ECE542, Fall 2004 Homework 7 Solutions
|
|
- Norah Montgomery
- 5 years ago
- Views:
Transcription
1 EECE54: Dgtal Cmmuncatns Thry Prf. M. Hayat ECE54, Fall 004 Hmwrk 7 Slutns Prblm. Unn Bund: Ρ Ρ annunc, 0 { snt} dy Q But Ρ{ annunc snt} f ( y ( (Assum ( If <, Ρ{ annunc snt} f ( y dy Q 4 6 Ρ 6Q 4Q Q 4 Nt: Fr xampl, 6Q cms frm sx cmbnatns fr whch. Ths ar (,, (,3, ( 3,4, ( 4,3, (,, ( 3,. Fr th spcfd, valus f and w hav: 3 Ρ Q( Q( 4 Q( Th unn bund s farly tght n ths xampl.. Bhattachanya Bund: Ρ [ ( y f ( y ] f, Us th fact that [ f y f ( y ] t dy dt ( 8 ( dy π and sm algbrac manpulatns t fnd: 9 Ρ Ths s largr than th unn bund bcaus Ρ ( s nw bng uppr bundd whr n th unn bund cas t was calculatd xactly.
2 EECE54: Dgtal Cmmuncatns Thry Prf. M. Hayat. Gallagr Bund: Frm class nts: [ ] ( ( Ε Ρ π π π π ( ( ( ( ( ( ( (, 0, ( ( Y y y y y y dy dy dy y f y f whr Y s a zr-man Gaussan r.v wth varanc. Nw [ ] N Y α α Ε fr any R α S, π Ε Y P ( ( (, By Jnsn s Inqualty (assumng 0 Hnc, Ε Y P π π ( ( ( ( ( ( ( ( ( ( (, S MATLAB pt t s th dpndnc f th bund n. Nt that th mnmum s at. Th Gallagr bund s quvalnt t th Bhattachanya bund n ths xampl. %Gallagr- bund plt
3 EECE54: Dgtal Cmmuncatns Thry Prf. M. Hayat clar r[0.6:.00:] ; %r0.5; Nrlngth(r; sg0.5; al./(*(sg^*(lr; %ba/(lr; aa(a./r.*{(i./(r.*(r - ; bba.*((l./r -; m [ 3 5 7]; Pzrs(4,Nr; fr l:4, pzrs(l,nr; fr l:4, f ( ~ ppxp(aa*(m(.^bb*(m(.^*m(*m{.*(a./(r.* (r; nd nd P(,:p.^r; nd P 0.5*sum(P,; subplt (,, smlgy(r,p,'k-' xlabl( {\rh} ' ylabl('gallager BOUND' subplt(,, plt(r(flr(nr/.:nr,p (flr(nr/.:nr,'k-' xlablc ( {\rh}' ylabl('gallager BOUND' 3
4 EECE54: Dgtal Cmmuncatns Thry Prf. M. Hayat Prblm 5.6 a By nspctn, a A ; b a b d r r r sn 45 r ( sn 45 r A A c 8-QAM: Ρ r r r A r A A 8-PSK: Ρ 8 8 av ( 0 5 av 0 Pwr advantag 6 (8-QAM s mr advantagus (.37 ( A 8 Prblm 5.7 By nspctn, 4
5 EECE54: Dgtal Cmmuncatns Thry Prf. M. Hayat r d 0 Nw, d r r r cs(45 s Pwr: Ρ 4 d 4 ; Ρ 8 d d d Addtnal pwr ( 5.3dB r d Prblm PSK: Max bt BFSK: rat Max symbl rat lg M 00 KHz 00 Kbts / s As abv wth M ; w gt 00 Kbts / s. Sparatn s btwn adacnt T frquncs. S max sparatn s. T S, W and # bts / symbl bts / sym. T 5 T 0 s wth bts / sym W S # bts / s 00 Kbts / s T 5
6 ECE54, Sprng 004 HW#8 Slutns Cnsdr an all-zr cdwrd cnsstng f k bts. Thr s a ttal k - rrr k k k pattrs. On th thr hand, th ttal numbr f bt rrrs s k. Thus, by assumng that all symbls ar qually prbabl, th avrag numbr f bt rrrs pr symbl rrr s k k- / k - (bt rrrs/pr symbl rrr. Nw lt P b b th prbablty f a bt rrr. Thn, th avrag numbr f bt rrrs pr symbl rrr s kp b. But, ths numbr s als qual t th prbablty f symbl rrr, P S, tms k k- / k -, whch stablshs th dsrd rlatnshp. In th cas f gray cdng, w nly nd t cnsdr n-bt symbl rrrs and gnr all thr symbl rrrs. Wth ths assumptn and by assumng as bfr that w cnsdr th all-zr cdwrd, thr wll b a ttal f k symbl rrrs. Nw nt that n ths cas th ttal numbr f bt rrrs s als k, snc ach symbl rrr rsults n nly n bt rrr. Hnc, th avrag numbr f bt rrrs pr symbl rrr s. Thus, by xamnng th avrag numbr f bt rrrs pr symbl rrr (as n Prblm w btan k P b P S. 3 Part I: Pck ε>0. Thr xsts δ >0 such that f(x- f(y < ε whnvr x- y < δ. Assum x n cnvrgs t x. Thn, w can chs an ntgr n 0, dpndng n δ, s that x n - x < δ whnvr n>n 0. Thus, f(x- f(x n < ε fr all n>n 0, r statd dffrntly: f(x n f(x. Part II: Lt A b a clsd and bundd st. Put B f(a and cnsdr a cnvrgnt squnc y n B. Lt y lm y n. W nd t shw that y B. Nt that y n f(x n fr sm x n A. Snc A s bundd, th squnc x n has a cnvrgnt subsqunc squnc x n,. Mrvr, snc A s clsd, lm x n, ls n A. Lt x lm x n,. Snc f s cntnuus, lm f(x n, f(x. But x A, whch mpls that f(x B (snc x A. But y lm n y n lm n f(x n lm f(x n, f(x B, whch prvs that B s clsd. Prf that B s bundd (by cntradctn: Assum that B s unbundd. Ths mans that w can fnd an ncrasng squnc y n B wth lm y n. Cnsdr th squnc x n A dfnd by y n f(x n. Snc A s bundd, th squnc x n has a cnvrgnt subsqunc x n,, and lm x n, x A snc A s clsd. By cntnuty, hwvr, lm y n, lm f(x n, f(x, and f(x< by dfntn f a functn vr A. Ths cntradcts th assumptn that y n, s dvrgnt. Hnc, B s bundd. 4 Pck a cnvrgnt squnc f vctrs x m frm th prscrbd st, whch w wll call E. Namly, x m x. W nd t shw that x s n th st E. Ths mans that x m - x 0 as m, whr. dnt Eucldan nrm. Ths m-dmnsnal
