A Lower Bound on the Error Exponent of Linear Block Codes over the Erasure Channel

Size: px
Start display at page:

Download "A Lower Bound on the Error Exponent of Linear Block Codes over the Erasure Channel"

Transcription

1 A Lowr Bod o th Error Expot of Liar Block Cods ovr th Erasr Chal Erico Paolii DEI, Uivrsity of Bologa via dll Uivrsità 50, Csa (FC Italy .paolii@ibo.it Gialigi Liva KN-SAN, Grma Arospac Ctr Müchr Strass 20, Wsslig, Grmay Gialigi.Liva@dlr.d arxiv: v cs.it] 2 Ja 209 Abstract A lowr bod o th maximm liklihood (ML dcodig rror xpot of liar block cod smbls, o th rasr chal, is dvlopd. Th lowr bod trs to b positiv, ovr a smbl spcific itrval of rasr probabilitis, wh th smbl wight spctral shap fctio tds to a gativ val as th fractioal codword wight tds to zro. For ths smbls w ca thrfor lowr bod th block-wis ML dcodig thrshold. Two xampls ar prstd, amly, liar radom parity-chck cods ad fixd-rat Raptor cods with liar radom prcodrs. Whil for th formr a fll aalytical soltio is possibl, for th lattr w ca lowr bod th ML dcodig thrshold o th rasr chal by simply solvig a 2 2 systm of oliar qatios. I. INTRODUCTION I this papr, a lowr bod o th ML dcodig rror xpot of liar cod smbls wh sd ovr rasr chals (ECs is drivd. Th calclatio of th bod rqirs th kowldg of th smbl wight spctral shap oly (dr a rlativly mild coditio, as it will b discssd latr. A gral lowr bod o th rror xpot, for ay discrt mmory-lss chal (DMC, was itrodcd ]. Its calclatio ivolvs th valatio of th maximm ratio btw th smbl avrag wight mrator (AWE ad th AWE of th radom liar cod smbl. Th tchiq of ] was sd i 2] to driv a lowr bod o th ML dcodig rror xpot of (xprgatd low-dsity paritychck (LDPC cod smbls 3]. Th bod o th rror xpot itrodcd i this papr is drivd from th tight io bod o th rror probability dr ML dcodig ovr th EC for liar block cod smbls of 4], 5]. A similar approach was followd i 6] to obtai a lowr bod o th rror xpot for xprgatd LDPC cod smbls. Or work xtds th rslt of 6] to ay liar cod smbl for which th wight spctral shap is kow, with th oly rqirmt that th logarithm of th AWE of th cod smbl (ormalizd to th block lgth covrgs i th block lgth iformly to th wight spctral shap. Th lowr bod trs ot to b positiv, ovr a smbl spcific itrval of rasr probabilitis, wh th smbl wight spctral shap fctio tds to a gativ val as th fractioal codword wight tds to zro. For A shortr vrsio of this papr, omittig som proofs, has b sbmittd to th 209 IEEE Itratioal Symposim o Iformatio Thory (ISIT. th liar radom cod smbl, w show that th bod o th rror xpot rcovrs Gallagr s radom codig rror xpot 7]. Th kowldg of th lowr bod o th rror xpot allows obtaiig a lowr bod o th smbl s ML rasr dcodig thrshold. As a xampl of applicatio, w driv a lowr bod o ML rasr dcodig thrshold for th smbl of fixd-rat Raptor cods 8] itrodcd i 9]. Rmarkably, th rslt is obtaid by simply solvig a 2 2 systm of oliar qatios. For th aalyzd smbls, th bod o th rror xpot drivd i this papr shows to b cosidrably tightr tha th gral bod of ] wh th lattr is spcializd to th biary rasr chal (BEC. II. PRELIMINARIES W cosidr trasmissio of liar block cods costrctd ovr F q, th fiit fild of ordr q, o a mmorylss q-ary rasr chal (q-ec o which ach codword symbol is corrctly rcivd with probability ǫ ad rasd with probability ǫ. A cod smbl is dfid as a st of cods alog with a probability distribtio o sch cods. W dot by C(,r,q a gric smbl of liar block cods ovr F q of lgth ad dsig rat r, ad by C C(,r,q a radom cod i th smbl. Th block-wis ML dcodig rror probability of C ovr th q-ec is idicatd as P B (C,ǫ ad its xpctatio ovr th smbl as E C(,r,q P B (C,ǫ]. W dfi th ML dcodig thrshold for th smbl C(,r,q ovr th q-ec as ǫ ML = spǫ (0, : E C(,r,qP B (C,ǫ] 0 as. Or startig poit is a ppr bod o E C(,r,q P B (C,ǫ] dvlopd i 4] for biary cods ad xtdd i 5] to obiary os. W hav ( E C(,r,q P B (C,ǫ] ǫ ( ǫ + ( r = =( r+ ( ǫ ( ǫ mi, w= ( w Aw ( w A(x = i=0 A ix i is th AWE of C. Giv th AWE A(x th growth rat of th wight distribtio, or wight spctral shap, of C(,r,q is dfid as 2 G(ω = lim loga ω. 2 I this papr all logarithms ar to th bas 2. (

