2. Random Search with Complete BST
|
|
- Todd Page
- 6 years ago
- Views:
Transcription
1 Tecnical Repor: TR-BUAA-ACT-06-0 Complexiy Analysis of Random Searc wi AVL Tree Gongwei Fu, Hailong Sun Scool of Compuer Science, Beiang Universiy {FuGW, April 7, 006 TR-BUAA-ACT Inroducion AVL ree is a classical daa srucure in compuer science, wic is commonly used o solve searcing problems. Searc from e roo can acieve bes efficiency averagely. However, wen AVL is implemened in disribued sysems, ree s are disribued across nwor. In a case, if all searces sar from e roo, e roo will becomes a bolenec. A sraigforward approac o address is issue is o allow searc o sar randomly from any. We call is ind of searc random searc. In is paper, we analyze e average searc leng in e case of random searc wi AVL. In secion, we perform e analysis of average searc leng over comple BST (Binary Searc Tree). Secion 3 presens e esimaion of average searc leng of AVL random searc.. Random Searc wi Comple BST Algorim presens a recursive algorim for random searc over a BST, in wic searcing can sar randomly from any. We ave e following ree assumpions in is paper: BST is comple, e dep of wic is and e number of s is n; Te probabiliy of searcing for eac ey is equal; Te probabiliy of searcing a sars from eac is equal. - -
2 Tecnical Repor: TR-BUAA-ACT-06-0 Algorim : Searc wi BST searc (curnode, ey) { if (curnode.conains(ey)) { rurn curnode; else if (curnode.inlefsubree(ey)) { searc (curnode.lefcild(), ey); else if (curnode.inrigsubree(ey)) { searc (curnode.rigcild(), ey); else if (paren! null) { searc (curnode.paren(), ey); else rurn null; Wi e above assumpions, e following wo facs can be go: a) n, log ( n ) b) Given a roo is e enrance of searcing, e TSL (Toal Searc Leng) is: roo, subree( roo)) 3 ( ) i i i ( ) Suppose e enrance of searcing is a cerain ( > ) a lies in e level of e BST, en e arg arg is possible o locae in e 3 saded areas sown in Figure. - -
3 Tecnical Repor: TR-BUAA-ACT-06-0 pa(, roo) subree( siblingnod e) subree( siblingnod e ) subree( ) subree( ) subree( ) Case : Figure. Searcing from a in e level For all arg in e sub-ree rooed a, i.e arg subree( ), e dep of e sub-ree is. So e TSL from o all e s wiin e sub-ree is: TSL ( Case : )) ( ) ( ) For all arg on e pa from o roo, i.e. arg pa(, roo), given a ere are s on e pa, e TSL from o all e s on e pa is:, pa(, roo)) 3 4 ( )( ) ( i ) i Case 3: For all arg in e sub-ree wi a ( ) level on pa(, roo) as is paren, i.e. arg subree( ), e TSL from o all e s wiin e sub-ree is: - 3 -
4 TSL ( Tecnical Repor: TR-BUAA-ACT-06-0 )) ( ) ( ) Similarly, for all arg in e sub-ree wi a ASLAVL ( 7, 5], > 3, < level on pa(, roo) as is paren, i.e. subree ), e arg ( TSL from o all e s wiin e sub-ree is: TSL ( )) 3 ( ) ( ) I can be seen a if arg is in e sub-ree wi a ( i) level on pa(, roo) as is paren, i.e. subree ), e TSL from o all e s wiin e sub-ree is: arg ( i TSL ( )) ( i ) ( ) ( ) ( ) i i Tus, e TSL from o all e s wiin e neigboring sub-rees is:, siblingsubree( )) i subree( i )) i [( ) i ] i [( ) i ] i ( i i ) i ( i ) i ( ) i i i i ( )( ) ( ) ( ) ( ) ( ) [( ) [( ) ( )( ) ] ( )( ] ) Hence, e TSL from o all e s wiin e BST is: roo)) - 4 -
