082-Engineering-Mathematics-Anthony-Croft-Robert-Davison-Martin-Hargreaves-James-Flint-Edisi-5-2017

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790 Chapter 24 The Fourier transformWhen we use this transform to approximate the Fourier transform of the function f (t)sampled at intervalsT, it follows from Equation (24.13) that we must multiply by thefactor T to obtain our approximation. An example of this is given in the nextsection.24.11 USINGTHED.F.T.TOESTIMATEAFOURIERTRANSFORMOne application of the d.f.t. is to estimate the continuous Fourier transform of a signalf (t). The following example shows how this can bedone.Example24.22 The signal f (t) = u(t)e −2t , where u(t) is the unit step function, is shown inFigure 24.18(a). Its Fourier transform, which can be found from Table 24.1, isF(ω) = 1 and a graph of |F(ω)|isshown inFigure 24.18(b).2+jωSuppose we obtain 16 sample values of f (t) at intervals ofT = 0.1 fromt = 0 tot = 1.5.(a) Obtain the d.f.t. of the sampled sequence.(b) Usethe d.f.t. toestimatethe trueFourier transform values.(c) Plot a graph tocompare values of |F[k]| and |F(ω)|.Solution (a) If f (t) =u(t)e −2t is sampled att =nT, that ist = 0,0.1,0.2,...,1.5, we obtainthe sequence f[n] = e −2nT = e −0.2n forn = 0,1,2,...,15. This is the sequencegiven inthe second column of Table 24.2.(b) Thecalculationofthed.f.t.isfartoolaborioustobedonebyhand.Insteadwehaveused the MATLAB ® command fft() to do the calculation and the results, F[k],have been placed inthe third column.(c) From Section 24.10 we know that the d.f.t. samples at intervals of 2π in the frequencydomain.SoforcomparisonthefourthcolumnshowsthetruevaluesofF(ω)NT1 f(t) = u(t)e – 2 t t4 + 2 30u F( v) u =1v0.5(a)1(b)Figure24.18The signal f (t) =u(t)e −2t and itsFourier transform.–30v
24.11 Using the d.f.t.to estimate a Fourier transform 791Table24.2n,k f[n] = e −0.2n F[k] F(ω k ) 0.1F[k]0 1.0000 5.2918 0.5000 0.52921 0.8187 1.4835 −1.9082j 0.1030 −0.2022j 0.1484 −0.1908j2 0.6703 0.7882 −1.0837j 0.0304 −0.1196j 0.0788 −0.1084j3 0.5488 0.6311 −0.6952j 0.0140 −0.0825j 0.0631 −0.0695j4 0.4493 0.5743 −0.4702j 0.0080 −0.0626j 0.0574 −0.0470j5 0.3679 0.5485 −0.3159j 0.0051 −0.0504j 0.0548 −0.0316j6 0.3012 0.5355 −0.1964j 0.0036 −0.0421j 0.0536 −0.0196j7 0.2466 0.5293 −0.0944j 0.0026 −0.0362j 0.0529 −0.0094j8 0.2019 0.5274 0.0020 −0.0317j 0.05279 0.1653 0.5293 +0.0944j 0.0016 −0.0282j 0.0529 +0.0094j10 0.1353 0.5355 +0.1964j 0.0013 −0.0254j 0.0536 +0.0196j11 0.1108 0.5485 +0.3159j 0.0011 −0.0231j 0.0548 +0.0316j12 0.0907 0.5743 +0.4702j 0.0009 −0.0212j 0.0574 +0.0470j13 0.0743 0.6311 +0.6952j 0.0008 −0.0196j 0.0631 +0.0695j14 0.0608 0.7882 +1.0837j 0.0007 −0.0182j 0.0788 +0.1084j15 0.0498 1.4835 +1.9082j 0.0006 −0.0170j 0.1484 +0.1908jalso sampled at intervals of 2π . Recall that to obtain an estimate of the FourierNTtransform of f (t) we must multiply the d.f.t. values byT = 0.1. This is shown inthe fifth column of the table.Figure24.19showsgraphsof |0.1F[k]|and |F(ω)|.Valuesof |F[k]|obtainedbeyondk = 8aremirrorimagesoftheearliervalues.ThisisbecauseF[N−k] =F[k]asprovedinQuestion5inExercises24.9.1.Thisisaphenomenon ofthed.f.t.andarisesbecauseofitsperiodicityandsymmetryproperties,furtherdetailsofwhicharebeyondthescopeof this book. The interested reader is referred to a text on signal processing for furtherdetails.0.60.50.4F ( k) = F0.3(2 pku v uN T )0.1uF[k]u0.20.10 2 4 6 8 10 12 14kFigure24.19Comparisonoftruevalues ofaFouriertransformand approximate values obtainedusingad.f.t.
