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Purdue - MATH - 366
MA 36600 LECTURE NOTES: FRIDAY, APRIL 3Systems of First Order Linear EquationsRecap. Recall that a rst order equation is an ordinary dierential equation in the formy = G(t, y ),y (t0 ) = y0 .In general, an nth order equation is an ordinary dierential
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: MONDAY, APRIL 6Circuits. Consider a circuit that contains three devices:i. an inductor (which behaves like a mass),ii. a resistor (which behaves like friction), andiii. a capacitor (which behaves like a spring).Such a circui
Purdue - MATH - 366
MA 36600 LECTURE NOTES: MONDAY, APRIL 6ApplicationsSpring-Mass System: One Mass, Two Springs. Now say that we have a mass m attached to twosprings with constants k1 and k2 , respectively. We assume that these springs are attached to the oppositeends o
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: FRIDAY, APRIL 10Systems of Linear EquationsLinear Independence. Consider a collection of m-dimensional vectors:a1k a2k x(k) = . ...amkWe say that the set x(1) , x(2) , . . . , x(n) is a linearly independent set if the on
Purdue - MATH - 366
MA 36600 LECTURE NOTES: FRIDAY, APRIL 103Characteristic Polynomials. We give a simple way to compute eigenvalues of an n n matrix A. Considerthe equationAx = x=( I A) x = 0.Since this holds for a nonzero vector x, we see that the matrix I A must be
Purdue - MATH - 366
MA 36600 LECTURE NOTES: FRIDAY, APRIL 10Systems of Linear EquationsSystems of Linear Dierential Equations. We return to the linear systemx1x2xm==...p11 (t) x1p21 (t) x1++= pm1 (t) x1p12 (t) x2p22 (t) x2+ + ...+ pm2 (t) x2+ Usin
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: MONDAY, APRIL 13Then the general solution to the nonhomogeneous equation is in the formx(t) = c1 x1 (t) + c2 x2 (t) + X (t)where c1 and c2 are constants. In terms of matrices, we see that the general solution is in the formx(
Purdue - MATH - 366
MA 36600 LECTURE NOTES: MONDAY, APRIL 133It suces then to show that x(c) = c for some constant c. Consider an initial value problem in the formd (c)x = P(t) x(c) ,x(c) (t0 ) = x0 .dtAccording to the Existence and Uniqueness Theorem, we know that a
Purdue - MATH - 366
4MA 36600 LECTURE NOTES: MONDAY, APRIL 13When yk = xk (k) we use the fact that x =ipndWd=( )xk (k)dtdtjpij (t) xjp to ndk=1=ni=1=nni=1 j =1nndxi (i) ( )xk (k) =pij (t) ( ) xj (i) xk (k) dti=1 j =1k=ipij (t) W x(1) , . . .
Purdue - MATH - 366
MA 36600 LECTURE NOTES: MONDAY, APRIL 13Basic Theory of Systems of First Order Linear EquationsSolutions to Systems of Linear Dierential Equations. We continue to focus on a system of rstorder dierential equations in the formx1x2xm==...p11
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 15Hence the denitions are consistent. As for Abels Theorem, we have the trace tP1 (t)tr P(t) = =W (t) = C exp trP( ) d = C exp P0 (t)tP1 ( )d .P0 ( )Homogeneous Systems. Again, consider the homogeneo
Purdue - MATH - 366
MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 153The characteristic polynomial isbca r2 + b r + cr1pA (r) = det=r r+ (1) =.c/a r + b/aaaaHence an eigenvalue r of A is a root of the characteristic equation a r2 + b r + c = 0.More generally, con
Purdue - MATH - 366
MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 15Basic Theory of Systems of First Order Linear EquationsExample. We explain how the Wronskian dened in the previous lecture is related to the Wronskian wedened during Lecture #24 on Friday, March 13. Consider t
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: MONDAY, APRIL 20Fundamental MatricesRecap. Consider the initial value problemdx = P(t) x,x(t0 ) = x0 .dtAssuming that P(t) = pij (t) is an n n matrix, say that we can nd n functions x(1) , x(2) , . . . , x(n) suchthati.