7 Prblm 4.3 : (a E [z(tz(t τ] E [{x(t τy(t t}{x(ty(t}] E [x(tx(t τ] E [y(ty(t τ] E [x(ty(t τ] E [y(tx(t τ] φ xx (τ φ yy (τ[φ yx (τφ xy (τ] But φ xx (τ φ yy (τand φ yx (τ φ xy (τ. Thrfr : E [z(tz(t τ] 0 (b E ( V frm th rsult n (a abv. Als : V T T 0 0 T 0 z(tdt E [z(az(b] dadb 0 T 0 E (VV T 0 E [z(az (b] dadb T T 0 0 N 0δ(a bdadb T 0 N 0da N 0 T Prblm 4.4 : E [x(t τx(t] A E [sn (πf c (t τθsn(πf c t θ] A cs πf cτ A E [cs (πf c(t τθ] whr th last qualty fllws frm th trgnmtrc dntty : sn A sn B [cs(a B cs(a B]. But : E [cs (πf c (t τθ] π 0 cs (πf c (t τθ p(θdθ π 0 cs (πf c (t τθ dθ 0 π Hnc : E [x(t τx(t] A cs πf cτ 46
8 Nt : Rlatnshp ( can als b btand by smpl dffrntatn f th rsdual rrr wth rspct t th cffcnts {s n }. Snc s n s, n gnral, cmplx-valud s n a n b n w hav t dffrntat wth rspct t bth ral and magnary parts : d da n E d [ da n s(t Kk s k f k (t ][ s(t K n s n f n (t ] dt 0 a nf n (t [ s(t K n s n f n (t ] a n f n (t [ s(t K n s n f n (t ] dt 0 a n R { f n(t [ s(t K n s n f n (t ]} dt 0 R { f n(t [ s(t K n s n f n (t ]} dt 0, n,,..., K whrwhavxpltdthdntty:(x x R{x}. Dffrntatn f E wth rspct t b n wll gv th crrspndng rlatnshp fr th magnary part; cmbnng th tw w gt (. Prblm 4.7 : Th prcdur s vry smlar t th n fr th ral-valud sgnals dscrbd n th bk (pags Th nly dffrnc s that th prctns shuld cnfrm t th cmplx-valud vctr spac : c s (tf (tdt and, n gnral fr th k-th functn : c k s k (tf (tdt,,,..., k Prblm 4.8 : Fr ral-valud sgnals th crrlatn cffcnts ar gvn by : km Ek E m s k(ts m (tdt and th Eucldan dstancs by : d ( km { E k E m } / E k E m km. Fr th sgnals n ths prblm : E, E, E 3 3, E
9 and: d ( d ( d ( d ( 4 5 d ( d ( Prblm 4.9 : Th nrgy f th sgnal wavfrm s m(t s: E s m (t dt s m(t M s k (t dt M k s m(tdt M M s M k (ts l (tdt k l M s m (ts k (tdt M s m (ts l (tdt M k M l E M M Eδ M kl k l M E E M E ( M M E E M Th crrlatn cffcnt s gvn by : mn s E m (ts n (tdt ( s E m (t ( M s k (t s n (t M k M ( s E m (ts n (tdt M M s M k (ts l (tdt k l ( M s E n (ts k (tdt M s m (ts l (tdt M k M l ME E E M M M M M M M s l (t dt l Prblm 4.0 : (a T shw that th wavfrms f n (t, n,...,3 ar rthgnal w hav t prv that: f m (tf n (tdt 0, m n 49
10 (c Th transtn matrx s : I n I n B n I n B n Th crrspndng Markv chan mdl s llustratd n th fllwng fgur : / / / / / 0 - /4 /4 æ Prblm 4. : (a I n a n a n, wth th squnc {a n } bng uncrrlatd randm varabls (. E (a nm a n δ(m. Hnc : φ (m E [I nm I n ]E[(a nm a nm (a n a n ] δ(m δ(m δ(m, m0, m± 0,.w. (b Φ uu (f T G(f Φ (f whr: Φ (f m φ (mxp(πfmt xp(4πft xp(4πft [ cs 4πfT] 4sn πft and G(f (AT ( sn πft πft 60
11 Thrfr : ( sn πft Φ uu (f 4A T sn πft πft (c { If {a n } taks } th valus (0, wth qual prbablty thn E(a n / ande(a nm a n /4, m 0 [ δ(m] /4. Thn : /, m0 φ (m E [I nm I n ]φ aa (0 φ aa ( φ aa ( [δ(m δ(m δ(m ] 4 and Φ (f m φ (mxp(πfmt sn πft Φ uu (f A T ( sn πft πft sn πft Thus, w btan th sam rsult as n (b, but th magntud f th varus quantts s rducd by a factr f 4. Prblm 4.3 : x(t R [u(txp(πf c t] whr u(t s(t ± ŝ(t. Hnc : S : U(f S(f ± Ŝ(f whr Ŝ(f { S(f, f > 0 S(f, f < 0 U(f { S(f ± S(f, f > 0 S(f S(f, f < 0 } { S(f r0, f > 0 0rS(f, f < 0 Snc th lwpass quvalnt f x(t s sngl-sdband, w cnclud that x(t s a sngl-sdband sgnal, t. Supps, fr xampl, that s(t has th fllwng spctrum. Thn, th spctra f th sgnals u(t (shwn n th fgur fr th cas u(t s(tŝ(t and x(t ar sngl-sdband } } 6