2 W dot th Kllback-Liblr (KL divrgc btw two Brolli distribtios with paramtrs ad v, both i (0,, by D(,v = log v +( log v. Morovr, w dot by H b ( = log ( log(, 0, th biary tropy fctio. Throghot th papr w mak s of th lowr ad ppr bods ( + 2H b(k/ 2 H b(k/ (2 k o th biomial cofficit, valid for all ogativ itgrs k. For ay two pairs (x,y ad (x 2,y 2 of rals, w writ (x,y (x 2,y 2 wh x x 2 ad y y 2. Rcall that a sqcf of ral-vald fctios oa R covrgs iformly to th fctio f : A R o A 0 A if for ay ε > 0 thr xists 0 (ε sch that, for all 0 (ε, f (x f(x < ε x A 0. W writ f f to idicat that f covrgs to f iformly. A cssary ad sfficit coditio for iform covrgc is stablishd by th followig lmma 0, Th. 7.0]. Lmma. Ltlim f (x = f(x x A 0. Thf f o A 0 if ad oly if sp x A0 f (x f(x 0 as. Th followig rslt will also b sfl. Lmma 2. Lt f,g : A R R b bodd fctios. Th if f(x if g(x sp f(x g(x. x A x A x A III. MAIN RESULTS This sctio prsts th mai rslts of this papr. A lowr bod o th asymptotic rror xpot o liar block cod smbls ovr th rasr chal is first dvlopd i Thorm. Th, Thorm 2 shows how this bod allows lowr bodig ǫ ML for smbls for which G(ω is cotios i (0,] ad gativ for small ogh ω. Thorm. Cosidr a liar block cod smbl C(,r,q ad lt its wight spctral shap G(ω b wll-dfid i0, ]. If loga ω G(ω th lim log E C(,r,qP B (C,ǫ] E G (ǫ Th fctio f ǫ (δ is dfid as ad E G (ǫ = if δ (0,] f ǫ(δ. (3 f ǫ (δ = D(δ,ǫ+g + (δ g + (δ = max0,g(δ (4 ( ω ] g(δ = if δh b +H b (ω G(ω. (5 ω (0,δ] δ Proof: Th proof is orgaizd ito two parts. W first ppr bod th right-had sid of ( to obtai a lowr bod o log E C(,r,qP B (C,ǫ]. Th w tak th limit of th lowr bod as. Lowr bodig log E C(,r,qP B (C,ǫ]: Th ppr bod ( ca b writt i th qivalt, mor compact form E C(,r,q P B (C,ǫ] ( ǫ ( ǫ mi = Lttig w = ω ad = δ, w hav 3, w= E C(,r,q P B (C,ǫ] ( a max ǫ ( ǫ,..., ( ] Aw mi, ( w w= w ( b max ǫ ( ǫ,..., (( ] Aw mi, max ( w,..., w ( w = max ǫ δ ( ǫ ( δ δ,..., δ (( ] δ δ Aω mi, max ( ω,...,δ ω ω c max 2 (H b(δ+δlogǫ+( δlog( ǫ δ,..., mi, δ(+ (δhb(ω max 2 ω,...,δ d = max 2 D(δ,ǫ δ,..., mi, δ(+ (δhb(ω max sp mi δ Q (0,] f = sp mi 2 D(δ,ǫ, δ(+ δ (0,] 2 D(δ,ǫ, δ(+ ω,...,δ 2 sp ω Q (0,δ] sp ω (0,δ] ( w δ H b(ω+ δ H b(ω+ Aw ( w. ] log Aω ] log Aω ] 2 (δh b( ω δ H log Aω b(ω+ ] 2 (δh b( ω δ H log Aω b(ω+ I th abov dvlopmt: a ad b ar d to h l= f(l hmax l N h f(l. Morovr: c is d to applicatio of th ppr ad lowr bods i (2; d to xpadig H b (δ ad rcallig th dfiitio of KL divrgc; to th fact that th sprmm ovr Q (0,] ppr bods th maximm ovr,..., ad, similarly, th sprmm ovr Q (0,δ] ppr bods th maximm ovr,...,δ; f to th dsity of Q. I th fial xprssio, both δ ad ω ar cosidrd as ral variabls. Th bod (6 is valid for ay lgth, rat r, ad fild ordr q. 3 For otatioal simplicity hraftr w writ A ω i li of A ω. (6

