CONTINUOUS TIME DYNAMIC PROGRAMMING

Size: px
Start display at page:

Download "CONTINUOUS TIME DYNAMIC PROGRAMMING"

Transcription

1 Eon. 511b Sprng 1993 C. Sms I. Th Opmaon Problm CONTINUOUS TIME DYNAMIC PROGRAMMING W onsdr h problm of maxmng subj o and EU(C, ) d (1) j ^ d = (C, ) d + σ (C, ) dw () h(c, ), (3) whr () and (3) hold for all n (, ). In solvng h problm w ak as gvn and known, whl h pahs of C and hrby for > ar subj o ho. W assum ha C and pahs mus b hosn so ha dsons mad a dpnd only on nformaon avalabl a. Tha s, our ho a mus b xprssd as a mappng from wha w wll know a, whh s {C s, s,w s, s }, o a ral vor C of hos mad a. Of ours () hn drmns s bhavor a. W assum and C ar boh vors, so σ s a marx. II. Rursv Sruur Th problm dfnd by (1)-(3) sars a m. W ould as asly dfn h problm as sarng a som arbrary da. Furhrmor, for vry nal valu of for whh h problm has a soluon, hr wll b som orrspondng valu of h objv funon, V(). Tha s, hr s a funon V() = EU(C *, ) -βs ds, (4) j +s +s whr h * ndas ha C * s hosn opmally. Th funon V s alld h valu funon. No ha h opmal ho of C n opmng (4) mus dpnd only on, no on ohr nformaon avalabl a, sn (4) slf and h ons- 1

2 rans do no pnd on h pas xp hrough. W wr C * =γ( ), and γ s h poly funon solvng h dynam programmng problm. Now obsrv ha (1) an b wrn as T EU(C, ) d =EU(C, ) d + (5) j j -βt EU(C, ) -βs ds. j T+s T+s T Th las rm on h rgh of (5) has h sam sruur as h orgnal ngral on h lf of (5), xp ha s shfd n m. Sn our hos of C T+s for s> hav no ff on h valu of h frs ngral on h rgh of (5), w an maxm h ovrall ngral n wo sps. Frs, maxm h sond rm on h rgh of (5), akng T as gvn. Thn, akng aoun of how T affs wha uly s obanabl from h sond rm on h rgh of (5), maxm ovr h (,T) nrval. Ths s Bllman s prnpl and an b sad mor onsly as h assron ha h problm (1)-(3) s uvaln o h problm of maxmng T EU(C, ) d + -βt V. (6) j T wh rsp o C and subj o () and (3). III. Condons Drmnng an Opmum Now assumng ha, undr h opmal ho of C, h objv funon (1) has a wll-dfnd fn valu, w an dfn a nw sohas pross Z = EU(γ, ) -βs ds. (7) j s s Th pross Z, bng of h form E X, s by onsruon a marngal and hrfor has

3 ^ Z =. (8) Bu now usng (6) and Io s lmma, w an form anohr xprsson for Z,.. 1 Z = U(γ(),) - βv() + D V rσ D V σ =. (9) 9 9 Of ours o form (9) w mus assum ha V s w dffrnabl. Ths provds us wh a nssary ondon for V o b h valu funon and γ o b h opmal poly funon, namly U(γ(),) - βv() + D V rσ D V σ =, (1) 9 for all possbl valus of. Euaon (1) by slf s no an uaon w an solv for V or γ. solubl uaon, w apply Bllman s uaon, whh s for hs sup To arrv a a 1 max { U-βV+D V rσ D V σ } =. (11) h(c,) 9 9 If, for som V and γ, (11) and (1) hold for vry possbl valu of, hn (subj o som rgulary ondons) V s h valu funon and γ s h opmal poly. To s hs, suppos φ s a sohas pross for C ha maks dpnd only on pas nformaon and, ha, whn s usd n () o gnra, sasfs (3). L and ~ = (1) ~ ~ ~ d = (φ,) d + σ (φ,)dw. (13) Furhr l Q = ~ -βs ~ U(φ, ) ds + V. (14) j s s No ha Q =V and ha 3

4 EQ ~ -βs L EU(φ, ) ds. (15) j s s In assrng (15) w ar assumng an mporan rgulary ondon ha aually fals n som vrsons of h frs smpl xampl w wll onsdr blow, h lnar-uadra prmann nom modl. Th ondon s ha for any fasbl Now E V L. (16) L ~ 1 Q= U(φ,) - βv +D V rσ D σ V, (17) 9 9 whr h mpl C and argumns n (17) ar φ and. ~ Obvously f (11) holds for all possbl valus of, Q, all. Ths, wh (15), mpls ha φ as h ho for C ylds a valu of h objv funon no grar han V( ). Sn hs holds for any Φ, V( ) s n fa h maxmum aanabl valu of h objv funon and s aand wh h poly rul γ. No ha whl (11) s a sandard, rlavly asy o rmmbr form for h Bllman uaon, supprsss, for h sak of smpl noaon, h mporan pons ha U, σ and ar boh funons of C and, whl V dpnds on alon. If U,, and σ ar dffrnabl n C, (11) mpls h frs-ordr ondon D U(C,) + D V D (C,) +.5 rd V D σ (C,)σ (C,) C C = µ D h, (18) C C 9 whr µ s a uhn-tukr mulplr ha vanshs for h(c,)<. For h as of a on-dmnsonal (18) aks h smplr form D U(C,) + V D (C,) + V σ (C,) D σ (C,) = µ D h. (19) C C C C Euaon (18) or (19) an b solvd, n prnpl, for C as a funon of, V, and V. Subsung hs bak no (1) gvs us a dffrnal uaon n V, V, 4