12 and : Φ vv (f a T U(f Fr th rctangular puls f QPSK, w hav : ( φ uu (τ T τ, 0 τ T T Fr th MSK puls : φ uu (τ u(t τu (tdt T τ T ( τ T cs π τ τ T π 0 sn πt T π τ sn T π(tτ sn dt T Prblm 4.8 : (a Fr smplcty w assum bnary CPM. Snc t s partal rspns : q(t T 0 u(tdt /4 q(t T 0 u(tdt /, q(t /, t > T s nly th last tw symbls wll hav an ffct n th phas : φ(t; I πh n k I k q(t kt, nt t nt T n k I k π (I n q(t (n T I n q(t nt, π It s asy t s that, aftr th frst symbl, th phas slp s : 0 f I n, I n hav dffrnt sgns, and sgn(i n π/(t fi n, I n hav th sam sgn. At th trmnal pnt t (n T th phas s : φ((n T ; I π n k Hnc th phas tr s as shwn n th fllwng fgur : I k π 4 I n 67
13 t0 tt tt t3t t4t 7π/4-5π/ π/ π/ π/ π/ π/ π/4 - æ (b Th stat trlls s btand frm th phas-tr mdul π: t0 tt tt t3t t4t - - φ 3 7π/4 - - φ 5π/ φ 3π/ φ 0 π/ æ 68
14 (c Th stat dagram s shwn n th fllwng fgur (wth th (I n, I n r(i n, I n thatcaus th rspctv transtns shwn n parnthss (-,. (-,- (-,. φ 5π/4 φ 3π/4 (, (-,- (, (, (-,- (, φ 3 7π/4 φ 0 π/4 (-,-.. (-,, (-, æ Prblm 4.9 : φ(t; I πh n k I k q(t kt (a Full rspns bnary CPFSK (q(t /: ( h /3. At th nd f ach bt ntrval th phas s : π nk I 3 k π nk I 3 k. Hnc th pssbl trmnal phas stats ar {0, π/3, 4π/3}. ( h 3/4. At th nd f ach bt ntrval th phas s : π 3 nk I 4 k 3π nk I 4 k. Hnc th pssbl trmnal phas stats ar {0, π/4, π/, 3π/4, π, 5π/4, 3π/, 7π/4} (b Partal rspns L 3, bnary CPFSK : q(t /6, q(t /3, q(3t /. Hnc, at th nd f ach bt ntrval th phas s : πh n k I k πh (I n /3I n /6 πh n k I k πh 3 (I n I n Th symbl lvls n th parnthss can tak th valus {3,,, 3}. S : ( h /3. Th pssbl trmnal phas stats ar : {0, π/9, 4π/9, π/3, 8π/9, 0π/9, 4π/3, 4π/9, 6π/9} 69
15 ( h 3/4. Th pssbl trmnal phas stats ar : {0,π/4,π/, 3π/4,π,5π/4, 3π/, 7π/4} Prblm 4.30 : Th 6-QAM sgnal s rprsntd as s(t I n cs πftq n sn πft, whr I n {±, ±3},Q n {±, ±3}. A suprpstn f tw 4-QAM (4-PSK sgnals s : s(t G [A n cs πft B n sn πft]c n cs πft C n sn πft whr A n,b n, C n,d n {±}. Clarly : I n GA n C n,q n GB n D n. Frm ths quatns t s asy t s that G gvs th rqurs quvalnc. Prblm 4.3 : W ar gvn by Equatn ( that th pulss c k (t ar dfnd as L c k (t s 0 (t s 0 [t (n La k,n ], 0 t T mn[l( a k,n n] n n Hnc, th tm supprt f th puls c k (t s 0 t T mn[l( a k,n n] n W nd t fnd th ndx ˆn whch mnmzs S L( a k,n n, r quvalntly maxmzs S La k,n n : ˆn argmax [La k,n n], n,..., L, a k,n 0, n It s asy t shw that ˆn L ( f all a k,n, n 0,,..., L ar zr (fr a spcfc k, and ˆn max{n : a k,n } ( thrws. Th frst cas ( s shwn mmdatly, snc f all a k,n, n 0,,..., L ar zr, thn max n S max n n, n 0,,..., L. Fr th scnd cas (, assum that thr ar n,n such that : n <n and a k,n, a k,n 0. ThnS (n L n >n ( S (n, snc n n <L du t th allwabl rang f n. S, fndng th bnary rprsntatn f k, k 0,,..., L, w fnd ˆn and th crrspndng S(n whch gvs th xtnt f th tm supprt f c k (t: k 0 a k,l 0,..., a k, 0, a k, 0 ˆn L S L k a k,l 0,..., a k, 0, a k, ˆn S L k /3 a k,l 0,..., a k,, a k, 0/ ˆn S L 70
Math 656 Midterm Examination March 27, 2015 Prof. Victor Matveev
Math 656 Mdtrm Examnatn March 7, 05 Prf. Vctr Matvv ) (4pts) Fnd all vals f n plar r artsan frm, and plt thm as pnts n th cmplx plan: (a) Snc n-th rt has xactly n vals, thr wll b xactly =6 vals, lyng n
More information:2;$-$(01*%<*=,-./-*=0;"%/;"-*
!"#$%'()%"*#%*+,-./-*+01.2(.*3+456789*!"#$%"'()'*+,-."/0.%+1'23"45'46'7.89:89'/' ;8-,"$4351415,8:+#9' Dr. Ptr T. Gallaghr Astrphyscs Rsarch Grup Trnty Cllg Dubln :2;$-$(01*%
More information9.5 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 informationLECTURE 5 Guassian Wave Packet
LECTURE 5 Guassian Wav Pact 1.5 Eampl f a guassian shap fr dscribing a wav pact Elctrn Pact ψ Guassian Assumptin Apprimatin ψ As w hav sn in QM th wav functin is ftn rprsntd as a Furir transfrm r sris.