5 Tecnical Repor: TR-BUAA-ACT-06-0 TSL ( )), pa(, roo)), siblingsubree( )) ( ) ( )( ) ( ) ( ) ( )( [( ) ] [ ( ) ( ) ( ) ( 4) 4] [( 4) 4] ( 4) Ten e TSL from eac wiin e BST o all e s wiin e BST is: ) TSL [ NumberOf ( ) roo))] { {[ [ ( 4) ( 4) ] ] [ ( ) ( 4) ] [( ) ] [ ( 4) ] ( ) [( ) ] Wi our ree assumpions menioned above, we ave e average searc leng ASL: ASL TSL SearcTimes [ ( 4) ] ( ) [( ) ( ) ] ( 4) ( ) 4 5 [( ) ( ) ] ( ) Te conclusion can also be drawn roug e following approac, in wic p ) is ( e probabiliy a all e level s exis in e BST. ASL ( roo)) ) ( 4) - 5 -
6 Tecnical Repor: TR-BUAA-ACT-06-0 ASL [ p( ) ASL( )] [ ( 4) ] [ {[ ( ) ( ( 4) ( 4) ] ] ) ( ) ( 4) ] {[ [( ) ] ( 4) 4 5 [( ) ( ) ] ( ) Moreover, i is can be easily calculaed a wen <, e ASL is. 3. Analysis of Random Searc wi AVL In secion, we ave e conclusion a e average searc leng of random searc wi comple BST is rougly equal o -5. Here, we give an esimaion of average searc leng of random searc wi AVL. Te ree assumpions menioned in secion for comple BST also old for AVL ree. Te difference bween a comple BST and an AVL is a e number of leaf s in an AVL can ranges from o -. Terefore, e average searc leng will be less an a of comple BST wi e same dep. Furermore, e average searc leng sould be larger an a of comple BST wi - dep. Ten, we can conclude: ASLAVL ( 7, 5], > 3, < For example, e average searc leng of an AVL wi 00 s is larger an 7 and less an/equal o Conclusion Wen AVL ree is used in disribued compuing, searcing sould no ly sar from e roo in order o avoid sysem bolenec. We analyze e average searc leng wi comple BST, and an esimaion o average searc leng wi AVL ree is given
Additional Exercises for Chapter What is the slope-intercept form of the equation of the line given by 3x + 5y + 2 = 0?
ddiional Eercises for Caper 5 bou Lines, Slopes, and Tangen Lines 39. Find an equaion for e line roug e wo poins (, 7) and (5, ). 4. Wa is e slope-inercep form of e equaion of e line given by 3 + 5y +
More informationAsymmetry and Leverage in Conditional Volatility Models
Economerics 04,, 45-50; doi:0.3390/economerics03045 OPEN ACCESS economerics ISSN 5-46 www.mdpi.com/journal/economerics Aricle Asymmery and Leverage in Condiional Volailiy Models Micael McAleer,,3,4 Deparmen
More informationMathematics Paper- II
R Prerna Tower, Road No -, Conracors Area, Bisupur, Jamsedpur - 8, Tel - (65789, www.prernaclasses.com Maemaics Paper- II Jee Advance PART III - MATHEMATICS SECTION - : (One or more opions correc Type
More informationAsymmetry and Leverage in Conditional Volatility Models*
Asymmery and Leverage in Condiional Volailiy Models* Micael McAleer Deparmen of Quaniaive Finance Naional Tsing Hua Universiy Taiwan and Economeric Insiue Erasmus Scool of Economics Erasmus Universiy Roerdam
More informationComparison between the Discrete and Continuous Time Models
Comparison beween e Discree and Coninuous Time Models D. Sulsky June 21, 2012 1 Discree o Coninuous Recall e discree ime model Î = AIS Ŝ = S Î. Tese equaions ell us ow e populaion canges from one day o
More information158 Calculus and Structures
58 Calculus and Structures CHAPTER PROPERTIES OF DERIVATIVES AND DIFFERENTIATION BY THE EASY WAY. Calculus and Structures 59 Copyrigt Capter PROPERTIES OF DERIVATIVES. INTRODUCTION In te last capter you
More information02. MOTION. Questions and Answers
CLASS-09 02. MOTION Quesions and Answers PHYSICAL SCIENCE 1. Se moves a a consan speed in a consan direcion.. Reprase e same senence in fewer words using conceps relaed o moion. Se moves wi uniform velociy.
