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2 edition of Families of sequences constructed from pseudorandom arrays found in the catalog.

Families of sequences constructed from pseudorandom arrays

V. L. Bastajian

Families of sequences constructed from pseudorandom arrays

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Published by UMIST in Manchester .
Written in English


Edition Notes

StatementV.L. Bastajian ; supervised by D. Green.
ContributionsGreen, D., Electrical Engineering and Electronics.
ID Numbers
Open LibraryOL19177149M

Examples of shift and add sequences Further properties of shift and add sequences Proof of Theorem Arithmetic Shift and Add Sequences Exercises Chapter m-Sequences Basic properties of m-sequences Decimations Interleaved structure Pseudo-noise arrays Fourier transforms and m-sequences. I have an array of 5 numbers and I need to figure out if one of those 3 combinations is in that array. For those not familiar with Yahtzee, there are 5 dice (the five numbers in the array) that can be from This book describes the optimized implementations of several arithmetic datapath, controlpath and pseudorandom sequence generator circuits for realization of high performance arithmetic circuits targeted towards a specific family of the high-end Field Programmable Gate Arrays (FPGAs). It explores regular, modular, cascadable and bit-sliced architectures of these circuits, by directly.


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Families of sequences constructed from pseudorandom arrays by V. L. Bastajian Download PDF EPUB FB2

The pseudo-random sequences of length 2* - 1, together with the zero sequence, are isomorphic to a field with 2m elements. Section describes pseudo-random arrays and properties. So far everything has been binary, but in Section IV we describe pseudo-random sequences and arrays. Abstract. A few constructions of infinite arrays such that, in each (2 n +n-1)×(2 n +1) subarray, each n×2 binary matrix appears exactly once, are given.

In other constructions each n×2 binary nonzero matrix appears exactly constructions are using patterns with distinct differences, and although the arrays are not linear they have some similar properties to by: 2.

Abstract. In earlier papers we introduced the measures of pseudorandomness of finite binary sequences [13], introduced the notion of f–complexity of families of binary sequences, constructed large families of binary sequences with strong PR (= pseudorandom) properties [6], [12], and we showed that one of the earlier constructions can be modified to obtain families with high f–complexity [4].Cited by: Furthermore, we introduce two large families of pseudorandom binary sequences constructed by the multiplicative inverse and additive character, and study the pseudorandom measures and the Gowers.

sequences, constructed large families of binary sequences with strong PR (= pseudorandom) properties [6], [12], and we showed that one of the earlier con-structions can be modified to obtain families with high f–complexity [4].

In another paper [14] we extended the study of pseudorandomness from binary se-quences to sequences on k symbols (“letters”). In [14] we also constructedone. It is proposed that this set of arrays be called a “pseudorandom sequence of arrays,” or PRSAs. Some interesting properties of the PRSA as well as its practical (hardware) implementation have been mentioned.

It has also been shown that our result is a special case of the general N (3)/ D (3) by: 5. A family of pseudorandom sequences of k symbols are constructed by using finite fields of prime-power order. Large families of pseudorandom sequences of k symbols and their complexity, Part II R.

Ahlswede, C. Mauduit and A. S´ark¨ozy Dedicated to the memory of Levon Khachatrian We continue the investigation of Part I, keep its terminology.

We present now criteria for a triple (r, t, p)tobek– by: 7. a sequence. Finally, we investigate the properties of a family of sequences constructed as the direct sum of two sequences with ideal autocorrela-tion, like the GMW sequences. 1 Introduction Traditionally, pseudorandom sequences have been employed in numerous appli-cations, for instance in spread spectrum, code division multiple access, optical.

When d = 1, perfect maps and pseudorandom arrays have been studied extensively as the two-dimensional generalization of de Bruijn sequences and m-sequence [5,15, 13]. For large values of d. Oon constructed large families of finite binary sequences with strong pseudorandom properties by using Dirichlet characters of large order.

In this paper Oon’s construction is generalized and extended. We prove that in our construction the well-distribution and correlation measures are as “small” as in the case of the Legendre by: 5.

The papers have been organized in topical sections on Boolean functions, perfect sequences, correlation of arrays, relative difference sets, aperiodic correlation, pseudorandom sequences and stream ciphers, crosscorrelation of sequences, prime numbers in sequences, OFDM and CDMA, and frequency-hopping sequences.