More informationGrand Canonical Ensemble
Th nsmbl of systms mmrsd n a partcl-hat rsrvor at constant tmpratur T, prssur P, and chmcal potntal. Consdr an nsmbl of M dntcal systms (M =,, 3,...M).. Thy ar mutually sharng th total numbr of partcls
More informationVowel package manual
Vwl pckg mnl FUKUI R Grdt Schl f Hmnts nd Sclgy Unvrsty f Tky 28 ctbr 2001 1 Drwng vwl dgrms 1.1 Th vwl nvrnmnt Th gnrl frmt f th vwl nvrnmnt s s fllws. [ptn(,ptn,)] cmmnds fr npttng vwls ptns nd cmmnds
More informationChapter 2 Linear Waveshaping: High-pass Circuits
Puls and Digital Circuits nkata Ra K., Rama Sudha K. and Manmadha Ra G. Chaptr 2 Linar Wavshaping: High-pass Circuits. A ramp shwn in Fig.2p. is applid t a high-pass circuit. Draw t scal th utput wavfrm
More informationModern Physics. Unit 5: Schrödinger s Equation and the Hydrogen Atom Lecture 5.6: Energy Eigenvalues of Schrödinger s Equation for the Hydrogen Atom
Mdrn Physics Unit 5: Schrödingr s Equatin and th Hydrgn Atm Lctur 5.6: Enrgy Eignvalus f Schrödingr s Equatin fr th Hydrgn Atm Rn Rifnbrgr Prfssr f Physics Purdu Univrsity 1 Th allwd nrgis E cm frm th
More informationThe Fourier Transform
/9/ Th ourr Transform Jan Baptst Josph ourr 768-83 Effcnt Data Rprsntaton Data can b rprsntd n many ways. Advantag usng an approprat rprsntaton. Eampls: osy ponts along a ln Color spac rd/grn/blu v.s.
More informationRandom Process Part 1
Random Procss Part A random procss t (, ζ is a signal or wavform in tim. t : tim ζ : outcom in th sampl spac Each tim w rapat th xprimnt, a nw wavform is gnratd. ( W will adopt t for short. Tim sampls
More informationThe 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 informationAnother Explanation of the Cosmological Redshift. April 6, 2010.
Anthr Explanatin f th Csmlgical Rdshift April 6, 010. Jsé Francisc García Juliá C/ Dr. Marc Mrncian, 65, 5. 4605 Valncia (Spain) E-mail: js.garcia@dival.s h lss f nrgy f th phtn with th tim by missin f
More informationLecture 3: Phasor notation, Transfer Functions. Context
EECS 5 Fall 4, ctur 3 ctur 3: Phasor notaton, Transfr Functons EECS 5 Fall 3, ctur 3 Contxt In th last lctur, w dscussd: how to convrt a lnar crcut nto a st of dffrntal quatons, How to convrt th st of
More information22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.
Subjct Chmistry Papr No and Titl Modul No and Titl Modul Tag 8/ Physical Spctroscopy / Brakdown of th Born-Oppnhimr approximation. Slction ruls for rotational-vibrational transitions. P, R branchs. CHE_P8_M
More informationTopic 5: Discrete-Time Fourier Transform (DTFT)
ELEC36: Signals And Systms Tpic 5: Discrt-Tim Furir Transfrm (DTFT) Dr. Aishy Amr Cncrdia Univrsity Elctrical and Cmputr Enginring DT Furir Transfrm Ovrviw f Furir mthds DT Furir Transfrm f Pridic Signals
More informationFrequency Response. Lecture #12 Chapter 10. BME 310 Biomedical Computing - J.Schesser
Frquncy Rspns Lcur # Chapr BME 3 Bimdical Cmpuing - J.Schssr 99 Idal Filrs W wan sudy Hω funcins which prvid frquncy slciviy such as: Lw Pass High Pass Band Pass Hwvr, w will lk a idal filring, ha is,
More informationLecture 27: The 180º Hybrid.
Whits, EE 48/58 Lctur 7 Pag f 0 Lctur 7: Th 80º Hybrid. Th scnd rciprcal dirctinal cuplr w will discuss is th 80º hybrid. As th nam implis, th utputs frm such a dvic can b 80º ut f phas. Thr ar tw primary
More informationEven/Odd Mode Analysis of the Wilkinson Divider
//9 Wilkinn Dividr Evn and Odd Md Analyi.dc / Evn/Odd Md Analyi f th Wilkinn Dividr Cnidr a matchd Wilkinn pwr dividr, with a urc at prt : Prt Prt Prt T implify thi chmatic, w rmv th grund plan, which
More informationTypes of Communication
Tps f Cmmunicatin Analg: cntinuus ariabls with nis {rrr 0} 0 (imprfct) Digital: dcisins, discrt chics, quantizd, nis {rrr} 0 (usuall prfct) Mssag S, S, r S M Mdulatr (t) channl; adds nis and distrtin M-ar
More informationWp/Lmin. Wn/Lmin 2.5V
UNIVERITY OF CALIFORNIA Cllege f Engneerng Department f Electrcal Engneerng and Cmputer cences Andre Vladmrescu Hmewrk #7 EEC Due Frday, Aprl 8 th, pm @ 0 Cry Prblem #.5V Wp/Lmn 0.0V Wp/Lmn n ut Wn/Lmn.5V
More information120~~60 o D 12~0 1500~30O, 15~30 150~30. ..,u 270,,,, ~"~"-4-~qno 240 2~o 300 v 240 ~70O 300
1 Find th plar crdinats that d nt dscrib th pint in th givn graph. (-2, 30 ) C (2,30 ) B (-2,210 ) D (-2,-150 ) Find th quatin rprsntd in th givn graph. F 0=3 H 0=2~ G r=3 J r=2 0 :.1 2 3 ~ 300 2"~ 2,
More information3.4 Properties of the Stress Tensor
cto.4.4 Proprts of th trss sor.4. trss rasformato Lt th compots of th Cauchy strss tsor a coordat systm wth bas vctors b. h compots a scod coordat systm wth bas vctors j,, ar gv by th tsor trasformato
More informationN J of oscillators in the three lowest quantum
. a) Calculat th fractinal numbr f scillatrs in th thr lwst quantum stats (j,,,) fr fr and Sl: ( ) ( ) ( ) ( ) ( ).6.98. fr usth sam apprach fr fr j fr frm q. b) .) a) Fr a systm f lcalizd distinguishabl
More information10.5 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 informationΕρωτήσεις και ασκησεις Κεφ. 10 (για μόρια) ΠΑΡΑΔΟΣΗ 29/11/2016. (d)
Ερωτήσεις και ασκησεις Κεφ 0 (για μόρια ΠΑΡΑΔΟΣΗ 9//06 Th coffcnt A of th van r Waals ntracton s: (a A r r / ( r r ( (c a a a a A r r / ( r r ( a a a a A r r / ( r r a a a a A r r / ( r r 4 a a a a 0 Th
More informationLucas Test is based on Euler s theorem which states that if n is any integer and a is coprime to n, then a φ(n) 1modn.