3 Nxt w xploit (6 to bod log E C(,r,qP B (C,ǫ] from blow. Owig to logarithm mootoicity w obtai log E C(,r,qP B (C,ǫ] if δ (0,] f (δ. (7 f ǫ, (δ = log+d(δ,ǫ+max 0, if ω (0,δ] ( log q δ(+ ( ω δh b +H b (ω loga ω. δ 2 Takig th limit: Nxt, w tak th limit as i both sids of (7. To kp th otatio compact w dfi h δ, (ω = log ω b( δ(+ δh +H b (ω loga ω δ g (δ + = max0,g (δ. g (δ = if ω (0,δ] h δ,(ω ad W also dfi ( ω h δ (ω = δh b +H b (ω G(ω (8 δ so that g(δ dfid i (5 flfills g(δ = if ω (0,δ] h δ (ǫ. W start by showig that f ǫ, f ǫ o ay itrval a,] sch that 0 < a <. W first show that g (δ g(δ o a,]. To this prpos w writ sp g (δ g(δ = sp if h δ,(ω if h δ(ω ω (0,δ] ω (0,δ] a sp sp ω (0,δ] = sp sp ω (0,δ] b sp h δ, (ω h δ (ω log δ(+ δ(+ log + loga ω G(ω + sp loga ω G(ω ω (0,δ] a is d to Lmma 2 ad b to triagl iqality. I th last xprssio, th first addd covrgs to zro as sic q is costat ad δ a,] with a > 0. Morovr, th scod addd covrgs to zro d to th hypothsis that (/loga ω G(ω ad by Lmma. Agai by Lmma w cocld that g (δ g(δ. Uiform covrgc of g (δ to g(δ trs ito iform covrgc of g + (δ to g + (δ. I fact, w hav g + (δ g + (δ g (δ g(δ for all δ ad, which implis 0 sp g + (δ g+ (δ sp g (δ g(δ. By sqz thorm w hav sp g (δ g + + (δ 0 as, ad thrfor g + g + by Lmma. W ar ow i a positio to prov iform covrgc of f ǫ, to f ǫ. I fact, w hav sp f ǫ, (δ f ǫ (δ = sp log +g+ (δ g+ (δ log + sp g (δ g + + (δ w applid triagl iqality. Covrgc to zro of th last xprssio is garatd by g + g +. Uiform covrgc of f ǫ, (δ to f ǫ (δ lads s to th statmt, as follows. Rcall that, if f f o A 0 th lim if x A0 f (x = if x A0 lim f (x = if x A0 f(x, i.., w ca xchag limit ad ifimm. Hc w ca writ lim log E C(,r,qP B (C,ǫ] lim if f ǫ,(δ = if = if f ǫ(δ if δ (0,] f ǫ(δ. lim f ǫ,(δ I th prvios qatio array, th first iqality is jstifid by th fact that if α α, β β, ad α β for all (possibly, largr tha som 0, th α β. Morovr, th two qalitis ar jstifid by f ǫ, (δ f ǫ (δ. Rmark. Th fctio E G (ǫ giv by (3 is ogativ for all 0 < ǫ <, sic it is dfid as th ifimm of th sm of two ogativ qatitis. Morovr, sic E G (ǫ bods th rror xpot of th giv smbl from blow, it mst flfill E G (ǫ = 0 for all r ǫ. Rmark 2. Th lowr bod E G (ǫ trs ot to b slss for all smbls for which G(ω 0 as ω 0 +, as for ay sch smbl w hav E G (ǫ = 0 for all 0 < ǫ <. To s this, simply obsrv that dr this sttig w hav if ω (0,δ] h δ (ω lim ω 0 + h δ (ω = 0 for all 0 < δ, ad thrfor g + (δ = 0 for all 0 < δ. Th, E G (ǫ = if δ (0,] D(δ,ǫ = 0 for all 0 < ǫ < (simply tak δ = ǫ. Th followig lmma charactrizs th fctio g + (δ dfid i (4. Lmma 3. Th fctio g + (δ has th followig proprtis: g + (δ = 0 for all r δ ; 2 If G(ω is cotios i (0, th g + (δ is oicrasig ad cotios; 3 If G(ω is cotios i (0, ad lim ω 0 + G(ω = γ < 0 th: a lim δ 0 + g + (δ = γ ; b δ = spδ (0, r] : g + (δ > 0 is strictly positiv; c g + (δ > 0 δ (0,δ ; g + (δ = 0 δ δ,]. Proof: Tak ay r δ ad lt ǫ = δ. W mst hav E G (δ = if δ (0,] D(δ,δ + g + (δ] = 0 (Rmark. This yilds δ = δ, hc g + (δ = E G (δ = 0. 2 Th fctioh(ω,δ = h δ (ω is cotios ad drivabl with rspct to (w.r.t. δ. Sic h(ω, δ/ δ = log((δ ω/δ < 0, w hav h δ (ω > h δ2 (ω 0 < ω δ < δ 2. (9 Morovr, cotiity of G(ω trs ito cotiity of h δ (ω also w.r.t. ω. W dfi h δ (0 = lim ω 0 + h δ (ω, so that h δ (ω is cotios (w.r.t. ω o th compact 0,δ]. W lt ˆω δ = argmi ω 0,δ] h δ (ω. Takigz < y ad sig (9, w ca writ g(y = h y (ˆω y < h y (ˆω z < h z (ˆω z = g(z which shows that