5 V, and alon. Ths s a sond ordr dffrnal uaon (paral dffrnal uaon n h as of a non-salar ) n V, and an n prnpl b solvd, gvn appropra boundary ondons. Ofn n fndng a soluon s hlpful, nsad of ombnng (1) wh (18) o oban a dffrnal uaon n V, o ombn (18) wh h drvav of (1) wh rsp o. Ths s usful baus ofn h rsulng sysm an b rdud o a dffrnal uaon n γ, whh s ofn mor drly usful han V. Also, h drvav of (1) wh rsp o has an nrpraon as a dffrnal uaon n m (rahr han ) ha an somms b ombnd wh () o oban a sysm of dffrnal uaons wh rsp o m n C and. Ths may allow us o prod drly o soluons for or hararaons of C and as funons of m, whh may agan b of mor dr nrs han hr V or γ. Dffrnang (1) wh rsp o gvs D U - βd V + D V D +.5rD V D σ σ () D V +.5 rd V σ σ 9 +D Uγ +D VD γ +.5rD V D σ σ C C γ =. C 9 9 No ha whn µ=, (18) abov mpls ha h las ln of () (all h rms nvolvng γ ) s dnally ro. Whn µ, h onsran h(γ(),)= holds, so D C h γ = -D h. (1) Thus h rms on h las ln of () always ar ual o -µd h. Ths fa and h rsulng smplfaon of () s wha s known as h nvlop horm. I lavs us wh D U - βd V + D V D +.5rD V D σ σ () 9 9 +D V+.5rD V σ σ =-µd h. 9 No ha Io s lmma mpls ha h las wo rms on h lf of () ar xaly D V, so ha () an b wrn 5

6 -D V = D U - βd V + D V D +.5rD V D σ σ + µ D h (3) 9 9 In fa, f w dfn λ=d V, w an rwr (18) and (3) as D U + λ D +.5 rd λ D σ σ C C - µ D h = (4) C C 9 -λ =D U-βλ + λ D +.5rD λ D σ σ + µ D h. (5) 9 9 In h drmns as, whr σ, or n any ohr as whr σ s onsan, (), (4) and (5) form h usual Hamlonan frs-ordr ondons. Whl hs sysm s sll oasonally of som us n nrprng sohas problms, s no so drly usful baus of h apparan of D λ n h sohas vrson. Ths prvns h sysm from bng nrprd as a s of dffrnal uaons n h m pahs of C, and λ. IV. Th Lnar-Quadra Prmann Inom Modl L s apply wha w v dvlopd n h prdng sons o h onnuous m vrson of h sandard prmann nom modl. W onsdr h problm of maxmng subj o Spalng (4) and (5) o hs as ylds Combnng (8) and (9) gvs us E(C-.5C ) d (6) j da = (ra + Y - C) d + σ dw. (7) 1-C=-λ (8) -λ = (r-β)λ. (9) C = (r-β)(1-c) (3) 6

7 whh n h ladng as of r=β produs Hall s onluson ha onsumpon s a marngal. Rwrng (8) n rms of γ() (o g bak o (3) as appld o hs problm) gvs us γ A+.5γ σ = (r-β)(1-γ), (31) an ordnary (nonlnar) sond-ordr dffrnal uaon n γ. Euaon (31) has a las wo vry smpl soluons. On s γ() 1. Ths s h poly of sng C a s saaon lvl forvr. Th ohr maks γ lnar, so ha γ = and γ=a+ba for som a and b. I s asy o hk ha (31) hn mpls b (ra + Y - a - ba) = (r - β) (1 - a - ba). (3) From (3) w onlud ha f b, b=r-β. In ha as w an onlud furhr ha a=(β/r-1)y+β/r-1. In h spal as β=r, hs rdus o h rul C=rA+Y. Ths wo soluons boh dsplay wha s alld rany uvaln. Tha s, baus h rm n σ, h only on affd by h prsn of unrany, dsappars from (31) for hs soluons, hy ar soluons also o h vrson of h problm ha has σ =. W ould hav found hs soluons by gnorng h prsn of unrany, and hy would nonhlss hav bn orr whn unrany was nrodud. Ths rsul s obvously a spal as. I always arss whn U s uadra n s argumns, s lnar n s argumns, and hr s no sd onsran h, h lnar-uadra as. [A ompl vrson of hs nos would go on o dsuss how h prsn of wo soluons ha work for all an b ronld wh h opmaly prnpl and wha o mak of all h ohr, nonlnar soluons o (31).] 7

Advanced Queueing Theory. M/G/1 Queueing Systems

Advanced Queueing Theory. M/G/1 Queueing Systems Advand Quung Thory Ths slds ar rad by Dr. Yh Huang of Gorg Mason Unvrsy. Sudns rgsrd n Dr. Huang's ourss a GMU an ma a sngl mahn-radabl opy and prn a sngl opy of ah sld for hr own rfrn, so long as ah sld

More information

Consider a system of 2 simultaneous first order linear equations

Consider a system of 2 simultaneous first order linear equations Soluon of sysms of frs ordr lnar quaons onsdr a sysm of smulanous frs ordr lnar quaons a b c d I has h alrna mar-vcor rprsnaon a b c d Or, n shorhand A, f A s alrady known from con W know ha h abov sysm

More information

t=0 t>0: + vr - i dvc Continuation

t=0 t>0: + vr - i dvc Continuation hapr Ga Dlay and rcus onnuaon s rcu Equaon >: S S Ths dffrnal quaon, oghr wh h nal condon, fully spcfs bhaor of crcu afr swch closs Our n challng: larn how o sol such quaons TUE/EE 57 nwrk analys 4/5 NdM

More information

Chapter 7. Now, for 2) 1. 1, if z = 1, Thus, Eq. (7.20) holds

Chapter 7. Now, for 2) 1. 1, if z = 1, Thus, Eq. (7.20) holds Chapr 7, n, 7 Ipuls rspons of h ovng avrag flr s: h[, ohrws sn / / Is frquny rspons s: sn / Now, for a BR ransfr funon,, For h ovng-avrag flr, sn / W shall show by nduon ha sn / sn / sn /,, Now, for sn

More information

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns

Summary: Solving a Homogeneous System of Two Linear First Order Equations in Two Unknowns Summary: Solvng a Homognous Sysm of Two Lnar Frs Ordr Equaons n Two Unknowns Gvn: A Frs fnd h wo gnvalus, r, and hr rspcv corrspondng gnvcors, k, of h coffcn mar A Dpndng on h gnvalus and gnvcors, h gnral

More information

(heat loss divided by total enthalpy flux) is of the order of 8-16 times

(heat loss divided by total enthalpy flux) is of the order of 8-16 times 16.51, Rok Prolson Prof. Manl Marnz-Sanhz r 8: Convv Ha ransfr: Ohr Effs Ovrall Ha oss and Prforman Effs of Ha oss (1) Ovrall Ha oss h loal ha loss r n ara s q = ρ ( ) ngrad ha loss s a S, and sng m =