More informationA corporate-crime perspective on fisheries: liability rules and non-compliance
A corporae-crime perspecive on fiseries: liabiliy rules and non-compliance FRANK JENSEN, Corresponding auor Universiy of Copenagen, Deparmen of Food and Resource Economics, Roligedsvej 3, 1958 Frederiksberg
More informationCORRELATION EQUATIONS: FORCED AND FREE CONVECTION
CHAPER 0 0. Inroducion CORREAION EQUAIONS: FORCED AND FREE CONECION A ey facor in convecion is e ea e ea ransfer coefficien. Insead of deermining we deermine e ssel number, wic a dimensionless ea ransfer
More informationTHE CATCH PROCESS (continued)
THE CATCH PROCESS (coninued) In our previous derivaion of e relaionsip beween CPUE and fis abundance we assumed a all e fising unis and all e fis were spaially omogeneous. Now we explore wa appens wen
More informationCONSIDERATIONS REGARDING THE OPTIMUM DESIGN OF PRESTRESSED ELEMENTS
Bullein of e Transilvania Universiy of Braşov CIBv 5 Vol. 8 (57) Special Issue No. - 5 CONSIDERTIONS REGRDING THE OPTIU DESIGN OF PRESTRESSED ELEENTS D. PRECUPNU C. PRECUPNU bsrac: Engineering educaion
More information1 The concept of limits (p.217 p.229, p.242 p.249, p.255 p.256) 1.1 Limits Consider the function determined by the formula 3. x since at this point
MA00 Capter 6 Calculus and Basic Linear Algebra I Limits, Continuity and Differentiability Te concept of its (p.7 p.9, p.4 p.49, p.55 p.56). Limits Consider te function determined by te formula f Note
More informationLogarithmic functions
Roberto s Notes on Differential Calculus Capter 5: Derivatives of transcendental functions Section Derivatives of Logaritmic functions Wat ou need to know alread: Definition of derivative and all basic
More information7.1 Using Antiderivatives to find Area
7.1 Using Antiderivatives to find Area Introduction finding te area under te grap of a nonnegative, continuous function f In tis section a formula is obtained for finding te area of te region bounded between
More informationlecture 26: Richardson extrapolation
43 lecture 26: Ricardson extrapolation 35 Ricardson extrapolation, Romberg integration Trougout numerical analysis, one encounters procedures tat apply some simple approximation (eg, linear interpolation)
More informationStability and Bifurcation in a Neural Network Model with Two Delays
Inernaional Mahemaical Forum, Vol. 6, 11, no. 35, 175-1731 Sabiliy and Bifurcaion in a Neural Nework Model wih Two Delays GuangPing Hu and XiaoLing Li School of Mahemaics and Physics, Nanjing Universiy
More informationMath 1241 Calculus Test 1
February 4, 2004 Name Te first nine problems count 6 points eac and te final seven count as marked. Tere are 120 points available on tis test. Multiple coice section. Circle te correct coice(s). You do
More informationOur main purpose in this section is to undertake an examination of the stock
3. Caial gains ax and e sock rice volailiy Our main urose in is secion is o underake an examinaion of e sock rice volailiy by considering ow e raional seculaor s olding canges afer e ax rae on caial gains
More informationFunction Composition and Chain Rules
Function Composition and s James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 8, 2017 Outline 1 Function Composition and Continuity 2 Function
More information(a) At what number x = a does f have a removable discontinuity? What value f(a) should be assigned to f at x = a in order to make f continuous at a?
Solutions to Test 1 Fall 016 1pt 1. Te grap of a function f(x) is sown at rigt below. Part I. State te value of eac limit. If a limit is infinite, state weter it is or. If a limit does not exist (but is
More informationTaylor Series and the Mean Value Theorem of Derivatives
1 - Taylor Series and te Mean Value Teorem o Derivatives Te numerical solution o engineering and scientiic problems described by matematical models oten requires solving dierential equations. Dierential
More informationSection 15.6 Directional Derivatives and the Gradient Vector
Section 15.6 Directional Derivatives and te Gradient Vector Finding rates of cange in different directions Recall tat wen we first started considering derivatives of functions of more tan one variable,
More informationANALYSIS OF LINEAR AND NONLINEAR EQUATION FOR OSCILLATING MOVEMENT
УД 69486 Anna Macurová arol Vasilko Faculy of Manufacuring Tecnologies Tecnical Universiy of ošice Prešov Slovakia ANALYSIS OF LINEAR AND NONLINEAR EQUATION FOR OSCILLATING MOVEMENT Macurová Anna Vasilko
More informationApproximating the Powers with Large Exponents and Bases Close to Unit, and the Associated Sequence of Nested Limits
In. J. Conemp. Ma. Sciences Vol. 6 211 no. 43 2135-2145 Approximaing e Powers wi Large Exponens and Bases Close o Uni and e Associaed Sequence of Nesed Limis Vio Lampre Universiy of Ljubljana Slovenia
More informationThe total error in numerical differentiation
AMS 147 Computational Metods and Applications Lecture 08 Copyrigt by Hongyun Wang, UCSC Recap: Loss of accuracy due to numerical cancellation A B 3, 3 ~10 16 In calculating te difference between A and
More informationDerivation Of The Schwarzschild Radius Without General Relativity
Derivation Of Te Scwarzscild Radius Witout General Relativity In tis paper I present an alternative metod of deriving te Scwarzscild radius of a black ole. Te metod uses tree of te Planck units formulas:
More information3.1 Extreme Values of a Function
.1 Etreme Values of a Function Section.1 Notes Page 1 One application of te derivative is finding minimum and maimum values off a grap. In precalculus we were only able to do tis wit quadratics by find
More informationOutline. simplest HMM (1) simple HMMs? simplest HMM (2) Parameter estimation for discrete hidden Markov models
Oulie Parameer esimaio for discree idde Markov models Juko Murakami () ad Tomas Taylor (2). Vicoria Uiversiy of Welligo 2. Arizoa Sae Uiversiy Descripio of simple idde Markov models Maximum likeliood esimae
More informationPrecalculus Test 2 Practice Questions Page 1. Note: You can expect other types of questions on the test than the ones presented here!