Purdue - MATH - 366
MA 36600 LECTURE NOTES: MONDAY, APRIL 203To see why this suces, rst recall the Product Rule:ddd0x=x = x0 = [A ] x0 = A x.dtdtdtAs for the initial condition:x(0) = (0) x0 = I x0 = x0 .We now show that (t) satises the initial value problem ab
Purdue - MATH - 366
MA 36600 LECTURE NOTES: MONDAY, APRIL 20Homogeneous Systems with Constant CoefficientsExample #2. We have already seen that the general solution to the homogeneous system1d21x=x1 1dt2is the functioncos t t/2sin t t/2e+ c2e. sin tcos t
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 22Now we return to the general case. Consider an n n matrix A. Say that there exists a nonsingular n nmatrix T such that T1 A T = D is an n n diagonal matrix. Such a matrix A is said to be diagonalizable.We wi
Purdue - MATH - 366
MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 22Fundamental MatricesDiagonalizable Matrices. We explain how to exponentiate an arbitrary matrix. First, we consider aspecial case. We say that an n n matrix is a diagonal matrix if it is in the formr1 0 0 0
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: FRIDAY, APRIL 23Example. Again, consider the 2 2 matrix1A=411=tr A = 2det A = 3=disc A = 16pA (r) = r2 2 r 3 = (r 3) (r + 1) .Hence the eigenvalues are r1 = 3 and r2 = 1, with corresponding eigenvectors a121a121
Purdue - MATH - 366
MA 36600 LECTURE NOTES: FRIDAY, APRIL 233It is unclear whether we can nd a matrix T such that T1 A T is a diagonal matrix because we only haveone eigenvector. Consider instead the matrix1 1 010101T==T==.1 1111 11Consider the product10
Purdue - MATH - 366
MA 36600 LECTURE NOTES: FRIDAY, APRIL 23Diagonalizing 2 2 MatricesDistinct Eigenvalues. We explain how we chose thewe discuss a general theory which holds especially wellaA = 11a21matrices D and T in the previous example. Indeed,for 2 2 matrices.
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: MONDAY, APRIL 27Matrix Exponentiation Revisited. We saw in the previous lecture thatrtr1 0e10D==exp (D t) =.0 r20er2 tWe show that1 c t rt=exp (J t) =e.01To see why, recall the denition exp (J t) = k Jk tk /k !
Purdue - MATH - 366
MA 36600 LECTURE NOTES: MONDAY, APRIL 27Repeated EigenvaluesJordan Canonical Form. We explain the general theory for when we can diagonalize a 2 2 matrix A.Say that we have eigenvalues r1 and r2 .i. If r1 = r2 i.e., we have distinct eigenvalues, then
Purdue - MATH - 366
2MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 29in terms of the fundamental matrixrte10(t) = exp (D t) = ...00..er2 t...000...ern tThe desired solution is x(t) = T y(t)..Example. Consider the systemdx = A x + g(t)dtin terms of2
Purdue - MATH - 366
MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 29 By the Product Rule for Matricesd 2dQ dQQ =Q+ Q = QP + PQ = 2QPdtdtdt=3d kQ = k Qk1 P ;dtso that we have the formulad1 d k 1exp Q(t) =Q=k Qk1 P = exp Q(t) P(t).dtk ! dtk!k=0k=0We attemp