4 g(δ is mootoically dcrasig ad, as a cosqc, that g + (δ is o-icrasig. Nxt, w prov cotiity of g(δ as it implis cotiity of g + (δ. W d to show that for ay θ > 0 thr xists α(θ s.t. z y < α(θ implis g(z g(y < θ. It is asy to prov that for ay θ > 0 thr xists α (θ s.t. z y < α (θ implis h z (ω h y (ω < θ/2 for all ω (0,miy,z. 4 W rfr to this proprty as Proprty. Morovr, cotiity of h δ (ω w.r.t. ω, srs that for ay θ > 0 thr xists α 2 (θ s.t. ξ ω < α 2 (θ implis h δ (ξ h δ (ω < θ/2. W rfr to this proprty as Proprty 2. Hraftr w addrss th casz < y, th argmt forz > y big vry similar. Lt y z < miα (θ,α 2 (θ ad rcall th abov dfiitio of ˆω y ad ˆω y. W d to distigish two cass. Cas : ˆω y < z. Proprty implis h z (ˆω y h y (ˆω y < θ/2. By (9 w hav h z (ˆω y > h y (ˆω y ad thrfor h z (ˆω y h y (ˆω y = h z (ˆω y h y (ˆω y = h z (ˆω y h z (ˆω z +h z (ˆω z h y (ˆω y a = h z (ˆω y h z (ˆω z + h z (ˆω z h y (ˆω y a is d to th dfiitios of ˆω z ad ˆω y ad to z < y. Ths, g(z g(y = h z (ˆω z h y (ˆω y h z (ˆω y h y (ˆω y < θ/2 < θ. Cas 2: ˆω y z. Proprty ad proprty 2 imply h z (z h y (z < θ/2 ad h y (z h y (ˆω y < θ/2, rspctivly, yildig (by triagl iqality h z (z h y (ˆω y h z (z h y (z + h y (z h y (ˆω y < θ. Howvr, w also hav h z (z h y (ˆω y a = h z (z h y (ˆω y = h z (z h z (ˆω z +h z (ˆω z h y (ˆω y b = h z (z h z (ˆω z + h z (ˆω z h y (ˆω y both a ad b ar d to h z (z h z (ˆω z h y (ˆω y. Hc, g(z g(y = h z (ˆω z h y (ˆω y h z (z h y (ˆω y < θ. 3a Lt s look at th bhavior of g + (δ as δ 0 +. Sic 0 < ω δ, w mst also hav ω 0 +, which yilds lim δ 0 + g + (δ = max0,lim (δ,ω (0 +,0 +,0<ω δh(ω,δ = γ. 3b Th fctio g + (δ tds to a positiv mbr as δ 0 + ad is zro for ay δ btw r ad. Sic th fctio is cotios, δ = spδ (0, r] : g + (δ > 0 mst b strictly positiv. 