Precalculus Test 2 Practice Questions Page Note: You can expect oter types of questions on te test tan te ones presented ere! Questions Example. Find te vertex of te quadratic f(x) = 4x 2 x. Example 2.
More informationOn two general nonlocal differential equations problems of fractional orders
Malaya Journal of Maemaik, Vol. 6, No. 3, 478-482, 28 ps://doi.org/.26637/mjm63/3 On wo general nonlocal differenial equaions problems of fracional orders Abd El-Salam S. A. * and Gaafar F. M.2 Absrac
More informationThe Verlet Algorithm for Molecular Dynamics Simulations
Cemistry 380.37 Fall 2015 Dr. Jean M. Standard November 9, 2015 Te Verlet Algoritm for Molecular Dynamics Simulations Equations of motion For a many-body system consisting of N particles, Newton's classical
More informationA = h w (1) Error Analysis Physics 141
Introduction In all brances of pysical science and engineering one deals constantly wit numbers wic results more or less directly from experimental observations. Experimental observations always ave inaccuracies.
More informationIntegral Calculus, dealing with areas and volumes, and approximate areas under and between curves.
Calculus can be divided into two ke areas: Differential Calculus dealing wit its, rates of cange, tangents and normals to curves, curve sketcing, and applications to maima and minima problems Integral
More informationLIMITS AND DERIVATIVES CONDITIONS FOR THE EXISTENCE OF A LIMIT
LIMITS AND DERIVATIVES Te limit of a function is defined as te value of y tat te curve approaces, as x approaces a particular value. Te limit of f (x) as x approaces a is written as f (x) approaces, as
More informationChapters 19 & 20 Heat and the First Law of Thermodynamics
Capters 19 & 20 Heat and te First Law of Termodynamics Te Zerot Law of Termodynamics Te First Law of Termodynamics Termal Processes Te Second Law of Termodynamics Heat Engines and te Carnot Cycle Refrigerators,
More informationCombining functions: algebraic methods
Combining functions: algebraic metods Functions can be added, subtracted, multiplied, divided, and raised to a power, just like numbers or algebra expressions. If f(x) = x 2 and g(x) = x + 2, clearly f(x)
More informationVolume 29, Issue 3. Existence of competitive equilibrium in economies with multi-member households
Volume 29, Issue 3 Existence of competitive equilibrium in economies wit multi-member ouseolds Noriisa Sato Graduate Scool of Economics, Waseda University Abstract Tis paper focuses on te existence of
More informationDerivative at a point
Roberto s Notes on Differential Calculus Capter : Definition of derivative Section Derivative at a point Wat you need to know already: Te concept of liit and basic etods for coputing liits. Wat you can
More informationRunge-Kutta methods. With orders of Taylor methods yet without derivatives of f (t, y(t))
Runge-Kutta metods Wit orders of Taylor metods yet witout derivatives of f (t, y(t)) First order Taylor expansion in two variables Teorem: Suppose tat f (t, y) and all its partial derivatives are continuous
More informationKalman filtering for maximum likelihood estimation given corrupted observations.
