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This paper presents a class of random orthogonal sequences associated with the number theoretic Hilbert transform. We present a constructive procedure for finding the random sequences for different modulus values. These random sequences…

Cryptography and Security · Computer Science 2013-11-28 Subhash Kak

This paper presents a general expression for a number-theoretic Hilbert transform (NHT). The transformations preserve the circulant nature of the discrete Hilbert transform (DHT) matrix together with alternating values in each row being…

Cryptography and Security · Computer Science 2014-08-18 Subhash Kak

This paper presents an approach for the development of a number theoretic discrete Hilbert transform. The forward transformation has been applied by taking the odd reciprocals that occur in the DHT matrix with respect to a power of 2.…

Discrete Mathematics · Computer Science 2009-11-13 Renuka Kandregula

This paper presents new results in the theory of number theoretic Hilbert (NHT) transforms. New polymorphic solutions have been found for the 14-point and 16-point transforms. Several transform pairs are computed and solutions found for…

Cryptography and Security · Computer Science 2013-10-28 Vamsi Sashank Kotagiri

We propose a novel algorithm for large-scale regression problems named histogram transform ensembles (HTE), composed of random rotations, stretchings, and translations. First of all, we investigate the theoretical properties of HTE when the…

Machine Learning · Statistics 2019-12-11 Hanyuan Hang , Zhouchen Lin , Xiaoyu Liu , Hongwei Wen

The HRT (Heil-Ramanathan-Topiwala) conjecture stipulates that the set of any finitely many time-frequency shifts of a non-zero square Lebesgue integrable function is linearly independent. The present work settles two special cases of this…

Functional Analysis · Mathematics 2024-01-15 Kasso A. Okoudjou , Vignon Oussa

Random residue sequences (RR) may be used in many random number applications including those related to multiple access in communications. This paper investigates variations on an algorithm to generate RR sequences that was proposed earlier…

Cryptography and Security · Computer Science 2014-06-13 Vamsi Sashank Kotagiri

Statistical properties of random cross-correlated sequences constructed by the convolution method (likewise referred to as the Rice's or the inverse Fourier transformation) are examined. Algorithms for their generation are discussed. They…

Statistical Mechanics · Physics 2015-06-16 A. A. Maystrenko , S. S. Melnik , G. M. Pritula , O. V. Usatenko

This paper presents 10-point and 12-point versions of the recently introduced number theoretic Hilbert (NHT) transforms. Such transforms have applications in signal processing and scrambling. Polymorphic solutions with respect to different…

Cryptography and Security · Computer Science 2013-10-14 Vamsi Sashank Kotagiri

We study the structure of multiple correlation sequences defined by measure preserving actions of commuting transformations. When the iterates of the transformations are integer polynomials we prove that any such correlation sequence is the…

Dynamical Systems · Mathematics 2023-07-19 Nikos Frantzikinakis

The HRT (Heil-Ramanathan-Topiwala) posits the linear independence of any set of nonzero square-integrable vectors obtained from a single nonzero vector $f$ by applying a finite set of time-frequency shift operators. In this short note, we…

Functional Analysis · Mathematics 2023-05-23 Vignon Oussa

A transformed auto-correlation method is presented here, where a received signal is transformed based on a priori reflecting model, and then the transformed signal is cross-correlated to its original one. If the model is correct, after…

Instrumentation and Methods for Astrophysics · Physics 2014-07-03 Jianfeng Zhou , Yang Gao

We recast homogeneous linear recurrence sequences with fixed coefficients in terms of partial Bell polynomials, and use their properties to obtain various combinatorial identities and multifold convolution formulas. Our approach relies on a…

Combinatorics · Mathematics 2014-12-17 Daniel Birmajer , Juan B. Gil , Michael D. Weiner

Random contractions (sub-unitary random matrices) appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with discrete time. We analyze statistical properties of complex…

Chaotic Dynamics · Physics 2009-10-31 Yan V. Fyodorov , H. -J. Sommmers

Properties of the recently reported homogeneous Hilbert curves are deduced and reported. The nature of the affine transformations involved in the construction of the Hilbert curves is explored. The analytical representation of proper and…

Algebraic Geometry · Mathematics 2013-11-13 E. Estevez-Rams , I. Brito-Reyes

In this paper, we investigate PN-sequences with ideal autocorrelation property and the consequences of this property on the number of +1s and -1s and run structure of sequences. We begin by discussing and surveying about the length of…

Information Theory · Computer Science 2017-10-10 Mohammad J. Khojasteh , Morteza H. Shoreh , Jawad A. Salehi

In this paper we investigate the problem of estimating the regression function in models with correlated observations. The data is obtained from several experimental units each of them forms a time series. We propose a new estimator based…

Statistics Theory · Mathematics 2019-06-13 Djihad Benelmadani , Karim Benhenni , Sana Louhichi

Two particle correlations are studied in the reaction plane of peripheral relativistic heavy ion reactions where the initial state has substantial angular momentum. The earlier predicted rotation effect and Kelvin Helmholtz Instability,…

Nuclear Theory · Physics 2013-05-06 L. P. Csernai , S. Velle

The HRT (Heil-Ramanathan-Topiwala) conjecture asks whether a finite collection of time-frequency shifts of a non-zero square integrable function on $\mathbb{R}$ is linearly independent. This longstanding conjecture remains largely open even…

Classical Analysis and ODEs · Mathematics 2018-12-21 Kasso A. Okoudjou

Recurrent neural networks (RNNs) are brain-inspired models widely used in machine learning for analyzing sequential data. The present work is a contribution towards a deeper understanding of how RNNs process input signals using the response…

Machine Learning · Statistics 2021-02-15 Soon Hoe Lim
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