3c Sic g + (δ is also o-icrasig, it mst b positiv o th whol itrval (0,δ ad mst b ll ls (i.., o δ,]. Th xt thorm shows that, dr coditios o G(ω, thr xists a itrval of vals of ǫ ovr which E G (ǫ is positiv. For th corrspodig smbls, E G (ǫ is thrfor sfl to lowr bod ǫ ML. 4 Th proof is basd o th obsrvatio that h z(ω h y(ω icrass mootoically with ω, yildig h z(ω h y(ω h z(m h y(m = MH b ( z y /M, M = maxz,y. Cotiity of H b ( lads to th coclsio. Thorm 2. Ltδ = spδ (0, r] : g + (δ > 0 r. If G(ω is cotios i (0, ad lim ω 0 + G(ω < 0, th E G (ǫ > 0 ǫ (0,δ ad E G (ǫ = 0 ǫ δ,], ad thrfor ǫ ML δ. Proof: Tak ay ǫ s.t. δ ǫ. W hav 0 E G (ǫ = if δ (D(δ,ǫ + g + (δ D(ǫ,ǫ + g + (ǫ = 0, ad thrfor E G (ǫ = 0. Tak ow ay ǫ s.t. 0 < ǫ < δ. Sic D(δ,ǫ ad g + (δ ar both ogativ fctios, to hav E G (ǫ = if δ (D(δ,ǫ+g + (δ = 0 w d to fid δ s.t. both D(δ,ǫ ad g + (δ ar ll. To hav D(δ,ǫ = 0 w d to choos δ = ǫ; howvr, sic 0 < ǫ < r w hav g + (ǫ > 0 ad thrfor E G (ǫ > 0. I th xt sctio w prst rslts for two smbls flfillig th hypothss of Thorm 2, amly, th smbl of liar radom parity-chck cods ovr F q ad th smbl of fixd-rat biary Raptor cods with liar radom prcodrs 9]. For th first smbl th fctio E G (ǫ ca b obtaid aalytically ad coicids with Gallagr s radom codig bod ovr th q-ec. For th scod o, E G (ǫ shall b comptd mrically. Howvr, if oly th lowr bod o ǫ ML is of itrst, it may b comptd by simply solvig a 2 2 systm of qatios. IV. RESULTS FOR SPECIFIC ENSEMBLES A. Liar Radom Parity-Chck Cods Cosidr th smbl of liar radom parity-chck cods ovr F q idcd by a ( r radom parity-chck matrix whos tris ar idpdt ad idtically distribtd (i.i.d. radom variabls iformly distribtd i F q. For this smbl w hav th followig rslt. Thorm 3. For th smbl of liar radom parity-chck cods w hav δ = r ad thrfor ǫ ML = r. Morovr log ( ǫ q +ǫ rlogq 0 < ǫ < ǫ c E G (ǫ = D( r,ǫ ǫ c ǫ < r (0 0 ǫ r ǫ c = ( r/(+(r. Proof: Th xpctd wight mrator of th liar radom parity-chck smbl is A ω = ( ω (q ω q ( r ad th corrspodig wight spctral shap is G(ω = H b (ω+ωlog(q ( rlogq. Uiform covrgc of loga ω to G(ω may b provd i a vry simpl way, by obsrvig that sp ω loga ω G(ω = sp ( ω log H b (ω ω sp log(+ = log(+ ω w applid th lowr bod i (2. Sic log(+ 0 as, w cocld that loga ω G(ω. Th fctio h δ (ω dfid i (8 assms th form ( ω h δ (ω = δh b ωlog(+( rlogq. δ