alman filering maimum likelihood esimaion given corruped observaions... Holmes Naional Marine isheries Service Inroducion he alman filer is used o eend likelihood esimaion o cases wih hidden saes such
More informationIntroduction to Derivatives
Introduction to Derivatives 5-Minute Review: Instantaneous Rates and Tangent Slope Recall te analogy tat we developed earlier First we saw tat te secant slope of te line troug te two points (a, f (a))
More informationExercises for numerical differentiation. Øyvind Ryan
Exercises for numerical differentiation Øyvind Ryan February 25, 2013 1. Mark eac of te following statements as true or false. a. Wen we use te approximation f (a) (f (a +) f (a))/ on a computer, we can
More informationFuzzy Laplace Transforms for Derivatives of Higher Orders
Maemaical Teory and Modeling ISSN -58 (Paper) ISSN 5-5 (Online) Vol, No, 1 wwwiiseorg Fuzzy Laplace Transforms for Derivaives of Higer Orders Absrac Amal K Haydar 1 *and Hawrra F Moammad Ali 1 College
More informationThe Priestley-Chao Estimator
Te Priestley-Cao Estimator In tis section we will consider te Pristley-Cao estimator of te unknown regression function. It is assumed tat we ave a sample of observations (Y i, x i ), i = 1,..., n wic are
More information1. Consider the trigonometric function f(t) whose graph is shown below. Write down a possible formula for f(t).
. Consider te trigonometric function f(t) wose grap is sown below. Write down a possible formula for f(t). Tis function appears to be an odd, periodic function tat as been sifted upwards, so we will use
More informationDEFINITION OF A DERIVATIVE
DEFINITION OF A DERIVATIVE Section 2.1 Calculus AP/Dual, Revised 2017 viet.dang@umbleisd.net 2.1: Definition of a Derivative 1 DEFINITION A. Te derivative of a function allows you to find te SLOPE OF THE
More informationHigher Order Difference Schemes for Heat Equation
Available a p://pvau.edu/aa Appl. Appl. Ma. ISSN: 9-966 Vol., Issue (Deceber 009), pp. 6 7 (Previously, Vol., No. ) Applicaions and Applied Maeaics: An Inernaional Journal (AAM) Higer Order Difference
More informationWe name Functions f (x) or g(x) etc.
Section 2 1B: Function Notation Bot of te equations y 2x +1 and y 3x 2 are functions. It is common to ave two or more functions in terms of x in te same problem. If I ask you wat is te value for y if x
More informationMethod For Solving Fuzzy Integro-Differential Equation By Using Fuzzy Laplace Transformation
INERNAIONAL JOURNAL OF SCIENIFIC & ECHNOLOGY RESEARCH VOLUME 3 ISSUE 5 May 4 ISSN 77-866 Meod For Solving Fuzzy Inegro-Differenial Equaion By Using Fuzzy Laplace ransformaion Manmoan Das Danji alukdar
More informationLecture 21. Numerical differentiation. f ( x+h) f ( x) h h
Lecture Numerical differentiation Introduction We can analytically calculate te derivative of any elementary function, so tere migt seem to be no motivation for calculating derivatives numerically. However
More informationOrder of Accuracy. ũ h u Ch p, (1)
Order of Accuracy 1 Terminology We consider a numerical approximation of an exact value u. Te approximation depends on a small parameter, wic can be for instance te grid size or time step in a numerical
More informationA Study of Impedance Control in Flexible Printed Circuit (FPC)
A Sudy of Impedance Conrol in Flexible Prined Circui (FPC) Tomonari Yokoyama 1, Hiroio Waanabe 1, Yukiaru Sakaguci 1, Haruo Miyazawa 1, Yosiaru Unami 1 and Nobuyuki Sadakaa 1 Ordinary, requiremens for
More informationMTH-112 Quiz 1 Name: # :
MTH- Quiz Name: # : Please write our name in te provided space. Simplif our answers. Sow our work.. Determine weter te given relation is a function. Give te domain and range of te relation.. Does te equation
More informationStochastic Reliability Analysis of Two Identical Cold Standby Units with Geometric Failure & Repair Rates
DOI: 0.545/mjis.07.500 Socasic Reliabiliy Analysis of Two Idenical Cold Sandby Unis wi Geomeric Failure & Repair Raes NITIN BHARDWAJ AND BHUPENDER PARASHAR Email: niinbardwaj@jssaen.ac.in; parasar_b@jssaen.ac.in
More informationContinuity. Example 1
Continuity MATH 1003 Calculus and Linear Algebra (Lecture 13.5) Maoseng Xiong Department of Matematics, HKUST A function f : (a, b) R is continuous at a point c (a, b) if 1. x c f (x) exists, 2. f (c)
More informationChapter 2. Limits and Continuity 16( ) 16( 9) = = 001. Section 2.1 Rates of Change and Limits (pp ) Quick Review 2.1
Capter Limits and Continuity Section. Rates of Cange and Limits (pp. 969) Quick Review..... f ( ) ( ) ( ) 0 ( ) f ( ) f ( ) sin π sin π 0 f ( ). < < < 6. < c c < < c 7. < < < < < 8. 9. 0. c < d d < c