More information

innovations shocks white noise

innovations shocks white noise Innovaons Tm-srs modls ar consrucd as lnar funcons of fundamnal forcasng rrors, also calld nnovaons or shocks Ths basc buldng blocks sasf var σ Srall uncorrlad Ths rrors ar calld wh nos In gnral, f ou

More information

The Variance-Covariance Matrix

The Variance-Covariance Matrix Th Varanc-Covaranc Marx Our bggs a so-ar has bn ng a lnar uncon o a s o daa by mnmzng h las squars drncs rom h o h daa wh mnsarch. Whn analyzng non-lnar daa you hav o us a program l Malab as many yps o

More information

Frequency Response. Response of an LTI System to Eigenfunction

Frequency Response. Response of an LTI System to Eigenfunction Frquncy Rsons Las m w Rvsd formal dfnons of lnary and m-nvaranc Found an gnfuncon for lnar m-nvaran sysms Found h frquncy rsons of a lnar sysm o gnfuncon nu Found h frquncy rsons for cascad, fdbac, dffrnc

More information

Lecture 4: Laplace Transforms

Lecture 4: Laplace Transforms Lur 4: Lapla Transforms Lapla and rlad ransformaions an b usd o solv diffrnial quaion and o rdu priodi nois in signals and imags. Basially, hy onvr h drivaiv opraions ino mulipliaion, diffrnial quaions

More information

9. Simple Rules for Monetary Policy

9. Simple Rules for Monetary Policy 9. Smpl Ruls for Monar Polc John B. Talor, Ma 0, 03 Woodford, AR 00 ovrvw papr Purpos s o consdr o wha xn hs prscrpon rsmbls h sor of polc ha conomc hor would rcommnd Bu frs, l s rvw how hs sor of polc

More information

10.5 Linear Viscoelasticity and the Laplace Transform

10.5 Linear Viscoelasticity and the Laplace Transform Scn.5.5 Lnar Vclacy and h Lalac ranfrm h Lalac ranfrm vry uful n cnrucng and analyng lnar vclac mdl..5. h Lalac ranfrm h frmula fr h Lalac ranfrm f h drvav f a funcn : L f f L f f f f f c..5. whr h ranfrm

More information

Boyce/DiPrima 9 th ed, Ch 7.8: Repeated Eigenvalues

Boyce/DiPrima 9 th ed, Ch 7.8: Repeated Eigenvalues Boy/DiPrima 9 h d Ch 7.8: Rpad Eignvalus Elmnary Diffrnial Equaions and Boundary Valu Problms 9 h diion by William E. Boy and Rihard C. DiPrima 9 by John Wily & Sons In. W onsidr again a homognous sysm

More information

Supplementary Figure 1. Experiment and simulation with finite qudit. anharmonicity. (a), Experimental data taken after a 60 ns three-tone pulse.

Supplementary Figure 1. Experiment and simulation with finite qudit. anharmonicity. (a), Experimental data taken after a 60 ns three-tone pulse. Supplmnar Fgur. Eprmn and smulaon wh fn qud anharmonc. a, Eprmnal daa akn afr a 6 ns hr-on puls. b, Smulaon usng h amlonan. Supplmnar Fgur. Phagoran dnamcs n h m doman. a, Eprmnal daa. Th hr-on puls s

More information

Vertical Sound Waves

Vertical Sound Waves Vral Sond Wavs On an drv h formla for hs avs by onsdrn drly h vral omonn of momnm qaon hrmodynam qaon and h onny qaon from 5 and hn follon h rrbaon mhod and assmn h snsodal solons. Effvly h frs ro and

More information

Problem 1: Consider the following stationary data generation process for a random variable y t. e t ~ N(0,1) i.i.d.

Problem 1: Consider the following stationary data generation process for a random variable y t. e t ~ N(0,1) i.i.d. A/CN C m Sr Anal Profor Òcar Jordà Wnr conomc.c. Dav POBLM S SOLIONS Par I Analcal Quon Problm : Condr h followng aonar daa gnraon proc for a random varabl - N..d. wh < and N -. a Oban h populaon man varanc

More information

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS Answr Ky Nam: Da: UNIT # EXPONENTIAL AND LOGARITHMIC FUNCTIONS Par I Qusions. Th prssion is quivaln o () () 6 6 6. Th ponnial funcion y 6 could rwrin as y () y y 6 () y y (). Th prssion a is quivaln o

More information

ELEN E4830 Digital Image Processing

ELEN E4830 Digital Image Processing ELEN E48 Dgal Imag Procssng Mrm Eamnaon Sprng Soluon Problm Quanzaon and Human Encodng r k u P u P u r r 6 6 6 6 5 6 4 8 8 4 P r 6 6 P r 4 8 8 6 8 4 r 8 4 8 4 7 8 r 6 6 6 6 P r 8 4 8 P r 6 6 8 5 P r /

More information

Math 3301 Homework Set 6 Solutions 10 Points. = +. The guess for the particular P ( ) ( ) ( ) ( ) ( ) ( ) ( ) cos 2 t : 4D= 2

Math 3301 Homework Set 6 Solutions 10 Points. = +. The guess for the particular P ( ) ( ) ( ) ( ) ( ) ( ) ( ) cos 2 t : 4D= 2 Mah 0 Homwork S 6 Soluions 0 oins. ( ps) I ll lav i o you o vrify ha y os sin = +. Th guss for h pariular soluion and is drivaivs is blow. Noi ha w ndd o add s ono h las wo rms sin hos ar xaly h omplimnary

More information

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule Lcur : Numrical ngraion Th Trapzoidal and Simpson s Rul A problm Th probabiliy of a normally disribud (man µ and sandard dviaion σ ) vn occurring bwn h valus a and b is B A P( a x b) d () π whr a µ b -

More information

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors

Boyce/DiPrima 9 th ed, Ch 2.1: Linear Equations; Method of Integrating Factors Boc/DiPrima 9 h d, Ch.: Linar Equaions; Mhod of Ingraing Facors Elmnar Diffrnial Equaions and Boundar Valu Problms, 9 h diion, b William E. Boc and Richard C. DiPrima, 009 b John Wil & Sons, Inc. A linar

More information

( ) ( ) + = ( ) + ( )

