorithm is executed on a single array, employing about 3n²/2 PEs without any need for costly inter-phase I/0. Due to a novel data steering mechanism, the three algorithmic phases are maximally overlapped. Design optimality is established using systolic precedence diagrams. It is also shown that merging the functions of two adjacent PEs into a single PE is possible resulting in maximal PE utilization. An interesting result regarding cascading phase-optimal arrays is obtained.     

Parallel generation of permutations on systolic arrays

We present a systolic algorithm to generate all the n! permutations of n given items. The computational model used is a linear systolic array consisting of n identical PEs. This algorithm requires n! time steps to solve this problem. Since any PE is identical and executes the same program, it is suitable for VLSI implementation. The correctness of the algorithm is proved. We also consider the ranking and unranking functions of permutations in this parallel algorithm     

Note on unit tangent vector computation for homotopy curve tracking on a hypercube

Probability-one homotopy methods are a class of methods for solving nonlinear systems of equations that are globally convergent from an arbitrary starting point. The essence of all such algorithms is the construction of an appropriate homotopy map ρ_a(λ, x) and subsequent tracking of some smooth curve γ in the zero set of the homotopy map. Tracking a homotopy curve involves finding the unit tangent vector at different points along the zero curve, which amounts to calculating the kernel of the n × (n + 1) Jacobian matrix Dρ_a(λ, x). While computing the tangent vector is just one part of the curve tracking algorithm, it can require a significant percentage of the total tracking time. This note presents computational results showing the performance of several different parallel orthogonal factorization/triangular system solving algorithms for the tangent vector computation on a hypercube.     

On the latent roots of λ matrices

In this paper we consider equations defined by (1.3)–(1.2)–(1.4). We describe in detail three algorithms for the approximate determination of |λ_nr|, for |λ₁| resp. for one of the λ_j's. The single steps of the algorithms are the four fundamental operations and the positive value of k^th roots of positive numbers and the main interest of them lies in the fact that (the algorithms themselves and so) their lengths depend only on n, r and the prescribed relative error and not on the entries of the matrices A_ν.     

Order-configuration functions: Mathematical characterizations and applications to digital signal and image processing

We call a function f in n variables an order-configuration function if for any x₁,…, x_n such that x_i1 … x_in we have f(x₁,…, x_n) = x_t, where t is determined by the n-tuple (i₁,…, i_n) corresponding to that ordering. Equivalently, it is a function built as a minimum of maxima, or a maximum of minima. Well-known examples are the minimum, the maximum, the median, and more generally rank functions, or the composition of rank functions. Such types of functions are often used in nonlinear processing of digital signals or images (for example in the median or separable median filter, min-max filters, rank filters, etc.). In this paper we study the mathematical properties of order-configuration functions and of a wider class of functions that we call order-subconfiguration functions. We give several characterization theorems for them. We show through various examples how our concepts can be used in the design of digital signal filters or image transformations based on order-configuration functions.     

Partial words and a theorem of Fine and Wilf revisited

A word of length n over a finite alphabet A is a map from {0,…,n−1} into A. A partial word of length n over A is a partial map from {0,…,n−1} into A. In the latter case, elements of {0,…,n−1} without image are called holes (a word is just a partial word without holes). In this paper, we extend a fundamental periodicity result on words due to Fine and Wilf to partial words with two or three holes. This study was initiated by Berstel and Boasson for partial words with one hole. Partial words are motivated by molecular biology.     

The error analysis for degree reduction of Bézier curves

The error analysis of Farin's and Forrest's algorithms for generating an approximation of degree n − 1 to an n^th degree Bézier curve is presented. Algorithms are based on observations of the geometric properties of the Bézier curve which allow the development of detailed error analysis. By combining subdivision with a degree reduction algorithm, a piecewise approximation can be generated, which is within some preset error tolerance of the original curve. The number of subdivisions required can be determined a priori and a piecewise approximation of degree m can be generated by iterating the scheme.     

Two minimum spanning forest algorithms on fixed-size hypercube computers

Two parallel algorithms for finding minimum spanning forest (MSF) of a weighted undirected graph on hypercube computers, consisting of a fixed number of processors, are presented. One algorithm is suited for sparse graphs, the other for dense graphs. Our design strategy is based on successive elimination of non-MSF edges. The input graph is partitioned equally among different processors, which then repeatedly eliminate non-MSF edges and merge results to gradually construct the desired MSF of the entire graph. Low communication overhead is achieved by restricting the message-flow to between the neighboring processors in the hypercube topology. The correctness of our approach is due to a theorem which states that with total-ordered edges, if an edge of an arbitrary subgraph does not belong to its MSF, then it does not belong to the MSF of the entire graph. For a graph of n vertices and m edges, our first algorithm finds an MSF in O(m log m)/p) time using p processors for p ≤ (mlog m)/n(1+log(m/n)). The second algorithm, efficient for dense graphs, requires O(n²/p) time for p≤n/log n.     

Fast median filtering algorithms for mesh computers

Two fast algorithms for median filtering of images using parallel computers having 2-D mesh interconnections are given. Both algorithms assume that an n × n image is loaded onto the mesh with one processing element per pixel. One algorithm performs median filtering over d × d neighborhoods in O(d²) time and works with pixel values in an arbitrarily large range. This algorithm, while theoretically suboptimal, achieves a lower constant than a previously published asymptotically—optimal algorithm and is simpler to program. The second algorithm assumes that the range of pixel values is limited and relatively small, and it accomplishes median filtering in O(d) time.