Modul 10 Addtonal Topcs 10.1 Lctur 1 Prambl: Dtrmnng whthr a gvn ntgr s prm or compost s known as prmalty tstng. Thr ar prmalty tsts whch mrly tll us whthr a gvn ntgr s prm or not, wthout gvng us th factors
More informationcycle that does not cross any edges (including its own), then it has at least
W prov th following thorm: Thorm If a K n is drawn in th plan in such a way that it has a hamiltonian cycl that dos not cross any dgs (including its own, thn it has at last n ( 4 48 π + O(n crossings Th
More informationHardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R.
Hardy-Littlwood Conjctur and Excptional ral Zro JinHua Fi ChangLing Company of Elctronic Tchnology Baoji Shannxi P.R.China E-mail: fijinhuayoujian@msn.com Abstract. In this papr, w assum that Hardy-Littlwood
More informationReview - Probabilistic Classification
Mmoral Unvrsty of wfoundland Pattrn Rcognton Lctur 8 May 5, 6 http://www.ngr.mun.ca/~charlsr Offc Hours: Tusdays Thursdays 8:3-9:3 PM E- (untl furthr notc) Gvn lablld sampls { ɛc,,,..., } {. Estmat Rvw
More informationConsider 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 informationExternal Equivalent. EE 521 Analysis of Power Systems. Chen-Ching Liu, Boeing Distinguished Professor Washington State University
xtrnal quvalnt 5 Analyss of Powr Systms Chn-Chng Lu, ong Dstngushd Profssor Washngton Stat Unvrsty XTRNAL UALNT ach powr systm (ara) s part of an ntrconnctd systm. Montorng dvcs ar nstalld and data ar
More information10. The Discrete-Time Fourier Transform (DTFT)
Th Discrt-Tim Fourir Transform (DTFT Dfinition of th discrt-tim Fourir transform Th Fourir rprsntation of signals plays an important rol in both continuous and discrt signal procssing In this sction w
More informationCHAPTER 33: PARTICLE PHYSICS
Collg Physcs Studnt s Manual Chaptr 33 CHAPTER 33: PARTICLE PHYSICS 33. THE FOUR BASIC FORCES 4. (a) Fnd th rato of th strngths of th wak and lctromagntc forcs undr ordnary crcumstancs. (b) What dos that
More information2. Grundlegende Verfahren zur Übertragung digitaler Signale (Zusammenfassung) Informationstechnik Universität Ulm
. Grundlgnd Vrfahrn zur Übrtragung dgtalr Sgnal (Zusammnfassung) wt Dc. 5 Transmsson of Dgtal Sourc Sgnals Sourc COD SC COD MOD MOD CC dg RF s rado transmsson mdum Snk DC SC DC CC DM dg DM RF g physcal
More informationELEC 372 LECTURE NOTES, WEEK 11 Dr. Amir G. Aghdam Concordia University
ELEC 37 LECTURE NOTES, WEE Dr Amir Aghdam Cncrdia Univrity Part f th nt ar adaptd frm th matrial in th fllwing rfrnc: Mdrn Cntrl Sytm by Richard C Drf and Rbrt H Bihp, Prntic Hall Fdback Cntrl f Dynamic
More informationA 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 informationLecture 26: Quadrature (90º) Hybrid.
Whits, EE 48/58 Lctur 26 Pag f Lctur 26: Quadratur (9º) Hybrid. Back in Lctur 23, w bgan ur discussin f dividrs and cuplrs by cnsidring imprtant gnral prprtis f thrand fur-prt ntwrks. This was fllwd by
More informationEconomics 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 informationHeisenberg 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 information8-node quadrilateral element. Numerical integration
Fnt Elmnt Mthod lctur nots _nod quadrlatral lmnt Pag of 0 -nod quadrlatral lmnt. Numrcal ntgraton h tchnqu usd for th formulaton of th lnar trangl can b formall tndd to construct quadrlatral lmnts as wll
More informationHigh Energy Physics. Lecture 5 The Passage of Particles through Matter
High Enrgy Physics Lctur 5 Th Passag of Particls through Mattr 1 Introduction In prvious lcturs w hav sn xampls of tracks lft by chargd particls in passing through mattr. Such tracks provid som of th most
More informationNAME: 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 informationMicrowave Noise and LNA Design
Mcrwav and LA Dgn Mcrwav Crcut,6, JJEOG Outln Bac cncpt : thrmal n Equvalnt n tmpratur, n fgur maurmnt f pav ntwrk Rcvr dgn f trantr hry Maurmnt LA dgn bac LA dgn xampl Mcrwav Crcut,6, JJEOG Bac 3 Mcrwav
More informationFolding of Regular CW-Complexes
Ald Mathmatcal Scncs, Vol. 6,, no. 83, 437-446 Foldng of Rgular CW-Comlxs E. M. El-Kholy and S N. Daoud,3. Dartmnt of Mathmatcs, Faculty of Scnc Tanta Unvrsty,Tanta,Egyt. Dartmnt of Mathmatcs, Faculty
More informationSeptember 27, Introduction to Ordinary Differential Equations. ME 501A Seminar in Engineering Analysis Page 1. Outline
Introucton to Ornar Dffrntal Equatons Sptmbr 7, 7 Introucton to Ornar Dffrntal Equatons Larr artto Mchancal Engnrng AB Smnar n Engnrng Analss Sptmbr 7, 7 Outln Rvw numrcal solutons Bascs of ffrntal quatons
More informationHydrogen Atom and One Electron Ions
Hydrogn Atom and On Elctron Ions Th Schrödingr quation for this two-body problm starts out th sam as th gnral two-body Schrödingr quation. First w sparat out th motion of th cntr of mass. Th intrnal potntial
More information6. Negative Feedback in Single- Transistor Circuits
Lctur 8: Intrductin t lctrnic analg circuit 36--366 6. Ngativ Fdback in Singl- Tranitr ircuit ugn Paprn, 2008 Our aim i t tudy t ffct f ngativ fdback n t mall-ignal gain and t mall-ignal input and utput
More informationEAcos θ, where θ is the angle between the electric field and
8.4. Modl: Th lctric flux flows out of a closd surfac around a rgion of spac containing a nt positiv charg and into a closd surfac surrounding a nt ngativ charg. Visualiz: Plas rfr to Figur EX8.4. Lt A
More informationExam 1. It is important that you clearly show your work and mark the final answer clearly, closed book, closed notes, no calculator.
