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The Unilateral Z–Transform and Generating Functions
The Unilateral z{Transform and Generating Functions Recall from \Discrete{Time Linear, Time Invariant Systems and z-Transforms" that the behaviour of a discrete{time LTI system is determined by its impulse response function h[n] and that the z{transform of h[n] is 1 k H(z) = z− h[k] k=X −∞ If the LTI system is causal, then h[n] = 0 for all n < 0 and 1 k H(z) = z− h[k] Xk=0 Definition 1 (Unilateral z{Transform) The unilateral z{transform of the discrete{time signal x[n] (whether or not x[n] = 0 for negative n's) is defined to be 1 n (z) = z− x[n] X nX=0 When there is any danger of confusing the regular z{transform with the unilateral z{transform, 1 n X(z) = z− x[n] nX= 1 − is called the bilateral z{transform. Example 2 The signal x[n] = anu[n] is zero for all n < 0. So the unilateral z{transform of x[n] is the same as the ordinary z{transform. So, as we saw in Example 7 of \Discrete{Time Linear, Time Invariant Systems and z-Transforms", 1 n n 1 (z) = X(z) = z− a = 1 X 1 z− a nX=0 − 1 provided that z− a < 1, or equivalently z > a . Since the unilateral z{transform of any x[n] is always j j j j j j equal to the bilateral z{transform of the right{sided signal x[n]u[n], the region of convergence of a unilateral z{transform is always the exterior of a circle. -
On Fixed Points of Iterations Between the Order of Appearance and the Euler Totient Function
mathematics Article On Fixed Points of Iterations Between the Order of Appearance and the Euler Totient Function ŠtˇepánHubálovský 1,* and Eva Trojovská 2 1 Department of Applied Cybernetics, Faculty of Science, University of Hradec Králové, 50003 Hradec Králové, Czech Republic 2 Department of Mathematics, Faculty of Science, University of Hradec Králové, 50003 Hradec Králové, Czech Republic; [email protected] * Correspondence: [email protected] or [email protected]; Tel.: +420-49-333-2704 Received: 3 October 2020; Accepted: 14 October 2020; Published: 16 October 2020 Abstract: Let Fn be the nth Fibonacci number. The order of appearance z(n) of a natural number n is defined as the smallest positive integer k such that Fk ≡ 0 (mod n). In this paper, we shall find all positive solutions of the Diophantine equation z(j(n)) = n, where j is the Euler totient function. Keywords: Fibonacci numbers; order of appearance; Euler totient function; fixed points; Diophantine equations MSC: 11B39; 11DXX 1. Introduction Let (Fn)n≥0 be the sequence of Fibonacci numbers which is defined by 2nd order recurrence Fn+2 = Fn+1 + Fn, with initial conditions Fi = i, for i 2 f0, 1g. These numbers (together with the sequence of prime numbers) form a very important sequence in mathematics (mainly because its unexpectedly and often appearance in many branches of mathematics as well as in another disciplines). We refer the reader to [1–3] and their very extensive bibliography. We recall that an arithmetic function is any function f : Z>0 ! C (i.e., a complex-valued function which is defined for all positive integer). -
Ordinary Generating Functions
CHAPTER 10 Ordinary Generating Functions Introduction We’ll begin this chapter by introducing the notion of ordinary generating functions and discussing the basic techniques for manipulating them. These techniques are merely restatements and simple applications of things you learned in algebra and calculus. You must master these basic ideas before reading further. In Section 2, we apply generating functions to the solution of simple recursions. This requires no new concepts, but provides practice manipulating generating functions. In Section 3, we return to the manipulation of generating functions, introducing slightly more advanced methods than those in Section 1. If you found the material in Section 1 easy, you can skim Sections 2 and 3. If you had some difficulty with Section 1, those sections will give you additional practice developing your ability to manipulate generating functions. Section 4 is the heart of this chapter. In it we study the Rules of Sum and Product for ordinary generating functions. Suppose that we are given a combinatorial description of the construction of some structures we wish to count. These two rules often allow us to write down an equation for the generating function directly from this combinatorial description. Without such tools, we may get bogged down in lengthy algebraic manipulations. 10.1 What are Generating Functions? In this section, we introduce the idea of ordinary generating functions and look at some ways to manipulate them. This material is essential for understanding later material on generating functions. Be sure to work the exercises in this section before reading later sections! Definition 10.1 Ordinary generating function (OGF) Suppose we are given a sequence a0,a1,.. -
Labeled Factorization of Integers