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ENGINEERINGMATHEMATICSA Foundation
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At Pearson, we have a simple missio
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PEARSONEDUCATIONLIMITEDEdinburghGat
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ContentsPrefaceAcknowledgementsxvii
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Contents ix8.3 Addition,subtraction
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Contents xiChapter17 Numericalinteg
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Contents xiiiChapter24 TheFouriertr
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Contents xvAppendixI Representing a
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PrefaceAudienceThis book has been w
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AcknowledgementsWearegratefultothef
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1 ReviewofalgebraictechniquesConten
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1.2 Laws of indices 3So6 2 6 3 =6 5
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1.2 Laws of indices 5(c)(d)x 9x 5 =
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1.2 Laws of indices 71.2.4 Multiple
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1.2 Laws of indices 9Similarly(2 1/
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1.3 Number bases 11Solutions1 (a) 8
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1.3 Number bases 13giving83=64+16+3
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1.3 Number bases 15Example1.16 Conv
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1.3 Number bases 17Table1.4isusedto
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1.3 Number bases 19The display show
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1.4 Polynomial equations 21Example1
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1.4 Polynomial equations 23We now i
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so thatβ=−13Bycomparing coeffici
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1.5.1 Properandimproperfractions1.5
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1.5 Algebraic fractions 29(b) Facto
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1.5 Algebraic fractions 31and4x +2
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1.6 Solution of inequalities 33(g)(
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1.6 Solution of inequalities 35Exam
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1.6 Solution of inequalities 37Case
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1.7 Partial fractions 391.7 PARTIAL
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1.7 Partial fractions 41Thus we hav
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1.7 Partial fractions 43Solution Th
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1.7 Partial fractions 45EXERCISES1.
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1.8 Summation notation 47Engineerin
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1.8 Summation notation 49thecircuit
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Review exercises 1 513 Removethe br
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Review exercises 1 53[ ((d) 3 z −
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2.2 Numbers and intervals 55in orde
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2.3 Basic concepts of functions 57f
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2.3 Basic concepts of functions 59s
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2.3 Basic concepts of functions 61b
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2.3 Basic concepts of functions 63E
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2.3 Basic concepts of functions 65f
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2.3 Basic concepts of functions 67T
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2.3 Basic concepts of functions 691
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2.4 Review of some common engineeri
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2.4.2 Rationalfunctions2.4 Review o
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Table2.2Values ofa x fora = 0.5, 2
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2.4.4 Logarithmfunctions2.4 Review
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Review exercises 2 113REVIEWEXERCIS
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3 ThetrigonometricfunctionsContents
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Note thattanθ = BCAB = BCAC × ACA
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3.3 The trigonometric ratios 119yyB
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3.4 The sine, cosine and tangent fu
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3.5 The sincxfunction 123EXERCISES3
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3.6 Trigonometric identities 125ors
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3.6 Trigonometric identities 127Exa
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3.6 Trigonometric identities 129Exa
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3.7 Modelling waves using sint and
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3.8 Trigonometric equations 145sin
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3.8 Trigonometric equations 147tan
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Usingascientific calculator wehavez
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Review exercises 3 1516 Simplify th
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Review exercises 3 153(d) 1.581sin(
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4.2 Cartesian coordinate system --
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4.3 Cartesian coordinate system --
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4.4 Polar coordinates 1594.4 POLARC
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4.4 Polar coordinates 161yOurxFigur
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4.5 Some simple polar curves 163EXE
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4.5 Some simple polar curves 165uAn
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4.6 Cylindrical polar coordinates 1
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4.6 Cylindrical polar coordinates 1
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4.7 Spherical polar coordinates 171
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Review exercises 4 173zzFeeding lin
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5 DiscretemathematicsContents 5.1 I
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5.2 Set theory 177Example5.1 Useset
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5.2 Set theory 179EMNM fNfFigure5.2
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5.2 Set theory 181someelementsinA.W
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5.3 Logic 183CDCD(a)(b)CDCD(c)(d)(e
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5.4 Boolean algebra 185ABA . BFigur
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5.4 Boolean algebra 187Table5.12Tru
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5.4 Boolean algebra 189However, we
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5.4 Boolean algebra 191S0Stage0A0 B
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5.4 Boolean algebra 193V DDPMOSQ1DD
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5.4 Boolean algebra 195(d) A ·B·(
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Review exercises 5 19712 (a) A·B+A
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Review exercises 5 1997 (a) (A·B)
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6.2 Sequences 2016.2 SEQUENCESAsequ
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6.2 Sequences 203sin t1x[k]1- 3p-2p
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6.2 Sequences 205Ageneralgeometricp
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6.2 Sequences 207can sensibly letk
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6.3 Series 20913 ±12814 315 016 (a
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6.3.2 Sumofafinitegeometricseries6.