Exam N a m : _ S O L U T I O N P U I D : I n s t r u c t i o n s : It is important that you clarly show your work and mark th final answr clarly, closd book, closd nots, no calculator. T i m : h o u r
More informationSupplementary. Mode division multiplexing using an orbital angular momentum mode. sorter and MIMO-DSP over a graded-index few-mode optical fibre
Supplntary Md dvsn ultplxng usng an rbtal angular ntu d srtr and MIMO-DSP vr a gradd-ndx fw-d ptcal fbr Ha Huang 1,*, Gvann Mln 2,3,4,5,*, Martn P. J. Lavry 6,*, Gudng X 1, Yngxng Rn 1, Ynwn Ca 1, Nsar
More informationELEG 413 Lecture #6. Mark Mirotznik, Ph.D. Professor The University of Delaware
LG 43 Lctur #6 Mrk Mirtnik, Ph.D. Prfssr Th Univrsity f Dlwr mil: mirtni@c.udl.du Wv Prpgtin nd Plritin TM: Trnsvrs lctrmgntic Wvs A md is prticulr fild cnfigurtin. Fr givn lctrmgntic bundry vlu prblm,
More informationOutlier-tolerant parameter estimation
Outlr-tolrant paramtr stmaton Baysan thods n physcs statstcs machn larnng and sgnal procssng (SS 003 Frdrch Fraundorfr fraunfr@cg.tu-graz.ac.at Computr Graphcs and Vson Graz Unvrsty of Tchnology Outln
More information10/7/14. 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 informationMath 656 March 10, 2011 Midterm Examination Solutions
Math 656 March 0, 0 Mdtrm Eamnaton Soltons (4pts Dr th prsson for snh (arcsnh sng th dfnton of snh w n trms of ponntals, and s t to fnd all als of snh (. Plot ths als as ponts n th compl plan. Mak sr or
More informationShortest Paths in Graphs. Paths in graphs. Shortest paths CS 445. Alon Efrat Slides courtesy of Erik Demaine and Carola Wenk
S 445 Shortst Paths n Graphs lon frat Sls courtsy of rk man an arola Wnk Paths n raphs onsr a raph G = (V, ) wth -wht functon w : R. Th wht of path p = v v v k s fn to xampl: k = w ( p) = w( v, v + ).
More informationCOMPLEX NUMBER PAIRWISE COMPARISON AND COMPLEX NUMBER AHP
ISAHP 00, Bal, Indonsa, August -9, 00 COMPLEX NUMBER PAIRWISE COMPARISON AND COMPLEX NUMBER AHP Chkako MIYAKE, Kkch OHSAWA, Masahro KITO, and Masaak SHINOHARA Dpartmnt of Mathmatcal Informaton Engnrng
More informationBackground: We have discussed the PIB, HO, and the energy of the RR model. In this chapter, the H-atom, and atomic orbitals.
Chaptr 7 Th Hydrogn Atom Background: W hav discussd th PIB HO and th nrgy of th RR modl. In this chaptr th H-atom and atomic orbitals. * A singl particl moving undr a cntral forc adoptd from Scott Kirby
More information2F1120 Spektrala transformer för Media Solutions to Steiglitz, Chapter 1
F110 Spktrala transformr för Mdia Solutions to Stiglitz, Chaptr 1 Prfac This documnt contains solutions to slctd problms from Kn Stiglitz s book: A Digital Signal Procssing Primr publishd by Addison-Wsly.
More informationThe pn junction: 2 Current vs Voltage (IV) characteristics
Th pn junction: Currnt vs Voltag (V) charactristics Considr a pn junction in quilibrium with no applid xtrnal voltag: o th V E F E F V p-typ Dpltion rgion n-typ Elctron movmnt across th junction: 1. n
More informationSummary: 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 informationCOHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.
MTH rviw part b Lucian Mitroiu Th LOG and EXP functions Th ponntial function p : R, dfind as Proprtis: lim > lim p Eponntial function Y 8 6 - -8-6 - - X Th natural logarithm function ln in US- log: function
More information. This is made to keep the kinetic energy at outlet a minimum.
Runnr Francis Turbin Th shap th blads a Francis runnr is cmplx. Th xact shap dpnds n its spciic spd. It is bvius rm th quatin spciic spd (Eq.5.8) that highr spciic spd mans lwr had. This rquirs that th
More informationProd.C [A] t. rate = = =
Concntration Concntration Practic Problms: Kintics KEY CHEM 1B 1. Basd on th data and graph blow: Ract. A Prod. B Prod.C..25.. 5..149.11.5 1..16.144.72 15..83.167.84 2..68.182.91 25..57.193.96 3..5.2.1
More informationLectur 22. RF and Microwave Circuit Design Γ-Plane and Smith Chart Analysis. ECE 303 Fall 2005 Farhan Rana Cornell University
ctur RF ad Micrwav Circuit Dig -Pla ad Smith Chart Aalyi I thi lctur yu will lar: -pla ad Smith Chart Stub tuig Quartr-Wav trafrmr ECE 33 Fall 5 Farha Raa Crll Uivrity V V Impdac Trafrmati i Tramii i ω
More informationSearch sequence databases 3 10/25/2016
Sarch squnc databass 3 10/25/2016 Etrm valu distribution Ø Suppos X is a random variabl with probability dnsity function p(, w sampl a larg numbr S of indpndnt valus of X from this distribution for an
More informationCorrelation in tree The (ferromagnetic) Ising model
5/3/00 :\ jh\slf\nots.oc\7 Chaptr 7 Blf propagato corrlato tr Corrlato tr Th (frromagtc) Isg mol Th Isg mol s a graphcal mol or par ws raom Markov fl cosstg of a urct graph wth varabls assocat wth th vrtcs.