Labeled Factorization of Integers Augustine O. Munagi John Knopfmacher Centre for Applicable Analysis and Number Theory School of Mathematics, University of the Witwatersrand Wits 2050, Johannesburg, South Africa [email protected] Submitted: Jan 5, 2009; Accepted: Apr 16, 2009; Published: Apr 22, 2009 Mathematics Subject Classification: 11Y05, 05A05, 11B73, 11B13 Abstract The labeled factorizations of a positive integer n are obtained as a completion of the set of ordered factorizations of n. This follows a new technique for generating ordered factorizations found by extending a method for unordered factorizations that relies on partitioning the multiset of prime factors of n. Our results include explicit enumeration formulas and some combinatorial identities. It is proved that labeled factorizations of n are equinumerous with the systems of complementing subsets of {0, 1,...,n − 1}. We also give a new combinatorial interpretation of a class of generalized Stirling numbers. 1 Ordered and labeled factorization An ordered factorization of a positive integer n is a representation of n as an ordered product of integers, each factor greater than 1. The set of ordered factorizations of n will be denoted by F (n), and |F (n)| = f(n). For example, F (6) = {6, 2.3, 3.2}. So f(6) = 3. Every integer n> 1 has a canonical factorization into prime numbers p1,p2,..., namely m1 m2 mr n = p1 p2 ...pr , p1 <p2 < ··· <pr, mi > 0, 1 ≤ i ≤ r. (1) The enumeration function f(n) does not depend on the size of n but on the exponents mi. In particular we define Ω(n)= m1 + m2 + ··· + mr, Ω(1) = 0. -
A Subspace Theorem for Manifolds
A subspace theorem for manifolds Emmanuel Breuillard and Nicolas de Saxcé February 5, 2021 Abstract We prove a theorem that generalizes Schmidt’s Subspace Theorem in the context of metric diophantine approximation. To do so we reformulate the Subspace theorem in the framework of homogeneous dynamics by introducing and studying a slope formalism and the corresponding notion of semistability for diagonal flows. Introduction In 1972, Wolfgang Schmidt formulated his celebrated subspace theorem [32, Lemma 7], a far reaching generalization of results of Thue [37], Siegel [35], and Roth [28] on rational approximations to algebraic numbers. Around the same time, in his work on arithmeticity of lattices in Lie groups, Gregory Margulis [26] used the geometry of numbers to establish the recurrence of unipotent flows on the space of lattices GLd(R)=GLd(Z). More than two decades later, a quantita- tive refinement of this fact, the so-called quantitative non-divergence estimate, was used by Kleinbock and Margulis [18] in their solution to the Sprindzuk conjecture regarding the extremality of non-degenerate manifolds in metric dio- phantine approximation. As it turns out, these two remarkable results – the subspace theorem and the Sprindzuk conjecture – are closely related and can be understood together as statements about diagonal orbits in the space of lat- tices. In this paper we prove a theorem that generalizes both results at the same time. We also provide several applications. This marriage is possible thanks to a better understanding of the geometry lying behind the subspace theorem, in particular the notion of Harder-Narasimhan filtration for one-parameter di- agonal actions, which leads both to a dynamical reformulation of the original subspace theorem and to a further geometric understanding of the family of exceptional subspaces arising in Schmidt’s theorem. -
The Bloch-Wigner-Ramakrishnan Polylogarithm Function
Math. Ann. 286, 613424 (1990) Springer-Verlag 1990 The Bloch-Wigner-Ramakrishnan polylogarithm function Don Zagier Max-Planck-Insfitut fiir Mathematik, Gottfried-Claren-Strasse 26, D-5300 Bonn 3, Federal Republic of Germany To Hans Grauert The polylogarithm function co ~n appears in many parts of mathematics and has an extensive literature [2]. It can be analytically extended to the cut plane ~\[1, ~) by defining Lira(x) inductively as x [ Li m_ l(z)z-tdz but then has a discontinuity as x crosses the cut. However, for 0 m = 2 the modified function O(x) = ~(Liz(x)) + arg(1 -- x) loglxl extends (real-) analytically to the entire complex plane except for the points x=0 and x= 1 where it is continuous but not analytic. This modified dilogarithm function, introduced by Wigner and Bloch [1], has many beautiful properties. In particular, its values at algebraic argument suffice to express in closed form the volumes of arbitrary hyperbolic 3-manifolds and the values at s= 2 of the Dedekind zeta functions of arbitrary number fields (cf. [6] and the expository article [7]). It is therefore natural to ask for similar real-analytic and single-valued modification of the higher polylogarithm functions Li,. Such a function Dm was constructed, and shown to satisfy a functional equation relating D=(x-t) and D~(x), by Ramakrishnan E3]. His construction, which involved monodromy arguments for certain nilpotent subgroups of GLm(C), is completely explicit, but he does not actually give a formula for Dm in terms of the polylogarithm. In this note we write down such a formula and give a direct proof of the one-valuedness and functional equation. -