Purdue - MATH - 366
4MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 29We substitute this into the original equation:d (p)x = P(t) x(p) + g(t)dtddu+ u = P(t) u + g(t)dtdtddd(t) u g(t) = P(t) u = 0=(t) u = g(t).dtdtdtUpon inverting and integrating, we nd tha
Purdue - MATH - 366
MA 36600 LECTURE NOTES: WEDNESDAY, APRIL 29Nonhomogeneous SystemsConstant Coecients. Consider now the nonhomogeneous systemdx = A x + g(t)dtwhere A is a constant n n matrix. We will show that the general solution to this system is in the formx(t) =
Purdue - MATH - 366
2MA 36600 MIDTERM #1 REVIEW1.3: Classication of Dierential Equations. There are two types of dierential equations: ODEs or ordinary dierential equations are equations which do not involve partial derivatives. PDEs or partial dierential equations are
Purdue - MATH - 366
MA 36600 MIDTERM #1 REVIEW32.3: Modeling with First Order Equations. Mixing Problems: Say that we have a tank containing a volume V gal of a certain liquid. Aconcentration c lbs/gal of a certain substance ows in at a constant rate r gal/min, and a fau
Purdue - MATH - 366
4MA 36600 MIDTERM #1 REVIEWis an equilibrium solution. In general, an equilibrium solution is a constant which is a solution, so itsatises the equationf (yL ) = 0.Any constant yL such that f (yL ) = 0 is called a critical point for the function f (y
Purdue - MATH - 366
MA 36600 MIDTERM #1 REVIEW5#2. Choose a function h(y ) according to the ordinary dierential equation ydhgg= N (x, y ) =h(y ) =N (x, ) (x, ) d .dyyy#3. Choose the function f (x, y ) = g (x, y ) + h(y ). Recall that the solution is f (x, y )
Purdue - MATH - 366
6MA 36600 MIDTERM #1 REVIEW2.9: First Order Dierence Equations. A recursive relation the formyn+1 = (n, yn )is called a rst order dierence equation. Using Eulers Method, the dierential equation y = G(t, y )has the associated dierence equation yn+1 =
Purdue - MATH - 366
MA 36600 MIDTERM #1 REVIEWChapter 11.1: Some Basic Mathematical Models; Direction Fields. Newtons Second Law of Motion is the statement F = m a; it really meansd2 x= the sum of the forces on the object.dt2 Newtons Law of Gravitational Attraction is
Purdue - MATH - 366
2MA 36600 MIDTERM #2 REVIEW Say that y1 = y1 (t) and y2 = y2 (t) are solutions to the homogeneous equationa(t) y + b(t) y + c(t) y = 0.The Principle of Superposition states that the linear combination y (t) = c1 y1 (t) + c2 y2 (t) is also asolution f
Purdue - MATH - 366
MA 36600 MIDTERM #2 REVIEW3A fundamental set of solutions to the dierential equation is cfw_y1 , y2 in terms of the functionset cosh t if b2 4 a c > 0,et sinh t if b2 4 a c > 0,y1 (t) =y2 (t) =et cos tif b2 4 a c < 0.et sin tif b2 4 a c < 0.3.
Purdue - MATH - 366