More informationSFU UBC UNBC Uvic Calculus Challenge Examination June 5, 2008, 12:00 15:00
SFU UBC UNBC Uvic Calculus Callenge Eamination June 5, 008, :00 5:00 Host: SIMON FRASER UNIVERSITY First Name: Last Name: Scool: Student signature INSTRUCTIONS Sow all your work Full marks are given only
More informationThe Quantum Theory of Atoms and Molecules: The Schrodinger equation. Hilary Term 2008 Dr Grant Ritchie
e Quanum eory of Aoms and Molecules: e Scrodinger equaion Hilary erm 008 Dr Gran Ricie An equaion for maer waves? De Broglie posulaed a every paricles as an associaed wave of waveleng: / p Wave naure of
More informationA Method for Implementing a Probabilistic Model as a Relational Database
A Meod for Implemening a Probabilisic Model as a Relaional Daabase Absrac Tis paper discusses a meod for implemening a probabilisic inference sysem based on an exended relaional daa model. Tis model provides
More informationContinuity and Differentiability Worksheet
Continuity and Differentiability Workseet (Be sure tat you can also do te grapical eercises from te tet- Tese were not included below! Typical problems are like problems -3, p. 6; -3, p. 7; 33-34, p. 7;
More informationThe Derivative as a Function
Section 2.2 Te Derivative as a Function 200 Kiryl Tsiscanka Te Derivative as a Function DEFINITION: Te derivative of a function f at a number a, denoted by f (a), is if tis limit exists. f (a) f(a + )
More informationLearning based super-resolution land cover mapping
earning based super-resolution land cover mapping Feng ing, Yiang Zang, Giles M. Foody IEEE Fellow, Xiaodong Xiuua Zang, Siming Fang, Wenbo Yun Du is work was supported in part by te National Basic Researc
More information2.8 The Derivative as a Function
.8 Te Derivative as a Function Typically, we can find te derivative of a function f at many points of its domain: Definition. Suppose tat f is a function wic is differentiable at every point of an open
More informationû s L u t 0 s a ; i.e., û s 0
Te Hille-Yosida Teorem We ave seen a wen e absrac IVP is uniquely solvable en e soluion operaor defines a semigroup of bounded operaors. We ave no ye discussed e condiions under wic e IVP is uniquely solvable.
More informationLab 6 Derivatives and Mutant Bacteria
Lab 6 Derivatives and Mutant Bacteria Date: September 27, 20 Assignment Due Date: October 4, 20 Goal: In tis lab you will furter explore te concept of a derivative using R. You will use your knowledge
More informationRandom Walk with Anti-Correlated Steps
Random Walk wih Ani-Correlaed Seps John Noga Dirk Wagner 2 Absrac We conjecure he expeced value of random walks wih ani-correlaed seps o be exacly. We suppor his conjecure wih 2 plausibiliy argumens and
More informationUniversity Mathematics 2
University Matematics 2 1 Differentiability In tis section, we discuss te differentiability of functions. Definition 1.1 Differentiable function). Let f) be a function. We say tat f is differentiable at
More informationV.sin. AIM: Investigate the projectile motion of a rigid body. INTRODUCTION:
EXPERIMENT 5: PROJECTILE MOTION: AIM: Invesigae e projecile moion of a rigid body. INTRODUCTION: Projecile moion is defined as e moion of a mass from op o e ground in verical line, or combined parabolic
More informationSome Review Problems for First Midterm Mathematics 1300, Calculus 1
Some Review Problems for First Midterm Matematics 00, Calculus. Consider te trigonometric function f(t) wose grap is sown below. Write down a possible formula for f(t). Tis function appears to be an odd,
More informationQuantum Numbers and Rules
OpenStax-CNX module: m42614 1 Quantum Numbers and Rules OpenStax College Tis work is produced by OpenStax-CNX and licensed under te Creative Commons Attribution License 3.0 Abstract Dene quantum number.
More informationAn Approximation to the Solution of the Brusselator System by Adomian Decomposition Method and Comparing the Results with Runge-Kutta Method
Int. J. Contemp. Mat. Sciences, Vol. 2, 27, no. 2, 983-989 An Approximation to te Solution of te Brusselator System by Adomian Decomposition Metod and Comparing te Results wit Runge-Kutta Metod J. Biazar
More informationCalculus I Homework: The Derivative as a Function Page 1
Calculus I Homework: Te Derivative as a Function Page 1 Example (2.9.16) Make a careful sketc of te grap of f(x) = sin x and below it sketc te grap of f (x). Try to guess te formula of f (x) from its grap.