( ) ( ) + = ( ) + ( ) Mah 0 Homwork S 6 Soluions 0 oins. ( ps I ll lav i o you vrify ha h omplimnary soluion is : y ( os( sin ( Th guss for h pariular soluion and is drivaivs ar, +. ( os( sin ( ( os( ( sin ( Y ( D 6B os( +

More information

Wave Superposition Principle

Wave Superposition Principle Physcs 36: Was Lcur 5 /7/8 Wa Suroson Prncl I s qu a common suaon for wo or mor was o arr a h sam on n sac or o xs oghr along h sam drcon. W wll consdr oday sral moran cass of h combnd ffcs of wo or mor

More information

Elementary Differential Equations and Boundary Value Problems

Elementary Differential Equations and Boundary Value Problems Elmnar Diffrnial Equaions and Boundar Valu Problms Boc. & DiPrima 9 h Ediion Chapr : Firs Ordr Diffrnial Equaions 00600 คณ ตศาสตร ว ศวกรรม สาขาว ชาว ศวกรรมคอมพ วเตอร ป การศ กษา /55 ผศ.ดร.อร ญญา ผศ.ดร.สมศ

More information

Version 1.0 VLADIMIR V. KOROSTELEV. A Primer in Quantum Mechanics for NMR Students

Version 1.0 VLADIMIR V. KOROSTELEV. A Primer in Quantum Mechanics for NMR Students Vrson. VADMR V. KOROSTEEV A Prmr n Quanum Mhans for NMR Sudns Vladmr Koroslv, 8 vladmr.v.koroslv@ramblr.ru Tabl of Conns Conns. nroduon. Quanum Sas of Spn / 3. Opraors for Spn / 6 4. Hamlonan of spn n

More information

Theoretical Seismology

Theoretical Seismology Thorcal Ssmology Lcur 9 Sgnal Procssng Fourr analyss Fourr sudd a h Écol Normal n Pars, augh by Lagrang, who Fourr dscrbd as h frs among Europan mn of scnc, Laplac, who Fourr rad lss hghly, and by Mong.

More information

P. We make the following assumptions

P. We make the following assumptions Inrnaonal Journal of Sn and Rsar IJSR ISSN Onln: 39-764 Ind oprnus alu 5: 7896 Impa Faor 5: 639 Opmal Ddnd Prolm n ompound Posson Modl w orng Df a Run Yanan Wang Xong Song H nrs of nolog Sool of Sn anjn34

More information

Electromagnetic waves in vacuum.

Electromagnetic waves in vacuum. leromagne waves n vauum. The dsovery of dsplaemen urrens enals a peular lass of soluons of Maxwell equaons: ravellng waves of eler and magne felds n vauum. In he absene of urrens and harges, he equaons

More information

CIVL 8/ D Boundary Value Problems - Triangular Elements (T6) 1/8

CIVL 8/ D Boundary Value Problems - Triangular Elements (T6) 1/8 CIVL 8/7 -D Boundar Valu Problm - rangular Elmn () /8 SI-ODE RIAGULAR ELEMES () A quadracall nrpolad rangular lmn dfnd b nod, hr a h vrc and hr a h mddl a ach d. h mddl nod, dpndng on locaon, ma dfn a

More information

FAULT TOLERANT SYSTEMS

FAULT TOLERANT SYSTEMS FAULT TOLERANT SYSTEMS hp://www.cs.umass.du/c/orn/faultolransysms ar 4 Analyss Mhods Chapr HW Faul Tolranc ar.4.1 Duplx Sysms Boh procssors xcu h sam as If oupus ar n agrmn - rsul s assumd o b corrc If

More information

9.5 Complex variables

9.5 Complex variables 9.5 Cmpl varabls. Cnsdr th funtn u v f( ) whr ( ) ( ), f( ), fr ths funtn tw statmnts ar as fllws: Statmnt : f( ) satsf Cauh mann quatn at th rgn. Statmnt : f ( ) ds nt st Th rrt statmnt ar (A) nl (B)

More information

Continous system: differential equations

Continous system: differential equations /6/008 Coious sysm: diffrial quaios Drmiisic modls drivaivs isad of (+)-( r( compar ( + ) R( + r ( (0) ( R ( 0 ) ( Dcid wha hav a ffc o h sysm Drmi whhr h paramrs ar posiiv or gaiv, i.. giv growh or rducio

More information

INF5820 MT 26 OCT 2012

INF5820 MT 26 OCT 2012 INF582 MT 26 OCT 22 H22 Jn Tor Lønnng l@.uo.no Tody Ssl hn rnslon: Th nosy hnnl odl Word-bsd IBM odl Trnng SMT xpl En o lgd n r d bygg..9 h.6 d.3.9 rgh.9 wh.4 buldng.45 oo.3 rd.25 srgh.7 by.3 onsruon.33

More information

Engineering Circuit Analysis 8th Edition Chapter Nine Exercise Solutions

Engineering Circuit Analysis 8th Edition Chapter Nine Exercise Solutions Engnrng rcu naly 8h Eon hapr Nn Exrc Soluon. = KΩ, = µf, an uch ha h crcu rpon oramp. a For Sourc-fr paralll crcu: For oramp or b H 9V, V / hoo = H.7.8 ra / 5..7..9 9V 9..9..9 5.75,.5 5.75.5..9 . = nh,

More information

Lecture 4 : Backpropagation Algorithm. Prof. Seul Jung ( Intelligent Systems and Emotional Engineering Laboratory) Chungnam National University

Lecture 4 : Backpropagation Algorithm. Prof. Seul Jung ( Intelligent Systems and Emotional Engineering Laboratory) Chungnam National University Lcur 4 : Bacpropagaon Algorhm Pro. Sul Jung Inllgn Sm and moonal ngnrng Laboraor Chungnam Naonal Unvr Inroducon o Bacpropagaon algorhm 969 Mn and Papr aac. 980 Parr and Wrbo dcovrd bac propagaon algorhm.