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6.3 Series 213whereS ∞is known as
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6.4 The binomial theorem 215Example
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6.4 The binomial theorem 217EXERCIS
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6.6 Sequences arising from the iter
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6.6 Sequences arising from the iter
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Review exercises 6 22315 (a) Write
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7.2 Vectors and scalars: basic conc
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yjOirFigure7.19Thex--y plane withpo
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7.3 Cartesian components 235Solutio
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7.3 Cartesian components 237Enginee
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7.3 Cartesian components 2393 Ifa=4
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7.5 The scalar product 241OEFigure7
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7.5 The scalar product 243Example7.
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----------7.5 The scalar product 24
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7.6 The vector product 247a 3 bubPl
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7.6 The vector product 249The k com
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7.6 The vector product 251Engineeri
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7.7 Vectors ofndimensions 253andH =
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Review exercises 7 255EXERCISES7.71
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8 MatrixalgebraContents 8.1 Introdu
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8.3 Addition, subtraction and multi
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Example8.8 IfB =( ) 123andC=456⎛
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8.4 Using matrices in the translati
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8.4 Using matrices in the translati
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8.5 Some special matrices 271V new=
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Example8.18 IfA =Solution We haveA
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8.6.1 FindingtheinverseofamatrixFor
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8.6 The inverse of a 2 × 2 matrix
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8.7 Determinants 279In addition to
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8.8 The inverse of a 3 × 3 matrix
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8.9 Application to the solution of
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8.9 Application to the solution of
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Solution Firstconsider the equation
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8.10 Gaussian elimination 289anythi
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Eliminating the unwanted values int
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⎛R 1R 2→R 2−6R 1⎝R 3→R 3
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8.11 Eigenvalues and eigenvectors 2
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Itfollows thatso that(2−λ)(4−
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8.12 Analysis of electrical network
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8.13 Iterative techniques for the s
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8.14 Computer solutions of matrix p
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Review exercises 8 321V = [3;−6;4
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Review exercises 8 3234 (a) −8⎛
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9.2 Complex numbers 3259.2 COMPLEXN
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9.2 Complex numbers 3279.2.1 Thecom
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Similarly, wefind, by equating imag
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9.3 Operations with complex numbers
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9.5 Polar form of a complex number
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9.5.1 Multiplicationanddivisioninpo
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9.7 The exponential form of a compl
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9.7 The exponential form of a compl
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9.8 Phasors 341example, in the case
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9.8 Phasors 343Therefore,Ṽ S=ṼR
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which isclearly true,and the theore
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9.9 De Moivre’s theorem 347y25p
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9.9 De Moivre’s theorem 349Now, w
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9.10 Loci and regions of the comple
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9.10 Loci and regions of the comple
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Review exercises 9 3559 Sketch the
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10.2 Graphical approach to differen
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10.3 Limits and continuity 359f (t)
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10.3 Limits and continuity 361Theli
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10.4 Rate of change at a specific p
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10.5 Rate of change at a general po
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10.6 Existence of derivatives 371x
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10.7 Common derivatives 373Table10.