More informationSelf-Adjointness and Its Relationship to Quantum Mechanics. Ronald I. Frank 2016
Ronald I. Frank 06 Adjoint https://n.wikipdia.org/wiki/adjoint In gnral thr is an oprator and a procss that dfin its adjoint *. It is thn slf-adjoint if *. Innr product spac https://n.wikipdia.org/wiki/innr_product_spac
More informationEE 119 Homework 6 Solution
EE 9 Hmwrk 6 Slutin Prr: J Bkr TA: Xi Lu Slutin: (a) Th angular magniicatin a tlcp i m / th cal lngth th bjctiv ln i m 4 45 80cm (b) Th clar aprtur th xit pupil i 35 mm Th ditanc btwn th bjctiv ln and
More informationSoft k-means Clustering. Comp 135 Machine Learning Computer Science Tufts University. Mixture Models. Mixture of Normals in 1D
Comp 35 Machn Larnng Computr Scnc Tufts Unvrsty Fall 207 Ron Khardon Th EM Algorthm Mxtur Modls Sm-Suprvsd Larnng Soft k-mans Clustrng ck k clustr cntrs : Assocat xampls wth cntrs p,j ~~ smlarty b/w cntr
More informationENGI 4421 Probability & Statistics
Lecture Ntes fr ENGI 441 Prbablty & Statstcs by Dr. G.H. Gerge Asscate Prfessr, Faculty f Engneerng and Appled Scence Seventh Edtn, reprnted 018 Sprng http://www.engr.mun.ca/~ggerge/441/ Table f Cntents
More informationCh. 24 Molecular Reaction Dynamics 1. Collision Theory
Ch. 4 Molcular Raction Dynamics 1. Collision Thory Lctur 16. Diffusion-Controlld Raction 3. Th Matrial Balanc Equation 4. Transition Stat Thory: Th Eyring Equation 5. Transition Stat Thory: Thrmodynamic
More informationRandom Access Techniques: ALOHA (cont.)
Random Accss Tchniqus: ALOHA (cont.) 1 Exampl [ Aloha avoiding collision ] A pur ALOHA ntwork transmits a 200-bit fram on a shard channl Of 200 kbps at tim. What is th rquirmnt to mak this fram collision
More informationAnalyzing Frequencies
Frquncy (# ndvduals) Frquncy (# ndvduals) /3/16 H o : No dffrnc n obsrvd sz frquncs and that prdctd by growth modl How would you analyz ths data? 15 Obsrvd Numbr 15 Expctd Numbr from growth modl 1 1 5
More informationECE602 Exam 1 April 5, You must show ALL of your work for full credit.
ECE62 Exam April 5, 27 Nam: Solution Scor: / This xam is closd-book. You must show ALL of your work for full crdit. Plas rad th qustions carfully. Plas chck your answrs carfully. Calculators may NOT b
More informationTh n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v
Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v ll f x, h v nd d pr v n t fr tf l t th f nt r n r
More informationSupplementary Materials
6 Supplmntary Matrials APPENDIX A PHYSICAL INTERPRETATION OF FUEL-RATE-SPEED FUNCTION A truck running on a road with grad/slop θ positiv if moving up and ngativ if moving down facs thr rsistancs: arodynamic
More informationA Brief and Elementary Note on Redshift. May 26, 2010.
A Brif and Elmntary Nt n Rdshift May 26, 2010. Jsé Francisc García Juliá C/ Dr. Marc Mrncian, 65, 5. 46025 Valncia (Spain) E-mail: js.garcia@dival.s Abstract A rasnabl xplanatin f bth rdshifts: csmlgical
More informationSection 11.6: Directional Derivatives and the Gradient Vector
Sction.6: Dirctional Drivativs and th Gradint Vctor Practic HW rom Stwart Ttbook not to hand in p. 778 # -4 p. 799 # 4-5 7 9 9 35 37 odd Th Dirctional Drivativ Rcall that a b Slop o th tangnt lin to th
More informationElements of Statistical Thermodynamics
24 Elmnts of Statistical Thrmodynamics Statistical thrmodynamics is a branch of knowldg that has its own postulats and tchniqus. W do not attmpt to giv hr vn an introduction to th fild. In this chaptr,
More informationAn Application of Hardy-Littlewood Conjecture. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R.China
An Application of Hardy-Littlwood Conjctur JinHua Fi ChangLing Company of Elctronic Tchnology Baoji Shannxi P.R.China E-mail: fijinhuayoujian@msn.com Abstract. In this papr, w assum that wakr Hardy-Littlwood
More informationST 524 NCSU - Fall 2008 One way Analysis of variance Variances not homogeneous
ST 54 NCSU - Fall 008 On way Analyss of varanc Varancs not homognous On way Analyss of varanc Exampl (Yandll, 997) A plant scntst masurd th concntraton of a partcular vrus n plant sap usng ELISA (nzym-lnkd
More information² Ý ² ª ² Þ ² Þ Ң Þ ² Þ. ² à INTROIT. huc. per. xi, sti. su- sur. sum, cum. ia : ia, ia : am, num. VR Mi. est. lis. sci. ia, cta. ia.
str Dy Ps. 138 R 7 r r x, t huc t m m, l : p - í pr m m num m, l l : VR M rá s f ct st sc n -, l l -. Rpt nphn s fr s VR ftr ch vrs Ps. 1. D n, pr bá m, t c g ví m : c g ví ss s nm m m, t r r r c nm m
More informationPhysics 256: Lecture 2. Physics
Physcs 56: Lctur Intro to Quantum Physcs Agnda for Today Complx Numbrs Intrfrnc of lght Intrfrnc Two slt ntrfrnc Dffracton Sngl slt dffracton Physcs 01: Lctur 1, Pg 1 Constructv Intrfrnc Ths wll occur
More informationAbstract Interpretation: concrete and abstract semantics
Abstract Intrprtation: concrt and abstract smantics Concrt smantics W considr a vry tiny languag that manags arithmtic oprations on intgrs valus. Th (concrt) smantics of th languags cab b dfind by th funzcion
More informationWhere k is either given or determined from the data and c is an arbitrary constant.