More informationPolynomials 3: Powers of x 0 + h
near small binomial Capter 17 Polynomials 3: Powers of + Wile it is easy to compute wit powers of a counting-numerator, it is a lot more difficult to compute wit powers of a decimal-numerator. EXAMPLE
More informationSin, Cos and All That
Sin, Cos and All Tat James K. Peterson Department of Biological Sciences and Department of Matematical Sciences Clemson University Marc 9, 2017 Outline Sin, Cos and all tat! A New Power Rule Derivatives
More informationGeorey E. Hinton. University oftoronto. Technical Report CRG-TR February 22, Abstract
Parameer Esimaion for Linear Dynamical Sysems Zoubin Ghahramani Georey E. Hinon Deparmen of Compuer Science Universiy oftorono 6 King's College Road Torono, Canada M5S A4 Email: zoubin@cs.orono.edu Technical
More informationMath 31A Discussion Notes Week 4 October 20 and October 22, 2015
Mat 3A Discussion Notes Week 4 October 20 and October 22, 205 To prepare for te first midterm, we ll spend tis week working eamples resembling te various problems you ve seen so far tis term. In tese notes
More informationUNIT #6 EXPONENTS, EXPONENTS, AND MORE EXPONENTS REVIEW QUESTIONS
Answer Key Name: Date: UNIT # EXPONENTS, EXPONENTS, AND MORE EXPONENTS REVIEW QUESTIONS Part I Questions. Te epression 0 can be simpliied to () () 0 0. Wic o te ollowing is equivalent to () () 8 8? 8.
More information1 1. Rationalize the denominator and fully simplify the radical expression 3 3. Solution: = 1 = 3 3 = 2
MTH - Spring 04 Exam Review (Solutions) Exam : February 5t 6:00-7:0 Tis exam review contains questions similar to tose you sould expect to see on Exam. Te questions included in tis review, owever, are
More informationMA119-A Applied Calculus for Business Fall Homework 4 Solutions Due 9/29/ :30AM
MA9-A Applied Calculus for Business 006 Fall Homework Solutions Due 9/9/006 0:0AM. #0 Find te it 5 0 + +.. #8 Find te it. #6 Find te it 5 0 + + = (0) 5 0 (0) + (0) + =.!! r + +. r s r + + = () + 0 () +
More informationDefinition of the Derivative
Te Limit Definition of te Derivative Tis Handout will: Define te limit grapically and algebraically Discuss, in detail, specific features of te definition of te derivative Provide a general strategy of
More informationThe Krewe of Caesar Problem. David Gurney. Southeastern Louisiana University. SLU 10541, 500 Western Avenue. Hammond, LA
Te Krewe of Caesar Problem David Gurney Souteastern Louisiana University SLU 10541, 500 Western Avenue Hammond, LA 7040 June 19, 00 Krewe of Caesar 1 ABSTRACT Tis paper provides an alternative to te usual
More informationApplied Linear Statistical Models. Simultaneous Inference Topics. Simultaneous Estimation of β 0 and β 1 Issues. Simultaneous Inference. Dr.
Applied Linear Statistical Models Simultaneous Inference Dr. DH Jones Simultaneous Inference Topics Simultaneous estimation of β 0 and β 1 Bonferroni Metod Simultaneous estimation of several mean responses
More informationThe derivative function
Roberto s Notes on Differential Calculus Capter : Definition of derivative Section Te derivative function Wat you need to know already: f is at a point on its grap and ow to compute it. Wat te derivative
More informationEfficient algorithms for for clone items detection
Efficient algoritms for for clone items detection Raoul Medina, Caroline Noyer, and Olivier Raynaud Raoul Medina, Caroline Noyer and Olivier Raynaud LIMOS - Université Blaise Pascal, Campus universitaire
More informationDYNAMIC ECONOMETRIC MODELS Vol. 7 Nicolaus Copernicus University Toruń Piotr Fiszeder Nicolaus Copernicus University in Toruń
DYNAMIC ECONOMETRIC MODELS Vol. 7 Nicolaus Copernicus Universiy Toruń 006 Pior Fiszeder Nicolaus Copernicus Universiy in Toruń Consequences of Congruence for GARCH Modelling. Inroducion In 98 Granger formulaed
More informationSymbolic-Numeric Sparse Interpolation of Multivariate Polynomials
Symbolic-Numeric Sparse Inerpolaion o Mulivariae Polynomials Mark Giesbrech George Labahn Wen-shin Lee School o Compuer Science Universiy o Waerloo Approimae inerpolaion o polynomials Suppose we can sample
More informationNCCI: Simple methods for second order effects in portal frames