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10.8 Differentiation as a linear op
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Review exercises 10 385REVIEWEXERCI
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11.2 Rules of differentiation 387Th
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11.2 Rules of differentiation 389Th
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(b) Ify = ln(1 −t),theny ′ =
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11.3 Parametric, implicit and logar
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11.4 Higher derivatives 401Example1
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11.4 Higher derivatives 403yCByCAyB
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Review exercises 11 405Solutions1 (
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12.2 Maximum points and minimum poi
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12.3 Points of inflexion 415Solutio
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12.3 Points of inflexion 417y ′ =
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12.4 The Newton--Raphson method for
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12.4 The Newton--Raphson method for
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12.5 Differentiation of vectors 423
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Solution (a) Ifa = 3t 2 i +cos2tj,
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13.2 Elementary integration 42913.2
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13.2 Elementary integration 431Tabl
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Solution (a)sinx+cosx(j)2(k) 2t −
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13.2 Elementary integration 435Engi
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13.2 Elementary integration 4374.00
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Therefore,∫∫ 1sinmtsinnt dt = {
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13.2 Elementary integration 4412 (a
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13.3 Definite and indefinite integr
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Review exercises 13 4536716438 (a)
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Review exercises 13 45522 Calculate
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14 TechniquesofintegrationContents
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14.2 Integration by parts 459Usingt
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Usingintegration by parts we have
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14.3 Integration by substitution 46
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14.3 Integration by substitution 46
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14.4 Integration using partial frac
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Review exercises 14 469∫ π/3(b)
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15 ApplicationsofintegrationContent
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15.2 Average value of a function 47
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15.3 Root mean square value of a fu
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15.3 Root mean square value of a fu
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Review exercises 15 479(d) 0.7071(e
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[Example16.1 Show that f (x) =xandg
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Solution (a) We use the trigonometr
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16.3 Improper integrals 485iC 1 C 2
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∫ 2either of the integrals failst
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16.4 Integral properties of the del
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16.5 Integration of piecewise conti
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16.6 Integration of vectors 49316.6
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Review exercises 16 49512 Given14 G
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17.2 Trapezium rule 497y{ {y 0 y ny
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17.2 Trapezium rule 499The differen
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yABCDE17.3 Simpson’s rule 501quad
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17.3 Simpson’s rule 503Table17.6T
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Review Exercises 17 505EXERCISES17.
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18 Taylorpolynomials,Taylorseriesan
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18.2 Linearization using first-orde
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18.2 Linearization using first-orde
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18.3 Second-order Taylor polynomial
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18.3 Second-order Taylor polynomial
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18.4 Taylor polynomials of the nth
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18.4. Taylor polynomials of the nth
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18.5 Taylor’s formula and the rem
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We know |x| < 1, and so 4x51518.5 T
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18.6 Taylor and Maclaurin series 52
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Review exercises 18 5337 (a) 0, 2,
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19.2 Basic definitions 535In engine
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19.2 Basic definitions 537Note also
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19.2 Basic definitions 539fromwhich
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19.3 First-order equations: simple
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19.4 First-order linear equations:
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and so, upon integrating,so that(co
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19.5 Second-order linear equations
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19.6 Constant coefficient equations
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thatis,β = 332The required particu
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19.7 Series solution of differentia
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19.8 Bessel’s equation and Bessel
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fromwhicha 5=− 124 a 3 = 1192 a 1
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n 5 2n 5 3n5 419.8 Bessel’s equat
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Review exercises 19 601quencies, kn
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20 OrdinarydifferentialequationsIIC
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20.2 Analogue simulation 605y iy i
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20.3 Higher order equations 607High
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20.4 State-space models 609Solution
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20.4 State-space models 611statevar
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20.4 State-space models 613R a L aT
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20.5 Numerical methods 615Combining
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20.6 Euler’s method 617and we can
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20.6 Euler’s method 619Whenx = 1,
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20.7 Improved Euler method 621Table
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20.8 Runge--Kutta method of order 4
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20.8.1 Higherorderequations20.8 Run
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21 TheLaplacetransformContents 21.1
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21.3 Laplace transforms of some com
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21.4 Properties of the Laplace tran
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(b) Usethe first shift theorem with
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21.5 Laplace transform of derivativ
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21.5 Laplace transform of derivativ
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21.6 Inverse Laplace transforms 639
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21.7 Using partial fractions to fin
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21.8 Finding the inverse Laplace tr
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21.8 Finding the inverse Laplace tr
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21.9 The convolution theorem 64721.