5 Lt ˆω(δ = q q δ. It is asy to s that this fctio tds to ( rlogq wh ω 0 +, is mootoically dcrasig for ω (0,ˆω(δ, taks a miimm at ω = ˆω(δ, ad icrass mootoically for ω (ˆω(δ,δ]. Hc, w hav g(ω = if ω (0,δ] h δ (ω = h δ (ˆω(δ = ( r δlogq so that g + ( r δlogq if0<δ < r (δ= max0,g(δ = 0 if r δ <. Th paramtr δ is thrfor qal to r. Sic ǫ ML δ = r ad ǫ ML r, w obtai ǫ ML = r. Nxt, w dvlop E G (ǫ aalytically. Basd o th abov fidigs, w hav E G (ǫ = mi if D(δ,ǫ+( r δlogq], δ (0, r if D(δ,ǫ δ r,] that immdiatly yilds E G (ǫ = 0 for all ǫ r (it sffics to tak δ = ǫ, corrspodig to th third row of (0. For 0 < ǫ < r w d to aalyz th fctio f ǫ (δ = D(δ,ǫ+ qǫ +(q ǫ. g + (δ = D(δ,ǫ + ( r δlogq. Lt ˆδ(ǫ = Takig th drivativ with rspct to δ, it is immdiat to s that this fctio dcrass mootoically for δ < ˆδ(ǫ, taks a miimm at δ = ˆδ(ǫ, ad icrass mootoically for δ > ˆδ(ǫ. Hraftr w d to distigish th two cass ˆδ(ǫ < r ad ˆδ(ǫ r. It is immdiat to vrify that thy corrspod to0 < ǫ < ǫ c adǫ c ǫ < r, rspctivly, ǫ c = ( r/(+(r. Cas : 0 < ǫ < ǫ c. I this cas th fctio D(δ,ǫ+( r δlogq has a miimm at δ = ˆδ(ǫ. It taks th val D( r,ǫ at δ = r. Thrfor w obtai E G (ǫ = mid(ˆδ(ǫ,ǫ+( r ˆδ(ǫlogq,D( r,ǫ = D(ˆδ(ǫ,ǫ+( r ˆδ(ǫlogq ( ǫ = log +ǫ rlogq q th third xprssio follows from simpl algbraic maiplatio. This yilds th first row of (0. Cas 2: ǫ c < ǫ < r. I this cas th fctio D(δ,ǫ+ ( r δlogq is mootoically dcrasig for δ (0, r, so its ifimm is tak as δ ( r. W obtai E G (ǫ = mid( r,ǫ,d( r,ǫ = D( r,ǫ that corrspods to th scod row of (0. Rmark 3. Itrstigly, th xprssio (0 of E G (ǫ trs ot to coicid with that of Gallagr s radom codig rror xpot for th q-ec ]. B. Fixd-Rat Raptor Cods with Liar Radom Prcodrs I this sbsctio w cosidr biary fixd-rat Raptor cod smbls with liar radom prcodig. A vctor of r iformatio bits is first codd by a otr liar block cod pickd radomly i th smbl of biary liar radom parity-chck cods with dsig rat r o, providig a vctor of r/r o itrmdiat bits. Itrmdiat bits ar frthr codd by a ir fixd-rat Lby-trasform (LT cod of rat r i ad otpt dgr distribtio Ω(x = j Ω jx j, gratig codd bits. Th ovrall dsig rat is r = r o r i. Th wight spctral shap of this smbl was charactrizd i 9]. It is giv by G(ω = H b (ω r i ( r o ν ω (λ 0 ( ν ω (λ = H b (λ+ωlog(ρ(λ+( ωlog( ρ(λ ad λ 0 = λ 0 (ω = argmaxν ω (λ. (2 λ D I (2, D = 0, if Ω j = 0 for ay v j ad D = (0, othrwis. Morovr,ρ(λ = d 2 j= Ω j ( 2λ j ], big d th maximm LT otpt dgr. Agai from 9]: G(ω i ( is cotios. 2 lim ω 0 + G(ω < 0 iff (r i,r o P, P = (r i,r o (0,0 : r i ( r o 3 Th drivativ of G(ω is > max λ D r ih b (λ+log( ρ(λ]. (3 G (ω = log ω ω +log ρ(λ 0 ρ(λ 0. (4 4 G (ω > 0 for 0 < ω < 2 ad lim ω 0 + G (ω = +. Uiform covrgc of loga ω to G(ω ca b provd sig argmts from 9, Sc. III]. Morovr, th hypothss of Thorm 2 ar satisfid wh(r i,r o P, P is giv by (3. As opposd to liar radom parity-chck smbls, i this cas E G (ǫ shall b comptd mrically. Howvr, if oly th lowr bod δ o th ML dcodig thrshold ǫ ML is of itrst, it may b comptd fficitly, as show xt. Thorm 4. Cosidr a biary Raptor smbl with a liar radom prcodr ad lt (r i,r o P. Th ǫ ML δ δ is th smallst ˆδ s.t. (ˆδ,ˆλ 0 is a soltio of th 2 2 systm r i ( r o r i H b (ˆλ 0 ( ˆδlog( ρ(ˆλ 0 = 0 (5 r i log ˆλ 0 ˆλ 0 ˆδ ρ(ˆλ 0 ρ (ˆλ 0 log = 0. (6 Proof: If (r i,r o P th Thorm 2 applis. W hav ǫ ML δ, δ = spδ (0, r] : g + (δ > 0 ad δ > 0. Owig to cotiity of h δ (ω w ca writ g + (δ = max0,h δ (ˆω, ˆω = ˆω(δ = argmax ω (0,δ] h δ (ω. From (8 ad (4 w obtai dh δ (ω dω = log ω δ ω log ρ(λ 0 ρ(λ 0 (7 which rvals how dh δ (ω/dω + as ω δ. 5 Ths, th maximm caot b tak at ω = δ ad ˆω mst b a soltio of dh δ (ω/dω = 0. Dfiig ˆλ 0 = argmax λ D νˆω (λ ad 5 ρ(λ 0 (ω caot covrg to as ω δ for ay 0 < δ r.