In a series of papers Mauduit and Sárközy (partly with coauthors) studied finite pseudorandom binary sequences. They showed that the Legendre symbol forms a “good” pseudorandom sequence, and they also tested other sequences for pseudorandomness, however, no large family of “good” pseudorandom sequences has been found by: Introduction Collision and avalanche e ect 1st construction: Legendre symbol 2nd construction: based on additive character Conclusion.

An ideally good family of pseudorandom binary sequences is collision free. If Fis not collision free but the number of collisions is limited =)they do. In cryptography one needs large families of binary sequences with strong pseudorandom properties.

In the last decades many families of this type have been constructed. However, in many applications it is not enough if our family of “good” sequences is large, it is more important to know that it has a rich, complex structure, and the Cited by: 6.

p-ary pseudo-random sequences. p-ary Pseudo Random Sequences. The p-ary case of PRSs, where p is an odd prime, has been studied by researchers from the thirties of the last century.

The p-ary m-sequences and the Gordon, Mills and Welch (GMW) sequences are two well-known families of perfect p-ary sequences of length p. Families of Multidimensional Arrays with Good Autocorrelation and Asymptotically Optimal Cross-correlation Sam Blake Janu Abstract We introduce a construction for families of 2n-dimensional arrays with asymptoti-cally optimal pairwise cross-correlation.

These arrays are constructed using a circulant array of n-dimensional Legendre Author: Sam Blake. We study a family of symmetric third-order recurring sequences with the aid of Riordan arrays and Chebyshev polynomials.

Formulas involving both Chebyshev poly-nomials and Fibonacci numbers are. Keywords: Chaotic map, pseudo-random binary sequence generator 1 Introduction Pseudorandom binary sequences using chaotic maps are continually increasing in the last three decades.

The need of novel ones is always expanding in the advanced interactive media. A novel pseudorandom number algorithm based on Logistic map, is pro-posed in [8]. A method of constructzon is presented for rectangular quaszorthogonal code arrays over the ring Z+ The proposed arrays are easy to generate: The four-phase lznear recurrzng sequences constructed Author: Serdar Boztas.

Array of sequence. Ask Question Asked 7 years, 2 months ago. Active 7 years, 2 months ago. Viewed 1k times 3. Let's say I have a sequence of integers, from 0 (always starting at 0) to 3. Now, I have an array of integers, which will hold those sequence looped one after the other, starting from a certain point.

An array of 5 elements, the. (3 votes, average: out of 5) Maximum-length sequences (also called as m-sequences or pseudo random (PN) sequences) are constructed based on Galois field theory which is an extensive topic in itself.A detailed treatment on the subject of Galois field theory can be found in references [1] and [2].

A pseudorandom binary sequence (PRBS) is a binary sequence that, while generated with a deterministic algorithm, is difficult to predict and exhibits statistical behavior similar to a truly random sequence.

PRBS generators are used in telecommunication, but also in encryption, simulation, correlation technique and time-of-flight spectroscopy. statistics and low correlation properties are constructed from addition of m-sequences with pairwise-prime periods (AMPP).

Using m-sequences as building blocks, the proposed method proved to be an efficient and flexible approach to construct long period pseudo-random sequences with desirable properties from short period : Jian Ren, Tongtong Li.

Sequences which have these properties (and in some cases also have other important properties) are the subject of this paper. We refer to such sequences as pseudurandorn and related sequences for reasons which are given below. The study of pseudorandom and related sequences spans more than twenty-five years.

STATISTICAL PROPERTIES OF PSEUDORANDOM SEQUENCES Ting Gu University of Kentucky, [email protected] termine the suitability of pseudorandom sequences for applications, we need to study their properties, in particular, their statistical properties. Wasilkowski who shows great care to me and my family.

My sincere thanks to : Ting Gu. T1 - On pseudorandomness of families of binary sequences. AU - Sárközy, András. PY - /1/ Y1 - /1/ N2 - In cryptography one needs large families of binary sequences with strong pseudorandom properties.

In the last decades many families of this type have been by: 6. Pseudorandom Sequences in Spread‐Spectrum Communications Generated by Cellular Automata, F.C. Ordaz‐Salazar et al. / ‐ Journal of Applied Research and Technology sequences [16].