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21.9 Solving linear constant coeffi
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21.10 Solving linear constant coeff
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X(s)= s3 −3s 2 −4s+6s 2 (s 2
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21.11 Transfer functions 659(c) x
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21.11 Transfer functions 661R(s)G(s
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21.11 Transfer functions 663R(s) +-
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21.11 Transfer functions 665Fuel va
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21.11 Transfer functions 667u a (t)
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21.12 Poles, zeros and thesplane 66
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21.13 Laplace transforms of some sp
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21.13.2 Periodicfunctions21.13 Lapl
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Review exercises 21 6792 Find the L
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22 Differenceequationsandtheztransf
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22.2 Basic definitions 68322.2.2 Th
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22.2 Basic definitions 685an inhomo
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22.3 Rewriting difference equations
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22.4 Block diagram representation o
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22.4 Block diagram representation o
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22.5 Design of a discrete-time cont
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22.6 Numerical solution of differen
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22.6 Numerical solution of differen
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22.7 Definition of the z transform
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22.7 Definition of the z transform
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22.8 Sampling a continuous signal 7
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22.9 The relationship between the z
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22.9 The relationship between the z
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22.10 Properties of the z transform
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22.11 Inversion of z transforms 715
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22.11 Inversion of z transforms 717
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22.12 The z transform and differenc
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Review exercises 22 721(e) q[k +3]
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23.2 Periodic waveforms 72323.2 PER
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23.2 Periodic waveforms 725f(t)1f(t
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23.3 Odd and even functions 727f(t)
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23.3 Odd and even functions 729f(t)
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23.3 Odd and even functions 731the
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23.5 Fourier series 733Table23.1Som
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23.5 Fourier series 735point out th
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23.5 Fourier series 737but cos(−n
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Page 775 and 776: ̸̸̸Review exercises 23 755The va
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Page 781 and 782: 24.3 Some properties of the Fourier
Page 783 and 784: ∫ 2[ ] eSolution (a) F(ω)=3 e
Page 785 and 786: 24.3 Some properties of the Fourier
Page 787 and 788: 24.4 Spectra 767uF(v)u2-4p -3p -2p
Page 789 and 790: The t−ω duality principle 769f(t
Page 791 and 792: 24.6 Fourier transforms of some spe
Page 793 and 794: 24.7 The relationship between the F
Page 795 and 796: 24.8 Convolution and correlation 77
Page 797 and 798: and theirproduct isF(ω)G(ω) =1(1+
Page 803 and 804: 24.9 The discrete Fourier transform
Page 805 and 806: 24.9 The discrete Fourier transform
Page 807 and 808: 24.10 Derivation of the d.f.t. 787T
Page 809: (Solution ConsiderF˜ ω + 2π )for
Page 813 and 814: 24.13 Some properties of the d.f.t.
Page 815 and 816: 24.14 The discrete cosine transform
Page 821 and 822: 24.15 Discrete convolution and corr
Page 841 and 842: Review exercises 24 821REVIEWEXERCI
Page 843 and 844: 25 FunctionsofseveralvariablesConte
Page 845 and 846: 25.3 Partial derivatives 825DCAz =