4MA 36600 MIDTERM #2 REVIEW3.6: Variation of Parameters. To nd the general solution of the nonhomogeneous equation a(t) y + b(t) y + c(t) y = f (t), performthe following steps:#1. Find a fundamental set of solutions cfw_y1 , y2 to a(t) y + b(t) y +
Purdue - MATH - 366
MA 36600 MIDTERM #2 REVIEW5 Let Q = Q(t) denote the charge in an electric circuit at time t; it is measured in coulombs. Similarly,I=dQdtdenotes the current; it is measured in amperes. We think of Q as the displacement u(t), and I asthe velocity u
Purdue - MATH - 366
6MA 36600 MIDTERM #2 REVIEWChapter 44.1: General Theory of nth Order Equations. An nth order linear dierential equation is an equation of the formdn ydn1 ydy+ P1 (t) n1 + + Pn1 (t)+ Pn (t) y = G(t).dtndtdtWe wish to solve the initial value pr
Purdue - MATH - 366
MA 36600 MIDTERM #2 REVIEW Say that we can factorZ (r) = a0 pk=17q sk skr rkr [k + i k ] r [k i k ].k=1real rootscomplex rootsThen the general solution is to the constant coecient homogeneous equation isspkm1y (t) =Ckm terk tk=1+
Purdue - MATH - 366
MA 36600 MIDTERM #2 REVIEW Say that we can factorZ (r) = a0 pk=17q sk skr rkr [k + i k ] r [k i k ].k=1real rootscomplex rootsThen the general solution is to the constant coecient homogeneous equation isspkm1y (t) =Ckm terk tk=1+
Purdue - MATH - 366
8MA 36600 MIDTERM #2 REVIEW4.4: The Method of Variation of Parameters. Consider the nth order nonhomogeneous linear dierential equationdn Ydn1 YdY+ P1 (t) n1 + + Pn1 (t)+ Pn (t) Y = G(t).ndtdtdtSay that cfw_y1 , y2 , . . . , yn is a fundamen
Purdue - MATH - 366
MA 36600 MIDTERM #2 REVIEWChapter 33.1: Homogeneous Equations with Constant Coecients. An ordinary dierential equation in the formd2 ydy= G t, y,dt2dtis called a second order dierential equation. If we have initial conditions in the formy (t0 )
Purdue - MATH - 366
MA 36600 LECTURE NOTES: WEDNESDAY, JANUARY 283for some function f (y ).We have seen several examples of autonomous equations: If v = v (t) denotes the velocity at time t of anmass m falling under the inuences of gravity and air resistance, thendv= g
Rutgers - MARKETING - 33:630:301
CHAPTER5:UNDERSTANDINGCONSUMERBEHAVIOR Purchasedecisionprocessconsistsoffivestages:ProblemrecognitionInformationsearchAlternativeevaluationPurchasedecisionPostpurchasebehavior CognitivedissonanceLEVELOFINVOLVEMENT:3CHARACTERISTICS Expensiveit
Rutgers - MARKETING - 33:630:301
Chapter 18: IMCPromotional Mix Inform Prospective Buyers Persuade Them To Try Remind Them of the BenefitsIntegrated MarketingCommunications (IMC)FIGURE 18-1 The communication processFIGUREconsists of six key elementsFIGURE 18-2 The five elements
Emory - MATH - 112
dCkj'_~itSm \(_-H-~e. a -~;JX-YC hoJ \eY\ge.l \ s -t. o f_ _-H-Q\~ a.~ e a. L \ st-/<+1.1s Y-a.~e.sD+ +c).or esu.b)ccLu- =+0e. r- ro r -5ollS+r; lrc.e;t.Y"Y"'\ ' t'"A0"'Y"\~U~1-d."*J.ldJr,"'J;? ~ ~cJp.~ i__c~; )'ir- - -
Emory - MATH - 112