More information

The Mathematics of Harmonic Oscillators

The Mathematics of Harmonic Oscillators Th Mhcs of Hronc Oscllors Spl Hronc Moon In h cs of on-nsonl spl hronc oon (SHM nvolvng sprng wh sprng consn n wh no frcon, you rv h quon of oon usng Nwon's scon lw: con wh gvs: 0 Ths s sos wrn usng h

More information

Chapter 2: Semi-Classical Light- Matter Interaction

Chapter 2: Semi-Classical Light- Matter Interaction Quanum Ops for Phoons and Opolrons (Farhan ana, Cornll Unvrs) Chapr : Sm-Classal Lgh- Mar Inraon. A Two-lvl Ssm Inrang wh Classal Elromagn Fld n h Absn of Dohrn.. Hamlonan for Inraon bwn Lgh and a Two-lvl

More information

Conventional Hot-Wire Anemometer

Conventional Hot-Wire Anemometer Convnonal Ho-Wr Anmomr cro Ho Wr Avanag much mallr prob z mm o µm br paal roluon array o h nor hghr rquncy rpon lowr co prormanc/co abrcaon roc I µm lghly op p layr 8µm havly boron op ch op layr abrcaon

More information

ECON 8105 FALL 2017 ANSWERS TO MIDTERM EXAMINATION

ECON 8105 FALL 2017 ANSWERS TO MIDTERM EXAMINATION MACROECONOMIC THEORY T. J. KEHOE ECON 85 FALL 7 ANSWERS TO MIDTERM EXAMINATION. (a) Wh an Arrow-Debreu markes sruure fuures markes for goods are open n perod. Consumers rade fuures onras among hemselves.

More information

Decline Curves. Exponential decline (constant fractional decline) Harmonic decline, and Hyperbolic decline.

Decline Curves. Exponential decline (constant fractional decline) Harmonic decline, and Hyperbolic decline. Dlin Curvs Dlin Curvs ha lo flow ra vs. im ar h mos ommon ools for forasing roduion and monioring wll rforman in h fild. Ths urvs uikly show by grahi mans whih wlls or filds ar roduing as xd or undr roduing.

More information

Control Systems (Lecture note #6)

Control Systems (Lecture note #6) 6.5 Corol Sysms (Lcur o #6 Las Tm: Lar algbra rw Lar algbrac quaos soluos Paramrzao of all soluos Smlary rasformao: compao form Egalus ad gcors dagoal form bg pcur: o brach of h cours Vcor spacs marcs

More information

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b

4.1 The Uniform Distribution Def n: A c.r.v. X has a continuous uniform distribution on [a, b] when its pdf is = 1 a x b 4. Th Uniform Disribuion Df n: A c.r.v. has a coninuous uniform disribuion on [a, b] whn is pdf is f x a x b b a Also, b + a b a µ E and V Ex4. Suppos, h lvl of unblivabiliy a any poin in a Transformrs

More information

Chapter 9 Transient Response

Chapter 9 Transient Response har 9 Transn sons har 9: Ouln N F n F Frs-Ordr Transns Frs-Ordr rcus Frs ordr crcus: rcus conan onl on nducor or on caacor gornd b frs-ordr dffrnal quaons. Zro-nu rsons: h crcu has no ald sourc afr a cran

More information

Problem Set 3 EC2450A. Fall ) Write the maximization problem of the individual under this tax system and derive the first-order conditions.

Problem Set 3 EC2450A. Fall ) Write the maximization problem of the individual under this tax system and derive the first-order conditions. Problem Se 3 EC450A Fall 06 Problem There are wo ypes of ndvduals, =, wh dfferen ables w. Le be ype s onsumpon, l be hs hours worked and nome y = w l. Uly s nreasng n onsumpon and dereasng n hours worked.

More information

Chapter 13 Laplace Transform Analysis

Chapter 13 Laplace Transform Analysis Chapr aplac Tranorm naly Chapr : Ouln aplac ranorm aplac Tranorm -doman phaor analy: x X σ m co ω φ x X X m φ x aplac ranorm: [ o ] d o d < aplac Tranorm Thr condon Unlaral on-dd aplac ranorm: aplac ranorm

More information

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35

2.1. Differential Equations and Solutions #3, 4, 17, 20, 24, 35 MATH 5 PS # Summr 00.. Diffrnial Equaions and Soluions PS.# Show ha ()C #, 4, 7, 0, 4, 5 ( / ) is a gnral soluion of h diffrnial quaion. Us a compur or calculaor o skch h soluions for h givn valus of h

More information

Chap 2: Reliability and Availability Models

Chap 2: Reliability and Availability Models Chap : lably ad valably Modls lably = prob{s s fully fucog [,]} Suppos from [,] m prod, w masur ou of N compos, of whch N : # of compos oprag corrcly a m N f : # of compos whch hav fald a m rlably of h

More information

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis (Schrh und Zuvrlässgk ngbr Sysm) Sochasc Rlably Analyss Conn Dfnon of Rlably Hardwar- vs. Sofwar Rlably Tool Asssd Rlably Modlng Dscrpons of Falurs ovr Tm Rlably Modlng Exampls of Dsrbuon Funcons Th xponnal

More information

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis

Safety and Reliability of Embedded Systems. (Sicherheit und Zuverlässigkeit eingebetteter Systeme) Stochastic Reliability Analysis Safy and Rlably of Embddd Sysms (Schrh und Zuvrlässgk ngbr Sysm) Sochasc Rlably Analyss Safy and Rlably of Embddd Sysms Conn Dfnon of Rlably Hardwar- vs. Sofwar Rlably Tool Asssd Rlably Modlng Dscrpons

More information

Lecture Notes 4: Consumption 1

Lecture Notes 4: Consumption 1 Leure Noes 4: Consumpon Zhwe Xu (xuzhwe@sju.edu.n) hs noe dsusses households onsumpon hoe. In he nex leure, we wll dsuss rm s nvesmen deson. I s safe o say ha any propagaon mehansm of maroeonom model s

More information

NAME: ANSWER KEY DATE: PERIOD. DIRECTIONS: MULTIPLE CHOICE. Choose the letter of the correct answer.