Page 847 and 848: 25.3 Partial derivatives 827Enginee
Page 849 and 850: 25.4 Higher order derivatives 829
Page 851 and 852: 25.4 Higher order derivatives 831Ex
Page 853 and 854: 25.5 Partial differential equations
Page 855 and 856: 25.6 Taylor polynomials and Taylor
Page 861 and 862:
25.7 Maximum and minimum points of
Page 863 and 864:
Page 865 and 866:
Page 867 and 868:
Review exercises 25 8474 Find allfi
Page 869 and 870:
26 VectorcalculusContents 26.1 Intr
Page 871 and 872:
26.3 The gradient of a scalar field
Page 873 and 874:
(b) At (0,0,0), ∇φ =0i+3j+0k =3j
Page 875 and 876:
26.3 The gradient of a scalar field
Page 877 and 878:
26.4.1 Physicalinterpretationof ∇
Page 879 and 880:
26.5 The curl of a vector field 859
Page 881 and 882:
26.6 Combining the operators grad,
Page 883 and 884:
26.6 Combining the operators grad,
Page 885 and 886:
Equation3Review exercises 26 865cur
Page 887 and 888:
27 Lineintegralsandmultipleintegral
Page 889 and 890:
27.2 Line integrals 869SolutionThe
Page 891 and 892:
27.3 Evaluation of line integrals i
Page 893 and 894:
27.4 Evaluation of line integrals i
Page 895 and 896:
27.5 Conservative fields and potent
Page 897 and 898:
27.5 Conservative fields and potent
Page 899 and 900:
Substitutingy =x 2 and dy = 2xdx we
Page 901 and 902:
27.6 Double and triple integrals 88
Page 903 and 904:
Page 905 and 906:
Page 907 and 908:
y10GDR27.6 Double and triple integr
Page 909 and 910:
27.7 Some simple volume and surface
Page 911 and 912:
Page 913 and 914:
Page 915 and 916:
27.8 The divergence theorem and Sto
Page 917 and 918:
27.8 The divergence theorem and Sto
Page 919 and 920:
27.9 Maxwell’s equations in integ
Page 921 and 922:
Page 923 and 924:
28 ProbabilityContents 28.1 Introdu
Page 925 and 926:
28.2 Introducing probability 905Ifm
Page 927 and 928:
28.2 Introducing probability 907Eng
Page 929 and 930:
28.3 Mutually exclusive events: the
Page 931 and 932:
28.3 Mutually exclusive events: the
Page 933 and 934:
28.4 Complementary events 913EXERCI
Page 935 and 936:
28.5 Concepts from communication th
Page 937 and 938:
28.5 Concepts from communication th
Page 939 and 940:
28.6 Conditional probability: the m
Page 941 and 942:
28.6 Conditional probability: the m
Page 943 and 944:
P(A ∩C) =P(C ∩A) =P(C)P(A|C)P(A
Page 945 and 946:
28.7 Independent events 9255 Compon
Page 947 and 948:
28.7 Independent events 927Solution
Page 949 and 950:
28.7 Independent events 929E 1,E 2a
Page 951 and 952:
Review exercises 28 931(d) A compon
Page 953 and 954:
29 Statisticsandprobabilitydistribu
Page 955 and 956:
29.3 Probability distributions -- d
Page 957 and 958:
29.4 Probability density functions
Page 959 and 960:
29.5 Mean value 939Example29.3 Find
Page 961 and 962:
29.6 Standard deviation 94129.6 STA
Page 963 and 964:
29.7 Expected value of a random var
Page 965 and 966:
29.7 Expected value of a random var
Page 967 and 968:
29.8 Standard deviation of a random
Page 969 and 970:
29.9 Permutations and combinations
Page 971 and 972:
29.9 Permutations and combinations
Page 973 and 974:
29.10 The binomial distribution 953
Page 975 and 976:
29.10 The binomial distribution 955
Page 977 and 978:
29.11 The Poisson distribution 957I
Page 979 and 980:
Table29.6Theprobabilitiesforbinomia
Page 981 and 982:
29.12 The uniform distribution 9615
Page 983 and 984:
29.14 The normal distribution 963So
Page 985 and 986:
29.14 The normal distribution 965N(
Page 987 and 988:
29.14 The normal distribution 967Ta
Page 989 and 990:
29.14 The normal distribution 969EX
Page 991 and 992:
29.15 Reliability engineering 971in
Page 993 and 994:
29.15 Reliability engineering 973En
Page 995 and 996:
29.15 Reliability engineering 975k
Page 997 and 998:
Review exercises 29 977Solutions1 0
Page 999 and 1000:
AppendicesContents I Representingac
Page 1001 and 1002:
II The Greek alphabet 981f(t)T0 t 0
Page 1003 and 1004:
Indexabsolute quantity88absorption
Page 1005 and 1006:
Index 985chord 357--8circuital law
Page 1007 and 1008:
Index 987cycle ofsint 131cycles ofl
Page 1009 and 1010:
Index 989eigenvalues andeigenvector
Page 1011 and 1012:
Index 991spectra 766--8t-w duality
Page 1013 and 1014:
Index 993characteristic impedance o
Page 1015 and 1016:
Index 995exclusive OR gate 189NAND
Page 1017 and 1018:
Index 997second-order 829--30, 833,
Page 1019 and 1020:
Index 999remainder term,Taylor’s
Page 1021 and 1022:
Index 1001solenoidal vectorfield 85
Page 1023 and 1024:
Index 1003calculus 849--66curl859--
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082-Engineering-Mathematics-Anthony-Croft-Robert-Davison-Martin-Hargreaves-James-Flint-Edisi-5-2017

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