6 rcallig (7, aftr som algbraic maiplatio this traslats to ˆω = δρ(ˆλ 0. (8 Th paramtr ˆλ 0 mst b a soltio of dνˆω (λ/dλ = 0. Dvlopig th drivativ w obtai r i log ˆλ 0 + ˆω ρ (ˆλ 0 ˆλ 0 ρ(ˆλ 0 log ( ˆω ρ (ˆλ 0 log = 0. ρ(ˆλ 0 (9 So far w hav show that g + (δ = max0,h δ (ˆω (ˆω,ˆλ 0 is a soltio of th systm of simltaos qatios (8 ad (9. Rcall ow from Thorm 2 that g + (δ > 0 for all 0 < δ < δ ad g + (δ = 0 for all δ δ. This cssarily implis h δ (ˆω > 0 for all 0 < δ < δ ad h δ (ˆω = 0, i.., δ is th smallst ˆδ sch that hˆδ(ˆω = 0, i.., aftr simpl maiplatio, th smallst ˆδ sch that ( r i ( r o r i H b (ˆλ 0 ( ˆδ ( ˆδlog ˆωˆδ = 0. Sbstittig (8 (with δ = ˆδ ito this lattr qatio yilds (5, whil sbstittig it ito (9 yilds (6. Exampl. Lt r o = 0.99, r i = 0.8, ad Ω(x b th LT otpt distribtio of 3GPP Raptor cods, i.., Ω(x = x x x x x x x 40. By dirct calclatio o ca vrify that (r i,r o P. Solvig (5 ad (6 w obtai th iq soltio (ˆδ,ˆλ 0 = ( , from which w cocld that ǫ ML δ = This bod is rlativly tightr that th o obtaid by mployig th gral bod i ], which rtrs ǫ ML V. CONCLUSIONS A lowr bod o th ML rror xpot of liar cod smbls ovr rasr chals has b drivd. Th lowr bod rqirs, dr mild coditios, jst th kowldg of th smbl wight spctral shap. Th applicatio to som liar block cod smbls has b dmostratd. For th spcific cas of fixd-rat Raptor cod smbls, th bod allows to compt a lowr bod o th ML dcodig thrshold, that is rmarkably tightr with rspct to th lowr bod obtaid with stablishd tchiqs. REFERENCES ] N. Shlma ad M. Fdr, Radom codig tchiqs for oradom cods, IEEE Tras. If. Thory, vol. 45, o. 6, pp , Sp ] G. Millr ad D. Brshti, Bods o th maximm-liklihood dcodig rror probability of low-dsity parity-chck cods, IEEE Tras. If. Thory, vol. 47, o. 7, pp , ] R. G. Gallagr, Low-Dsity Parity-Chck Cods. Cambridg, MA: M.I.T. Prss, ] C. Di, D. Proitti, T. Richardso, E. Tlatar, ad R. Urbak, Fiit lgth aalysis of low-dsity parity-chck cods o th biary rasr chal, IEEE Tras. If. Thory, vol. 48, pp , ] G. Liva, E. Paolii, ad M. Chiai, Bods o th rror probability of block cods ovr th q-ary rasr chal, IEEE Tras. Comm., vol. 6, o. 6, pp , J ] D. Brshti ad G. Millr, Asymptotic mratio mthods for aalyzig LDPC cods, IEEE Tras. If. Thory, vol. 50, o. 6, pp. 5 3, J ] R. G. Gallagr, Iformatio Thory ad Rliabl Commicatio. Nw York: Wily, ] M. Shokrollahi, Raptor cods, IEEE Tras. If. Thory, vol. 52, o. 6, pp , J ] F. Lázaro, E. Paolii, G. Liva, ad G. Bach, Distac spctrm of fixd-rat Raptor cods with liar radom prcodrs, IEEE J. Sl. Aras Comm., vol. 34, o. 2, pp , Fb ] W. Rdi, Pricipls of Mathmatical Aalysis, 3rd d. Nw York: McGraw-Hill, 976. ] S. Fashadi, S. O. Ghara, ad A. K. Khadai, Codig ovr a rasr chal with a larg alphabt siz, i Proc IEEE It. Symp. If. Thory, Toroto, Caada, Jl. 2008, pp