NAME: ANSWER KEY DATE: PERIOD. DIRECTIONS: MULTIPLE CHOICE. Choose the letter of the correct answer. R A T T L E R S S L U G S NAME: ANSWER KEY DATE: PERIOD PREAP PHYSICS REIEW TWO KINEMATICS / GRAPHING FORM A DIRECTIONS: MULTIPLE CHOICE. Chs h r f h rr answr. Us h fgur bw answr qusns 1 and 2. 0 10 20

More information

On the Existence and uniqueness for solution of system Fractional Differential Equations

On the Existence and uniqueness for solution of system Fractional Differential Equations OSR Jourl o Mhms OSR-JM SSN: 78-578. Volum 4 ssu 3 Nov. - D. PP -5 www.osrjourls.org O h Es d uquss or soluo o ssm rol Drl Equos Mh Ad Al-Wh Dprm o Appld S Uvrs o holog Bghdd- rq Asr: hs ppr w d horm o

More information

CHAPTER 7d. DIFFERENTIATION AND INTEGRATION

CHAPTER 7d. DIFFERENTIATION AND INTEGRATION CHAPTER 7d. DIFFERENTIATION AND INTEGRATION A. J. Clark School o Engnrng Dpartmnt o Cvl and Envronmntal Engnrng by Dr. Ibrahm A. Assakka Sprng ENCE - Computaton Mthods n Cvl Engnrng II Dpartmnt o Cvl and

More information

EE105 Fall 2015 Microelectronic Devices and Circuits. LTI: Linear Time-Invariant System

EE105 Fall 2015 Microelectronic Devices and Circuits. LTI: Linear Time-Invariant System EE5 Fall 5 Mrolron Dvs and Crus Prof. Mng C. Wu wu@s.rkl.du 5 Suarda Da all SD - LTI: Lnar Tm-Invaran Ssm Ssm s lnar sudd horoughl n 6AB: Ssm s m nvaran: Thr s no lok or m rfrn Th ransfr funon s no a funon

More information

Chain DOUBLE PITCH TYPE RS TYPE RS POLY-STEEL TYPE

Chain DOUBLE PITCH TYPE RS TYPE RS POLY-STEEL TYPE d Fr Flw OULE IC YE YE OLY-EEL YE Oubard wh d s (d ) s usd fr fr flw vya. Usually w srads ar usd h qupm. d s basd sadard rllr ha wh sd rllrs salld xdd ps. hr ar hr yps f bas ha: (1) ubl ph rllr ha wh sadard

More information

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT

An Indian Journal FULL PAPER. Trade Science Inc. A stage-structured model of a single-species with density-dependent and birth pulses ABSTRACT [Typ x] [Typ x] [Typ x] ISSN : 974-7435 Volum 1 Issu 24 BioTchnology 214 An Indian Journal FULL PAPE BTAIJ, 1(24), 214 [15197-1521] A sag-srucurd modl of a singl-spcis wih dnsiy-dpndn and birh pulss LI

More information

A Note on Estimability in Linear Models

A Note on Estimability in Linear Models Intrnatonal Journal of Statstcs and Applcatons 2014, 4(4): 212-216 DOI: 10.5923/j.statstcs.20140404.06 A Not on Estmablty n Lnar Modls S. O. Adymo 1,*, F. N. Nwob 2 1 Dpartmnt of Mathmatcs and Statstcs,

More information

Charging of capacitor through inductor and resistor

Charging of capacitor through inductor and resistor cur 4&: R circui harging of capacior hrough inducor and rsisor us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R, an inducor of inducanc and a y K in sris.

More information

Homework: Introduction to Motion

Homework: Introduction to Motion Homwork: Inroducon o Moon Dsanc vs. Tm Graphs Nam Prod Drcons: Answr h foowng qusons n h spacs provdd. 1. Wha do you do o cra a horzona n on a dsancm graph? 2. How do you wak o cra a sragh n ha sops up?

More information

arxiv: v1 [math.ap] 16 Apr 2016

arxiv: v1 [math.ap] 16 Apr 2016 Th Cauchy problm for a combuson modl n porous mda J. C. da Moa M. M. Sanos. A. Sanos arxv:64.4798v [mah.ap] 6 Apr 6 Absrac W prov h xsnc of a global soluon o h Cauchy problm for a nonlnar racon-dffuson

More information

t the propensity to consume the resource good. Maximizing U t in (9) subject to the budget constraint (8) yields

t the propensity to consume the resource good. Maximizing U t in (9) subject to the budget constraint (8) yields ISB 978-9-84468-8-5 Innaonal Confn on Issus n Busnss onoms Mang an Mamas (IBMM-6) Sngapo 5-6 6 Busnss Cls Capal nvonmn an Rnabl Rsous W-Bn Zang Rsuman Asa Paf Unvs Bppu-s Japan Absa: Ts pap nfs busnss

More information

Final Exam : Solutions

Final Exam : Solutions Comp : Algorihm and Daa Srucur Final Exam : Soluion. Rcuriv Algorihm. (a) To bgin ind h mdian o {x, x,... x n }. Sinc vry numbr xcp on in h inrval [0, n] appar xacly onc in h li, w hav ha h mdian mu b

More information

MECE 3320 Measurements & Instrumentation. Static and Dynamic Characteristics of Signals

MECE 3320 Measurements & Instrumentation. Static and Dynamic Characteristics of Signals MECE 330 MECE 330 Masurms & Isrumao Sac ad Damc Characrscs of Sgals Dr. Isaac Chouapall Dparm of Mchacal Egrg Uvrs of Txas Pa Amrca MECE 330 Sgal Cocps A sgal s h phscal formao abou a masurd varabl bg

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Convergence of Quintic Spline Interpolation

Convergence of Quintic Spline Interpolation Inrnaonal Journal o ompur Applcaons 97 8887 Volum 7 No., Aprl onvrgnc o Qunc Spln Inrpolaon Y.P. Dub Dparmn O Mamacs, L.N..T. Jabalpur 8 Anl Sukla Dparmn O Mamacs Gan Ganga ollg O Tcnog, Jabalpur 8 ASTRAT

More information

Exponential Stability Analysis of a System Comprised of a Robot and its Associated Safety Mechanism

Exponential Stability Analysis of a System Comprised of a Robot and its Associated Safety Mechanism rongs of nnul onfrn of hn nsu of ommunons Eponnl Sbl nlss of Ssm omprs of obo n s sso Sf Mhnsm Whu GUO ng YNG prmn of Mhms n nforms sn Zhngzhou Unvrs of lgh nusr Zhngzhou hn; E-ml: whguosr@hooomn; ngp66@hoon

More information

Solutions of the linearized Richards equation with arbitrary boundary and initial conditions: flux and soil moisture respectively

Solutions of the linearized Richards equation with arbitrary boundary and initial conditions: flux and soil moisture respectively Hydrology ays Soluons of h lnard Rchards uaon wh arbrary boundary and nal condons: flux and sol mosur rspcvly M. Mnan S. Pugnagh Unvrsà dgl Sud d Modna Rggo Emla p. Inggnra d Maral dllambn Va Vgnols 95

More information

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system 8. Quug sysms Cos 8. Quug sysms Rfrshr: Sml lraffc modl Quug dscl M/M/ srvr wag lacs Alcao o ack lvl modllg of daa raffc M/M/ srvrs wag lacs lc8. S-38.45 Iroduco o Tlraffc Thory Srg 5 8. Quug sysms 8.