NCC: Simple metods for second order effects in portal frames NCC: Simple metods for second order effects in portal frames NCC: Simple metods for second order effects in portal frames Tis NCC presents information
More informationChapter 2 Limits and Continuity
4 Section. Capter Limits and Continuity Section. Rates of Cange and Limits (pp. 6) Quick Review.. f () ( ) () 4 0. f () 4( ) 4. f () sin sin 0 4. f (). 4 4 4 6. c c c 7. 8. c d d c d d c d c 9. 8 ( )(
More informationInvestigating Euler s Method and Differential Equations to Approximate π. Lindsay Crowl August 2, 2001
Investigating Euler s Metod and Differential Equations to Approximate π Lindsa Crowl August 2, 2001 Tis researc paper focuses on finding a more efficient and accurate wa to approximate π. Suppose tat x
More informationSection 3.1: Derivatives of Polynomials and Exponential Functions
Section 3.1: Derivatives of Polynomials and Exponential Functions In previous sections we developed te concept of te derivative and derivative function. Te only issue wit our definition owever is tat it
More informationProfit Based Unit Commitment in Deregulated Electricity Markets Using A Hybrid Lagrangian Relaxation - Particle Swarm Optimization Approach
Profit Based Unit Commitment in Deregulated Electricity Markets Using A Hybrid Lagrangian Relaxation - Particle Swarm Optimization Approac Adline K. Bikeri, Cristoper M. Maina and Peter K. Kiato Proceedings
More informationPre-lab Quiz/PHYS 224 Earth s Magnetic Field. Your name Lab section
Pre-lab Quiz/PHYS 4 Eart s Magnetic Field Your name Lab section 1. Wat do you investigate in tis lab?. For a pair of Helmoltz coils described in tis manual and sown in Figure, r=.15 m, N=13, I =.4 A, wat
More informationProbabilistic Graphical Models Homework 1: Due January 29, 2014 at 4 pm
Probabilistic Grapical Models 10-708 Homework 1: Due January 29, 2014 at 4 pm Directions. Tis omework assignment covers te material presented in Lectures 1-3. You must complete all four problems to obtain
More information. h I B. Average velocity can be interpreted as the slope of a tangent line. I C. The difference quotient program finds the exact value of f ( a)
Capter Review Packet (questions - ) KEY. In eac case determine if te information or statement is correct (C) or incorrect (I). If it is incorrect, include te correction. f ( a ) f ( a) I A. represents
More information7 Semiparametric Methods and Partially Linear Regression
7 Semiparametric Metods and Partially Linear Regression 7. Overview A model is called semiparametric if it is described by and were is nite-dimensional (e.g. parametric) and is in nite-dimensional (nonparametric).
More informationINTRODUCTION TO CALCULUS LIMITS
Calculus can be divided into two ke areas: INTRODUCTION TO CALCULUS Differential Calculus dealing wit its, rates of cange, tangents and normals to curves, curve sketcing, and applications to maima and
More informationContinuity and Differentiability of the Trigonometric Functions
[Te basis for te following work will be te definition of te trigonometric functions as ratios of te sides of a triangle inscribed in a circle; in particular, te sine of an angle will be defined to be te
More information= 0 and states ''hence there is a stationary point'' All aspects of the proof dx must be correct (c)
Paper 1: Pure Matematics 1 Mark Sceme 1(a) (i) (ii) d d y 3 1x 4x x M1 A1 d y dx 1.1b 1.1b 36x 48x A1ft 1.1b Substitutes x = into teir dx (3) 3 1 4 Sows d y 0 and states ''ence tere is a stationary point''
More informationChapter 4 Derivatives [ ] = ( ) ( )= + ( ) + + = ()= + ()+ Exercise 4.1. Review of Prerequisite Skills. 1. f. 6. d. 4. b. lim. x x. = lim = c.
Capter Derivatives Review of Prerequisite Skills. f. p p p 7 9 p p p Eercise.. i. ( a ) a ( b) a [ ] b a b ab b a. d. f. 9. c. + + ( ) ( + ) + ( + ) ( + ) ( + ) + + + + ( ) ( + ) + + ( ) ( ) ( + ) + 7
More informationAVL trees. AVL trees
Dnamic set DT dnamic set DT is a structure tat stores a set of elements. Eac element as a (unique) ke and satellite data. Te structure supports te following operations. Searc(S, k) Return te element wose
More information