Exponntial growth and dcay applications W wish to solv an quation that has a drivativ. dy ky k > dx This quation says that th rat of chang of th function is proportional to th function. Th solution is
More informationCHAPTER 4. The First Law of Thermodynamics for Control Volumes
CHAPTER 4 T Frst Law of Trodynacs for Control olus CONSERATION OF MASS Consrvaton of ass: Mass, lk nrgy, s a consrvd proprty, and t cannot b cratd or dstroyd durng a procss. Closd systs: T ass of t syst
More informationJEE-2017 : Advanced Paper 2 Answers and Explanations
DE 9 JEE-07 : Advancd Papr Answrs and Explanatons Physcs hmstry Mathmatcs 0 A, B, 9 A 8 B, 7 B 6 B, D B 0 D 9, D 8 D 7 A, B, D A 0 A,, D 9 8 * A A, B A B, D 0 B 9 A, D 5 D A, B A,B,,D A 50 A, 6 5 A D B
More informationSection 3: Detailed Solutions of Word Problems Unit 1: Solving Word Problems by Modeling with Formulas
Sectn : Detaled Slutns f Wrd Prblems Unt : Slvng Wrd Prblems by Mdelng wth Frmulas Example : The factry nvce fr a mnvan shws that the dealer pad $,5 fr the vehcle. If the stcker prce f the van s $5,, hw
More informationEigenvalue Distributions of Quark Matrix at Finite Isospin Chemical Potential
Tim: Tusday, 5: Room: Chsapak A Eignvalu Distributions of Quark Matri at Finit Isospin Chmical Potntial Prsntr: Yuji Sasai Tsuyama National Collg of Tchnology Co-authors: Grnot Akmann, Atsushi Nakamura
More informationANALYSIS: The mass rate balance for the one-inlet, one-exit control volume at steady state is
Problm 4.47 Fgur P4.47 provds stady stat opratng data for a pump drawng watr from a rsrvor and dlvrng t at a prssur of 3 bar to a storag tank prchd 5 m abov th rsrvor. Th powr nput to th pump s 0.5 kw.
More information4.8 Huffman Codes. Wordle. Encoding Text. Encoding Text. Prefix Codes. Encoding Text
2/26/2 Word A word a word coag. A word contrctd ot of on of th ntrctor ar: 4.8 Hffan Cod word contrctd ng th java at at word.nt word a randozd grdy agorth to ov th ackng rob Encodng Txt Q. Gvn a txt that
More information2. Laser physics - basics
. Lasr physics - basics Spontanous and stimulatd procsss Einstin A and B cofficints Rat quation analysis Gain saturation What is a lasr? LASER: Light Amplification by Stimulatd Emission of Radiation "light"
More informationLECTURE 6 TRANSFORMATION OF RANDOM VARIABLES
LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt
More informationChemical Physics II. More Stat. Thermo Kinetics Protein Folding...
Chmical Physics II Mor Stat. Thrmo Kintics Protin Folding... http://www.nmc.ctc.com/imags/projct/proj15thumb.jpg http://nuclarwaponarchiv.org/usa/tsts/ukgrabl2.jpg http://www.photolib.noaa.gov/corps/imags/big/corp1417.jpg
More informationConsider the following passband digital communication system model. c t. modulator. t r a n s m i t t e r. signal decoder.
PASSBAND DIGITAL MODULATION TECHNIQUES Consder the followng passband dgtal communcaton system model. cos( ω + φ ) c t message source m sgnal encoder s modulator s () t communcaton xt () channel t r a n
More informationON THE ABSOLUTE CONVERGENCE OF A SERIES ASSOCIATED WITH A FOURIER SERIES. R. MOHANTY and s. mohapatra
ON THE ABSOLUTE CONVERGENCE OF A SERIES ASSOCIATED WITH A FOURIER SERIES R. MOHANTY and s. mhapatra 1. Suppse/(i) is integrable L in ( ir, it) peridic with perid 2ir, and that its Furier series at / =
More informationEngineering 323 Beautiful HW #13 Page 1 of 6 Brown Problem 5-12
Enginring Bautiful HW #1 Pag 1 of 6 5.1 Two componnts of a minicomputr hav th following joint pdf for thir usful liftims X and Y: = x(1+ x and y othrwis a. What is th probability that th liftim X of th
More informationCombinatorial Networks Week 1, March 11-12
1 Nots on March 11 Combinatorial Ntwors W 1, March 11-1 11 Th Pigonhol Principl Th Pigonhol Principl If n objcts ar placd in hols, whr n >, thr xists a box with mor than on objcts 11 Thorm Givn a simpl
More informationSection 6.1. Question: 2. Let H be a subgroup of a group G. Then H operates on G by left multiplication. Describe the orbits for this operation.
MAT 444 H Barclo Spring 004 Homwork 6 Solutions Sction 6 Lt H b a subgroup of a group G Thn H oprats on G by lft multiplication Dscrib th orbits for this opration Th orbits of G ar th right costs of H
More informationAs the matrix of operator B is Hermitian so its eigenvalues must be real. It only remains to diagonalize the minor M 11 of matrix B.
7636S ADVANCED QUANTUM MECHANICS Solutions Spring. Considr a thr dimnsional kt spac. If a crtain st of orthonormal kts, say, and 3 ar usd as th bas kts, thn th oprators A and B ar rprsntd by a b A a and
More information