More information

Economics 600: August, 2007 Dynamic Part: Problem Set 5. Problems on Differential Equations and Continuous Time Optimization

Economics 600: August, 2007 Dynamic Part: Problem Set 5. Problems on Differential Equations and Continuous Time Optimization THE UNIVERSITY OF MARYLAND COLLEGE PARK, MARYLAND Economcs 600: August, 007 Dynamc Part: Problm St 5 Problms on Dffrntal Equatons and Contnuous Tm Optmzaton Quston Solv th followng two dffrntal quatons.

More information

Single Correct Type. cos z + k, then the value of k equals. dx = 2 dz. (a) 1 (b) 0 (c)1 (d) 2 (code-v2t3paq10) l (c) ( l ) x.

Single Correct Type. cos z + k, then the value of k equals. dx = 2 dz. (a) 1 (b) 0 (c)1 (d) 2 (code-v2t3paq10) l (c) ( l ) x. IIT JEE/AIEEE MATHS y SUHAAG SIR Bhopl, Ph. (755)3 www.kolsss.om Qusion. & Soluion. In. Cl. Pg: of 6 TOPIC = INTEGRAL CALCULUS Singl Corr Typ 3 3 3 Qu.. L f () = sin + sin + + sin + hn h primiiv of f()

More information

Generalized Den Hartog tuned mass damper system for control of vibrations in structures

Generalized Den Hartog tuned mass damper system for control of vibrations in structures Earhqua Rssan Engnrng Sruurs VII 85 Gnralzd Dn Harog und ass dapr sys for onrol of vbraons n sruurs I. M. Abubaar B. J. M. ard Dparn of Cvl Engnrng, auly of Engnrng, Alahad Unvrsy, Sr, Lbya Absra Th Dn

More information

10/7/14. Mixture Models. Comp 135 Introduction to Machine Learning and Data Mining. Maximum likelihood estimation. Mixture of Normals in 1D

10/7/14. Mixture Models. Comp 135 Introduction to Machine Learning and Data Mining. Maximum likelihood estimation. Mixture of Normals in 1D Comp 35 Introducton to Machn Larnng and Data Mnng Fall 204 rofssor: Ron Khardon Mxtur Modls Motvatd by soft k-mans w dvlopd a gnratv modl for clustrng. Assum thr ar k clustrs Clustrs ar not rqurd to hav

More information

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control MEM 355 Prformanc Enhancmn of Dynamical Sysms A Firs Conrol Problm - Cruis Conrol Harry G. Kwany Darmn of Mchanical Enginring & Mchanics Drxl Univrsiy Cruis Conrol ( ) mv = F mg sinθ cv v +.2v= u 9.8θ

More information

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano

CHAPTER CHAPTER14. Expectations: The Basic Tools. Prepared by: Fernando Quijano and Yvonn Quijano Expcaions: Th Basic Prpard by: Frnando Quijano and Yvonn Quijano CHAPTER CHAPTER14 2006 Prnic Hall Businss Publishing Macroconomics, 4/ Olivir Blanchard 14-1 Today s Lcur Chapr 14:Expcaions: Th Basic Th

More information

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,

More information

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument Inrnaional Rsarch Journal of Applid Basic Scincs 03 Aailabl onlin a wwwirjabscom ISSN 5-838X / Vol 4 (): 47-433 Scinc Eplorr Publicaions On h Driais of Bssl Modifid Bssl Funcions wih Rspc o h Ordr h Argumn

More information

The Hyperelastic material is examined in this section.

The Hyperelastic material is examined in this section. 4. Hyprlastcty h Hyprlastc matral s xad n ths scton. 4..1 Consttutv Equatons h rat of chang of ntrnal nrgy W pr unt rfrnc volum s gvn by th strss powr, whch can b xprssd n a numbr of dffrnt ways (s 3.7.6):

More information

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari snbrg Modl Sad Mohammad Mahd Sadrnhaad Survsor: Prof. bdollah Langar bstract: n ths rsarch w tr to calculat analtcall gnvalus and gnvctors of fnt chan wth ½-sn artcls snbrg modl. W drov gnfuctons for closd

More information

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees

CPSC 211 Data Structures & Implementations (c) Texas A&M University [ 259] B-Trees CPSC 211 Daa Srucurs & Implmnaions (c) Txas A&M Univrsiy [ 259] B-Trs Th AVL r and rd-black r allowd som variaion in h lnghs of h diffrn roo-o-laf pahs. An alrnaiv ida is o mak sur ha all roo-o-laf pahs

More information

Fluctuation-Electromagnetic Interaction of Rotating Neutral Particle with the Surface: Relativistic Theory

Fluctuation-Electromagnetic Interaction of Rotating Neutral Particle with the Surface: Relativistic Theory Fluuaon-lroagn Inraon of Roang Nural Parl w Surfa: Rlavs or A.A. Kasov an G.V. Dov as on fluuaon-lroagn or w av alula rar for of araon fronal on an ang ra of a nural parl roang nar a polarabl surfa. parl

More information

Implementation of the Extended Conjugate Gradient Method for the Two- Dimensional Energized Wave Equation

Implementation of the Extended Conjugate Gradient Method for the Two- Dimensional Energized Wave Equation Lonardo Elcronc Jornal of raccs and Tchnolos ISSN 58-078 Iss 9 Jl-Dcmbr 006 p. -4 Implmnaon of h Endd Cona Gradn Mhod for h Two- Dmnsonal Enrd Wav Eqaon Vcor Onoma WAZIRI * Snda Ass REJU Mahmacs/Compr

More information

"Science Stays True Here" Journal of Mathematics and Statistical Science, Volume 2016, Science Signpost Publishing

Science Stays True Here Journal of Mathematics and Statistical Science, Volume 2016, Science Signpost Publishing "Scnc Says r Hr" Jornal of Mahmacs and Sascal Scnc Volm 6 343-356 Scnc Sgnpos Pblshng Mhod for a Solon o Som Class of Qas-Sac Problms n Lnar Vscolascy hory as Appld o Problms of Lnar orson of a Prsmac

More information

Mixing time with Coupling

Mixing time with Coupling Mixig im wih Couplig Jihui Li Mig Zhg Saisics Dparm May 7 Goal Iroducio o boudig h mixig im for MCMC wih couplig ad pah couplig Prsig a simpl xampl o illusra h basic ida Noaio M is a Markov chai o fii

More information

Notes on the stability of dynamic systems and the use of Eigen Values.