It has better randomness properties because of which it generates larger sequences than the other rules with chaotic behavior [15]. resulting pseudorandom sequences have excellent autocorrelation properties. Such a method can be extended to inverse prime expansions to any base.

Introduction The effort of finding new families of pseudorandom sequences is a part of the process of keeping one step ahead of eavesdroppers and they are important in the design of.

The m-sequence is a type of pseudorandom sequence that has been studied intensively. However, its security is threatened due to its low linear complexity. Based on the state transition rules of the m-sequence, our research group has proposed a new sequence by changing its state transition order.

This provides a large number of sequences with similar levels of pseudo-randomness and Author: Sun Quanling, Lv Hong, Chen Wanli, Qi Peng. Keywords: pseudorandom binary sequences, tent map, NIST statistical test suite 1. Introduction Producing cryptographically secure Pseudo Random Number Generators (PRNGs) is a well known debate for the last 50 years.

A special interest is paid in the literature for the construction of pseudorandom binary sequences generators. 1 Introduction A family of functions F s: f0;1gk!f0;1g‘, indexed by a key s 2f0;1gn, is said to be pseudorandom if it satisfies the following two properties: Easy to evaluate: The value F s(x) is efficiently computable given s and x.

Pseudorandom: The function F s cannot be efficiently distinguished from a uniformly random function R: f0;1gk!f0;1g‘, given access to pairs (xFile Size: KB. The book should cover pseudorandom number generation at an introductory level: I'm not looking for a complete encyclopedic treatment on every research paper ever published in the area, but enough content to gain an entry level understanding in the area that you'd expect someone to learn in a first undergraduate course on pseudo-random number.

and we have the following result. Lemma The matrices C and D commute. Since the columns are copies of a pseudorandom sequence, C in fact consists of k2 copies of a k1 x k1 matrix F arranged along the diagonal: (1 F0 1) C= 0 where F is the matrix 0 1 0 0 0 0 1 0 F= 0 0 0 1 10 II 12!kl-l The matrix D is somewhat more complicated because, when weapply there­.

Pseudorandom binary sequence, returned as a logical column vector, or a numeric column vector. seq contains the first n values of the PRBS generator. If mapping is set to 'signed'. A pseudorandom number generator, also known as a deterministic random bit generator, is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers.

The PRNG-generated sequence is not truly random, because it is completely determined by an initial value, called the PRNG's seed.

Although sequences that are closer to truly random can be generated using hardware random number generators, pseudorandom number generators. This construction is known as a pseudorandom generator (PRG). PRGs - nowadays we mostly use descendant constructs called PRFs and PRPs - allow us to send our messages securely while requiring much, much less random data.

We only need a tiny "seed" of random data and this is stretched into a much longer pseudorandom : Ari Kalfus. COM S { Cryptography Oct 1, Lecture Pseudorandom functions Instructor: Rafael Pass Scribe: Stefano Ermon 1 Recap De nition 1 (Gen;Enc;Dec) is a.

for generation of sequences of pseudorandom numbers that simulate a uniform distribution over the unit interval (0,1). These are the basic sequences from which are derived pseudorandom numbers from other distributions, pseudoran-dom samples, and pseudostochastic processes.

In Chapter 1, as elsewhere in this book, the emphasis is on methods that. The seed value controls the first value produced by the formula used to produce pseudorandom numbers, and since the formula is deterministic it also sets the full sequence produced after the seed is changed.

The argument to seed() can be any hashable object. The default is to use a platform-specific source of randomness, if one is available. and Facta pseudorandom bit generator is actually a family of such PRBGs. Thus the theoretical security results for a family of PRBGs are only an indirect indication about the security of individual members.

Two cryptographically secure pseudorandom bit File Size: KB.In cryptography, a pseudorandom function family, abbreviated PRF, is a collection of efficiently-computable functions which emulate a random oracle in the following way: no efficient algorithm can distinguish (with significant advantage) between a function chosen randomly from the PRF family and a random oracle (a function whose outputs are fixed completely at random).Recording 1, flips in a logbook provides a sequence of pseudorandom outcomes: in possession of the logbook each outcome is known for certain; however, a person without the logbook sees only a random string of heads and tails.