Appendix a Tables of Fermat Numbers and Their Prime Factors
Appendix A Tables of Fermat Numbers and Their Prime Factors The problem of distinguishing prime numbers from composite numbers and of resolving the latter into their prime factors is known to be one of the most important and useful in arithmetic. Carl Friedrich Gauss Disquisitiones arithmeticae, Sec. 329 Fermat Numbers Fo =3, FI =5, F2 =17, F3 =257, F4 =65537, F5 =4294967297, F6 =18446744073709551617, F7 =340282366920938463463374607431768211457, Fs =115792089237316195423570985008687907853 269984665640564039457584007913129639937, Fg =134078079299425970995740249982058461274 793658205923933777235614437217640300735 469768018742981669034276900318581864860 50853753882811946569946433649006084097, FlO =179769313486231590772930519078902473361 797697894230657273430081157732675805500 963132708477322407536021120113879871393 357658789768814416622492847430639474124 377767893424865485276302219601246094119 453082952085005768838150682342462881473 913110540827237163350510684586298239947 245938479716304835356329624224137217. The only known Fermat primes are Fo, ... , F4 • 208 17 lectures on Fermat numbers Completely Factored Composite Fermat Numbers m prime factor year discoverer 5 641 1732 Euler 5 6700417 1732 Euler 6 274177 1855 Clausen 6 67280421310721* 1855 Clausen 7 59649589127497217 1970 Morrison, Brillhart 7 5704689200685129054721 1970 Morrison, Brillhart 8 1238926361552897 1980 Brent, Pollard 8 p**62 1980 Brent, Pollard 9 2424833 1903 Western 9 P49 1990 Lenstra, Lenstra, Jr., Manasse, Pollard 9 p***99 1990 Lenstra, Lenstra, Jr., Manasse, Pollard -
The Observability of the Fibonacci and the Lucas Cubes
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Discrete Mathematics 255 (2002) 55–63 www.elsevier.com/locate/disc The observability of the Fibonacci and the Lucas cubes Ernesto DedÃo∗;1, Damiano Torri1, Norma Zagaglia Salvi1 Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy Received 5 April 1999; received inrevised form 31 July 2000; accepted 8 January2001 Abstract The Fibonacci cube n is the graph whose vertices are binary strings of length n without two consecutive 1’s and two vertices are adjacent when their Hamming distance is exactly 1. If the binary strings do not contain two consecutive 1’s nora1intheÿrst and in the last position, we obtainthe Lucas cube Ln. We prove that the observability of n and Ln is n, where the observability of a graph G is the minimum number of colors to be assigned to the edges of G so that the coloring is proper and the vertices are distinguished by their color sets. c 2002 Elsevier Science B.V. All rights reserved. MSC: 05C15; 05A15 Keywords: Fibonacci cube; Fibonacci number; Lucas number; Observability 1. Introduction A Fibonacci string of order n is a binary string of length n without two con- secutive ones. Let and ÿ be binary strings; then ÿ denotes the string obtained by concatenating and ÿ. More generally, if S is a set of strings, then Sÿ = {ÿ: ∈ S}. If Cn denotes the set of the Fibonacci strings of order n, then Cn+2 =0Cn+1 +10Cn and |Cn| = Fn, where Fn is the nth Fibonacci number. -
Functions of Random Variables
Names for Eg(X ) Generating Functions Topic 8 The Expected Value Functions of Random Variables 1 / 19 Names for Eg(X ) Generating Functions Outline Names for Eg(X ) Means Moments Factorial Moments Variance and Standard Deviation Generating Functions 2 / 19 Names for Eg(X ) Generating Functions Means If g(x) = x, then µX = EX is called variously the distributional mean, and the first moment. • Sn, the number of successes in n Bernoulli trials with success parameter p, has mean np. • The mean of a geometric random variable with parameter p is (1 − p)=p . • The mean of an exponential random variable with parameter β is1 /β. • A standard normal random variable has mean0. Exercise. Find the mean of a Pareto random variable. Z 1 Z 1 βαβ Z 1 αββ 1 αβ xf (x) dx = x dx = βαβ x−β dx = x1−β = ; β > 1 x β+1 −∞ α x α 1 − β α β − 1 3 / 19 Names for Eg(X ) Generating Functions Moments In analogy to a similar concept in physics, EX m is called the m-th moment. The second moment in physics is associated to the moment of inertia. • If X is a Bernoulli random variable, then X = X m. Thus, EX m = EX = p. • For a uniform random variable on [0; 1], the m-th moment is R 1 m 0 x dx = 1=(m + 1). • The third moment for Z, a standard normal random, is0. The fourth moment, 1 Z 1 z2 1 z2 1 4 4 3 EZ = p z exp − dz = −p z exp − 2π −∞ 2 2π 2 −∞ 1 Z 1 z2 +p 3z2 exp − dz = 3EZ 2 = 3 2π −∞ 2 3 z2 u(z) = z v(t) = − exp − 2 0 2 0 z2 u (z) = 3z v (t) = z exp − 2 4 / 19 Names for Eg(X ) Generating Functions Factorial Moments If g(x) = (x)k , where( x)k = x(x − 1) ··· (x − k + 1), then E(X )k is called the k-th factorial moment. -
On Hardy's Apology Numbers