Notes on the stability of dynamic systems and the use of Eigen Values. Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon

More information

Boosting and Ensemble Methods

Boosting and Ensemble Methods Boosng and Ensmbl Mhods PAC Larnng modl Som dsrbuon D ovr doman X Eampls: c* s h arg funcon Goal: Wh hgh probably -d fnd h n H such ha rrorh,c* < d and ar arbrarly small. Inro o ML 2 Wak Larnng

More information

Discrete Shells Simulation

Discrete Shells Simulation Dscrt Shlls Smulaton Xaofng M hs proct s an mplmntaton of Grnspun s dscrt shlls, th modl of whch s govrnd by nonlnar mmbran and flxural nrgs. hs nrgs masur dffrncs btwns th undformd confguraton and th

More information

COMPUTER SCIENCE 349A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PARTS 1, 2

COMPUTER SCIENCE 349A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PARTS 1, 2 COMPUTE SCIENCE 49A SAMPLE EXAM QUESTIONS WITH SOLUTIONS PATS, PAT.. a Dene he erm ll-ondoned problem. b Gve an eample o a polynomal ha has ll-ondoned zeros.. Consder evaluaon o anh, where e e anh. e e

More information

Let s look again at the first order linear differential equation we are attempting to solve, in its standard form:

Let s look again at the first order linear differential equation we are attempting to solve, in its standard form: Th Ingraing Facor Mhod In h prvious xampls of simpl firs ordr ODEs, w found h soluions by algbraically spara h dpndn variabl- and h indpndn variabl- rms, and wri h wo sids of a givn quaion as drivaivs,

More information

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison

Economics 302 (Sec. 001) Intermediate Macroeconomic Theory and Policy (Spring 2011) 3/28/2012. UW Madison Economics 302 (Sc. 001) Inrmdia Macroconomic Thory and Policy (Spring 2011) 3/28/2012 Insrucor: Prof. Mnzi Chinn Insrucor: Prof. Mnzi Chinn UW Madison 16 1 Consumpion Th Vry Forsighd dconsumr A vry forsighd

More information

Midterm exam 2, April 7, 2009 (solutions)

Midterm exam 2, April 7, 2009 (solutions) Univrsiy of Pnnsylvania Dparmn of Mahmaics Mah 26 Honors Calculus II Spring Smsr 29 Prof Grassi, TA Ashr Aul Midrm xam 2, April 7, 29 (soluions) 1 Wri a basis for h spac of pairs (u, v) of smooh funcions

More information

Answer Homework 5 PHA5127 Fall 1999 Jeff Stark

Answer Homework 5 PHA5127 Fall 1999 Jeff Stark Answr omwork 5 PA527 Fall 999 Jff Stark A patint is bing tratd with Drug X in a clinical stting. Upon admiion, an IV bolus dos of 000mg was givn which yildd an initial concntration of 5.56 µg/ml. A fw

More information

EE243 Advanced Electromagnetic Theory Lec # 10: Poynting s Theorem, Time- Harmonic EM Fields

EE243 Advanced Electromagnetic Theory Lec # 10: Poynting s Theorem, Time- Harmonic EM Fields Appl M Fall 6 Nuruhr Lcur # r 9/6/6 4 Avanc lcromagnc Thory Lc # : Poynng s Thorm Tm- armonc M Fls Poynng s Thorm Consrvaon o nrgy an momnum Poynng s Thorm or Lnar sprsv Ma Poynng s Thorm or Tm-armonc

More information

Lecture 12: Introduction to nonlinear optics II.

Lecture 12: Introduction to nonlinear optics II. Lcur : Iroduco o olar opcs II r Kužl ropagao of srog opc sgals propr olar ffcs Scod ordr ffcs! Thr-wav mxg has machg codo! Scod harmoc grao! Sum frqucy grao! aramrc grao Thrd ordr ffcs! Four-wav mxg! Opcal

More information

9.4 Absorption and Dispersion

9.4 Absorption and Dispersion 9.4 Absoon and Dsson 9.4. loagn Wavs n Conduos un dnsy n a onduo ollowng Oh s law: J Th Maxwll s uaons n a onduo lna da should b: ρ B B B J To sly h suaon w agu ha h hag dsaas uly n a aoso od. Fo h onnuy

More information

Gauge Theories. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year

Gauge Theories. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year Gau Thors Elmary Parcl Physcs Sro Iraco Fomoloy o Bo cadmc yar - Gau Ivarac Gau Ivarac Whr do Laraas or Hamloas com from? How do w kow ha a cra raco should dscrb a acual hyscal sysm? Why s h lcromac raco

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ

More information

Superstructure-based Optimization for Design of Optimal PSA Cycles for CO 2 Capture

Superstructure-based Optimization for Design of Optimal PSA Cycles for CO 2 Capture Supersruure-asedOpmaonforDesgnof OpmalPSACylesforCO 2 Capure R. S. Kamah I. E. Grossmann L.. Begler Deparmen of Chemal Engneerng Carnege Mellon Unversy Psurgh PA 523 Marh 2 PSA n Nex Generaon Power Plans

More information

Chapter 7 Stead St y- ate Errors

Chapter 7 Stead St y- ate Errors Char 7 Say-Sa rror Inroucon Conrol ym analy an gn cfcaon a. rann ron b. Sably c. Say-a rror fnon of ay-a rror : u c a whr u : nu, c: ouu Val only for abl ym chck ym ably fr! nu for ay-a a nu analy U o

More information

State Observer Design

State Observer Design Sa Obsrvr Dsgn A. Khak Sdgh Conrol Sysms Group Faculy of Elcrcal and Compur Engnrng K. N. Toos Unvrsy of Tchnology Fbruary 2009 1 Problm Formulaon A ky assumpon n gnvalu assgnmn and sablzng sysms usng

More information