: J) : x #=o -t x~ =/1'3-~S' X + cfw_:( >< ~x ~x~~-'d,i3(&,hnt-,.'L-7) _ .;<cfw_~x~1)X8X.s&~ X 2 _ 7 = 0> e 11" = X- ~I,:~P. Y . ~(e'1fi;z.' 7. )) t:. e7/1(( 7fi;ze-J~X-: e~;z./e ~y)~/,\~~-x.2.=o ~ J.rnXX32:;0x:2=-eO
Emory - MATH - 112
_ _~=L-nx.~> o~?.4_ _ _ _ _ _ _ _ _ _ _ __=- CXJ~ _L_I_"_~ ?f 2 .: 0! i I.J _ _x .-, + C)C) \J x ~ ~ e ,+S b /99 er .fo.ster_ _-=-__, _~_ ~ ~_i~2-,-~-~- ~ ~-~ - ~-~o.2Vx - - - - - - - -e=, _ _=0~-~r-~=~-~4 -~-,-:-t~.z-IJr_~C2
Emory - MATH - 112
T Yl~;' d e Se.W.A.~c.es~-CD F 0- e.-t-o '("' \'oJ ~\ ~ = "c. n - I) . . ;(. J_0 .' ~ \ ~-_-~-1+-= -p_ I-p-~~ ~.( 1'\+_('cfw_\-l).1-\ \.3(n+lJlY\II - !J \.1-\. 3 ' ~ . \ -=- ~ L f . - - - - - - .:=n! : :-3 [ h ( h - t) . . . ~ . I
Emory - MATH - 112
-,00r-~.,., = tOo.rUa.Jl.\-W I't-hSu.rn )Sn =0 . , :.:2. + . . Q n+- a.~1f~ a."h=I0. n00--n:Z; a.d.~ i VV") S nn -=,c.ov. V e rg e.S- n f\JE( o'l-h0rWtSe. )c rv0 0C7"3~hOn~ e-s).00~n =o-Q y -h =- 0- +~\ + -0-,4.-t
Emory - MATH - 112
d o.;j I~- J es-\ ~+-0, LOY\Je.K"gerYlc.e.hQ V\ d atA~ p 1 -/;LCD -n-th -tcrrY\ - cest1 ~Qn~tj u.YY\-n\-l:. GfP 1:J~\V er)DO~~h~c,.c00~t \+is~Y l.n +-;tn:';\h Q5e.on e1.lA.S \ o-YJ'13 ~ - th e=-1\"5n * h i .e r rn - tesT)h Ot.Z
Emory - MATH - 112
o1.QSj I q~/j)iV\~ra.Q t rst) _ _~~( .lp ~~~ (x-Pd _ _~-?), x.-,"-r p:>JS how ~ h P C unVVLSc;5r-'roof' :., B~Ik?~co )/r A-f'+IJ=~p_kIe ~oo [ -+1S in C e-.~;:> I JIp, _ Ie.:,bo 1 -* 1-1"_ J '-pJ-p' _I~Jk~f:>O~~Y \ \A '
Emory - MATH - 112
cfw_io.fj@fl/ir.rna-6~S erie6 JeST ( AST)-Par Z (-') "'an. I-f0< 0.n+l' ;:2.~Q0hR.( hOh-tner-eO-s'tn o.),J;)IIICT do-31 '2.r\' (\'3_" +l<\tn3j' 2.f nY"f!JM~' _:C -'\oss-'fV\u.Q+\pl)~.'(\ 3 < 1 ) 3- n -t- Io R 0 <: -
Emory - MATH - 112
00N OTE:~Q =Yl='~a ,) a.Co2 ' .tl"')J a+' . f-QQn -I)#' (_\)'R('R~y-~=lc~~-~-(k)~-cfw_-ls"ie.:.~-R') ~o.k. -: (.;zRJ~2.1[(R+\)~Qf(t-,:"1 :l."-~:l.lCt?+l) R .J(\'<+[) l ~\,(.J. C. ~+ i ll. =(~ \c<"\- :t)~ : : cSk+:2)(.2le+0
Emory - MATH - 112
__. -now) ~ o.:t: -t:Jv.- ~a'3I '='0.:1,;= ~..y#3 .5,13 5~.0.3 = ;). 4 ,~ \"'\+\J~ > \~ . . ( ~n)tos; Y\c-e. a.LL~o.e.t-ors_-~-U- . -3.).5.).1.)'"~~lo~ni-I ~ ,e.:l hb\~Cjer 'YhD.rv\ 1.Ja ~ \' 351.(dni:~J =1= 0 )"'h~~ . \.\.tp
Emory - MATH - 112
T e.st -t:o,GJC-.oY"\ \J e x ~ ~ c.e.-ni; J4~:@.l;n =1(i) 0:;n =;J.II:25 ( 3"n! j-<YnC~ n J .)11 =-0(_1)",-+1. In:L+ nl+/(_1)'J~Y13n6)G00n =3(_ -I")n-+J jl~.j "TT-CSlflY \-In 31 z.d) ~- - - sYl:'-I J n +n-300( \)n
Emory - MATH - 112
8!J~ra:b'o -tuJ;t:)n( n+:J.~~\y \n
Emory - MATH - 112
pp.002 : a n (X-c.)'"n ;oi~Qn(X-c.:JY)+Q=0.033Cit - c.') + \ "+-0.1aLX-~) + Q.;2.LX-e-J.,.,hLX - c.,' ) -+IIIp ower s eriesJ w eW 'l LL ~ i n d -t:h ed o rnO-i n ( ra.d 1 uSo .nd i ntervaL o f C Jhver<jence'J.5 0)g ivenp ow/r .
Emory - MATH - 112
daj 3 D~r-.lCL<-[.fC!h o.nc1lY1od~S~H-"II ct:1Lor's - :Theorem .~.-'"-"-'i00! '(x) an-I:Z; al'Jx-c-)~=fc ") (c.Jn11 I-t?(x) =- y'\ : =.!:'iIril- then"Y'lsO-Exo.YYJp I e: F.~r-1 jr)(:Jl Qx..j2(XJ = C DstCx);:C -Ds X