ON HARDY’S APOLOGY NUMBERS HENK KOPPELAAR AND PEYMAN NASEHPOUR Abstract. Twelve well known ‘Recreational’ numbers are generalized and classified in three generalized types Hardy, Dudeney, and Wells. A novel proof method to limit the search for the numbers is exemplified for each of the types. Combinatorial operators are defined to ease programming the search. 0. Introduction “Recreational Mathematics” is a broad term that covers many different areas including games, puzzles, magic, art, and more [31]. Some may have the impres- sion that topics discussed in recreational mathematics in general and recreational number theory, in particular, are only for entertainment and may not have an ap- plication in mathematics, engineering, or science. As for the mathematics, even the simplest operation in this paper, i.e. the sum of digits function, has application outside number theory in the domain of combinatorics [13, 26, 27, 28, 34] and in a seemingly unrelated mathematical knowledge domain: topology [21, 23, 15]. Pa- pers about generalizations of the sum of digits function are discussed by Stolarsky [38]. It also is a surprise to see that another topic of this paper, i.e. Armstrong numbers, has applications in “data security” [16]. In number theory, functions are usually non-continuous. This inhibits solving equations, for instance, by application of the contraction mapping principle because the latter is normally for continuous functions. Based on this argument, questions about solving number-theoretic equations ramify to the following: (1) Are there any solutions to an equation? (2) If there are any solutions to an equation, then are finitely many solutions? (3) Can all solutions be found in theory? (4) Can one in practice compute a full list of solutions? arXiv:2008.08187v1 [math.NT] 18 Aug 2020 The main purpose of this paper is to investigate these constructive (or algorith- mic) problems by the fixed points of some special functions of the form f : N N. -
Generating Functions
Mathematical Database GENERATING FUNCTIONS 1. Introduction The concept of generating functions is a powerful tool for solving counting problems. Intuitively put, its general idea is as follows. In counting problems, we are often interested in counting the number of objects of ‘size n’, which we denote by an . By varying n, we get different values of an . In this way we get a sequence of real numbers a0 , a1 , a2 , … from which we can define a power series (which in some sense can be regarded as an ‘infinite- degree polynomial’) 2 Gx()= a01++ ax ax 2 +. The above Gx() is the generating function for the sequence a0 , a1 , a2 , …. In this set of notes we will look at some elementary applications of generating functions. Before formally introducing the tool, let us look at the following example. Example 1.1. (IMO 2001 HK Preliminary Selection Contest) Find the coefficient of x17 in the expansion of (1++xx5720 ) . Solution. 17 5 7 20 The only way to form an x term is to gather two x and one x . Since there are C2 =190 ways to choose two x5 from the 20 multiplicands and 18 ways to choose one x7 from the remaining 18 multiplicands, the answer is 190×= 18 3420 . To gain a preliminary insight into how generating functions is related to counting, let us describe the above problem in another way. Suppose there are 20 bags, each containing a $5 coin and a $7 coin. If we can use at most one coin from each bag, in how many different ways can we pay $17, assuming that all coins are distinguishable (i.e. -
Figurate Numbers
Figurate Numbers by George Jelliss June 2008 with additions November 2008 Visualisation of Numbers The visual representation of the number of elements in a set by an array of small counters or other standard tally marks is still seen in the symbols on dominoes or playing cards, and in Roman numerals. The word "calculus" originally meant a small pebble used to calculate. Bear with me while we begin with a few elementary observations. Any number, n greater than 1, can be represented by a linear arrangement of n counters. The cases of 1 or 0 counters can be regarded as trivial or degenerate linear arrangements. The counters that make up a number m can alternatively be grouped in pairs instead of ones, and we find there are two cases, m = 2.n or 2.n + 1 (where the dot denotes multiplication). Numbers of these two forms are of course known as even and odd respectively. An even number is the sum of two equal numbers, n+n = 2.n. An odd number is the sum of two successive numbers 2.n + 1 = n + (n+1). The even and odd numbers alternate. Figure 1. Representation of numbers by rows of counters, and of even and odd numbers by various, mainly symmetric, formations. The right-angled (L-shaped) formation of the odd numbers is known as a gnomon. These do not of course exhaust the possibilities. 1 2 3 4 5 6 7 8 9 n 2 4 6 8 10 12 14 2.n 1 3 5 7 9 11 13 15 2.n + 1 Triples, Quadruples and Other Forms Generalising the divison into even and odd numbers, the counters making up a number can of course also be grouped in threes or fours or indeed any nonzero number k.