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In \cite{Castoldi}, $q^t \by (q+1)t$ ordered orthogonal arrays (OOAs) of strength $t$ over the alphabet $\FF_q$ were constructed using linear feedback shift register sequences (LFSRs) defined by {\em primitive} polynomials in $\FF_q[x]$. In…

Combinatorics · Mathematics 2019-01-10 Daniel Panario , Mark Saaltink , Brett Stevens , Daniel Wevrick

The focus of this thesis is the study and construction of covering arrays, relying on maximal period sequences and other tools from finite fields. A covering array of strength $t$, denoted $\mathrm{CA}(N; t, k,v)$, is an $N\times k$ array…

Combinatorics · Mathematics 2017-08-29 Georgios Tzanakis

Augmented orthogonal arrays (AOAs) were introduced by Stinson, who showed the equivalence between ideal ramp schemes and augmented orthogonal arrays (Discrete Math. 341 (2018), 299-307). In this paper, we show that there is an…

Combinatorics · Mathematics 2018-07-04 Xin Wang , Lijun Ji , Yun Li , Miao Liang

We construct orthogonal arrays OA$_{\lambda} (k,n)$ (of strength two) having a row that is repeated $m$ times, where $m$ is as large as possible. In particular, we consider OAs where the ratio $m / \lambda$ is as large as possible; these…

Combinatorics · Mathematics 2018-12-14 Charles J. Colbourn , Douglas R. Stinson , Shannon Veitch

An orthogonal array (OA), denoted by $\text{OA}(M, n, q, t)$, is an $M \times n$ matrix over an alphabet of size $q$ such that every selection of $t$ columns contains each possible $t$-tuple exactly $\lambda=M / q^t$ times. An irredundant…

Information Theory · Computer Science 2025-06-05 Maryam Bajalan , Peter Boyvalenkov

Orthogonal array, a classical and effective tool for collecting data, has been flourished with its applications in modern computer experiments and engineering statistics. Driven by the wide use of computer experiments with both qualitative…

Methodology · Statistics 2022-03-15 Yuanzhen He , C. Devon Lin , Fasheng Sun

For prime powers q we use "strongly orthogonal" linear Sudoku solutions of order q^2 to construct ordered orthogonal arrays of type OOA (4,s,2,q), and for each q we present a range of values of s for which these constructions are valid.

Combinatorics · Mathematics 2014-12-22 John Lorch

We propose a novel method for the construction of orthogonal arrays. The algorithm makes use of the Kronecker Product operator in association with unit column vectors to generate new orthogonal arrays from existing orthogonal arrays. The…

Discrete Mathematics · Computer Science 2012-10-26 Ankit Pat

Mixed (asymmetric) orthogonal arrays (MOAs) generalize classical orthogonal arrays by allowing columns over different alphabets. However, their study requires very different structural tools than those used for symmetric orthogonal arrays…

Information Theory · Computer Science 2026-03-20 Maryam Bajalan , Peter Boyvalenkov , Ferruh Özbudak

Designs for Order-of-Addition (OofA) experiments have received growing attention due to their impact on responses based on the sequence of component addition. In certain cases, these experiments involve heterogeneous groups of units, which…

Methodology · Statistics 2026-02-04 Chang-Yun Lin

Orthogonal arrays are a type of combinatorial design that were developed in the 1940s in the design of statistical experiments. In 1947, Rao proved a lower bound on the size of any orthogonal array, and raised the problem of constructing…

Data Structures and Algorithms · Computer Science 2024-05-15 Nicholas Harvey , Arvin Sahami

An orthogonal array OA(q^{2n-1},q^{2n-2}, q,2) is constructed from the action of a subset of PGL(n+1,q^2) on some non--degenerate Hermitian varieties in PG(n,q^2). It is also shown that the rows of this orthogonal array correspond to some…

Combinatorics · Mathematics 2009-07-18 A. Aguglia , L. Giuzzi

We generate all the Orthogonal Arrays (OAs) of a given size n and strength t as the union of a collection of OAs which belong to an inclusion-minimal set of OAs. We derive a formula for computing the (Generalized) Word Length Pattern of a…

Statistics Theory · Mathematics 2018-01-03 Roberto Fontana , Fabio Rapallo

In an early paper, He and Tang [Biometrika 100 (2013) 254-260] introduced and studied a new class of designs, strong orthogonal arrays, for computer experiments, and characterized such arrays through generalized orthogonal arrays. The…

Statistics Theory · Mathematics 2014-08-29 Yuanzhen He , Boxin Tang

Conventional array designs based on circular fourth-order cumulant typically adopt a single expression form of the fourth-order difference co-array (FODCA), which limits the achievable degrees of freedom (DOFs) and neglects the impact of…

Signal Processing · Electrical Eng. & Systems 2025-08-28 Si Wang , Guoqiang Xiao

We study the problem of inferring a sparse vector from random linear combinations of its components. We propose the Accelerated Orthogonal Least-Squares (AOLS) algorithm that improves performance of the well-known Orthogonal Least-Squares…

Machine Learning · Statistics 2018-04-17 Abolfazl Hashemi , Haris Vikalo

The $q^k$ (full) factorial design with replication $\lambda$ is the multi-set consisting of $\lambda$ occurrences of each element of each $q$-ary vector of length $k$; we denote this by $\lambda\times [q]^k$. An $m\times n$ row-column…

Combinatorics · Mathematics 2023-03-29 Fahim Rahim , Nicholas J. Cavenagh

Orthogonal array and a large set of orthogonal arrays are important research objects in combinatorial design theory, and they are widely applied to statistics, computer science, coding theory and cryptography. In this paper, some new series…

Combinatorics · Mathematics 2023-12-20 Guangzhou Chen , Xiaodong Niu , Jiufeng Shi

We give a framework for generalizing LDPC code constructions that use Transversal Designs or related structures such as mutually orthogonal Latin squares. Our construction offers a broader range of code lengths and codes rates. Similar…

Combinatorics · Mathematics 2022-05-03 Diane Donovan , Asha Rao , Elif Üsküplü , E. Ş. Yazıcı

We present an intriguing discovery related to Random Fourier Features: in Gaussian kernel approximation, replacing the random Gaussian matrix by a properly scaled random orthogonal matrix significantly decreases kernel approximation error.…

Machine Learning · Computer Science 2016-10-31 Felix X. Yu , Ananda Theertha Suresh , Krzysztof Choromanski , Daniel Holtmann-Rice , Sanjiv Kumar
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