10. Joint Moments and Joint Characteristic Functions

10. Joint Moments and Joint Characteristic Functions 0 Joit Momts ad Joit Charactristic Fctios Followig sctio 6 i this sctio w shall itrodc varios paramtrs to compactly rprst th iformatio cotaid i th joit pdf of two rvs Giv two rvs ad ad a fctio g x y dfi

More information

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series Chatr Ifiit Sris Pag of Sctio F Itgral Tst Chatr : Ifiit Sris By th d of this sctio you will b abl to valuat imror itgrals tst a sris for covrgc by alyig th itgral tst aly th itgral tst to rov th -sris

More information

Fooling Newton s Method a) Find a formula for the Newton sequence, and verify that it converges to a nonzero of f. A Stirling-like Inequality

Fooling Newton s Method a) Find a formula for the Newton sequence, and verify that it converges to a nonzero of f. A Stirling-like Inequality Foolig Nwto s Mthod a Fid a formla for th Nwto sqc, ad vrify that it covrgs to a ozro of f. ( si si + cos 4 4 3 4 8 8 bt f. b Fid a formla for f ( ad dtrmi its bhavior as. f ( cos si + as A Stirlig-li

More information

1985 AP Calculus BC: Section I

1985 AP Calculus BC: Section I 985 AP Calculus BC: Sctio I 9 Miuts No Calculator Nots: () I this amiatio, l dots th atural logarithm of (that is, logarithm to th bas ). () Ulss othrwis spcifid, th domai of a fuctio f is assumd to b

More information

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z Sris Expasio of Rciprocal of Gamma Fuctio. Fuctios with Itgrs as Roots Fuctio f with gativ itgrs as roots ca b dscribd as follows. f() Howvr, this ifiit product divrgs. That is, such a fuctio caot xist

More information

DTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1

DTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1 DTFT Proprtis Exampl - Dtrmi th DTFT Y of y α µ, α < Lt x α µ, α < W ca thrfor writ y x x From Tabl 3., th DTFT of x is giv by ω X ω α ω Copyright, S. K. Mitra Copyright, S. K. Mitra DTFT Proprtis DTFT

More information

PURE MATHEMATICS A-LEVEL PAPER 1

PURE MATHEMATICS A-LEVEL PAPER 1 -AL P MATH PAPER HONG KONG EXAMINATIONS AUTHORITY HONG KONG ADVANCED LEVEL EXAMINATION PURE MATHEMATICS A-LEVEL PAPER 8 am am ( hours) This papr must b aswrd i Eglish This papr cosists of Sctio A ad Sctio

More information

Statistics 3858 : Likelihood Ratio for Exponential Distribution

Statistics 3858 : Likelihood Ratio for Exponential Distribution Statistics 3858 : Liklihood Ratio for Expotial Distributio I ths two xampl th rjctio rjctio rgio is of th form {x : 2 log (Λ(x)) > c} for a appropriat costat c. For a siz α tst, usig Thorm 9.5A w obtai

More information

H2 Mathematics Arithmetic & Geometric Series ( )

H2 Mathematics Arithmetic & Geometric Series ( ) H Mathmatics Arithmtic & Gomtric Sris (08 09) Basic Mastry Qustios Arithmtic Progrssio ad Sris. Th rth trm of a squc is 4r 7. (i) Stat th first four trms ad th 0th trm. (ii) Show that th squc is a arithmtic

More information

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges.

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges. Optio Chaptr Ercis. Covrgs to Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Divrgs 8 Divrgs Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Covrgs to Covrgs to 8 Proof Covrgs to π l 8 l a b Divrgt π Divrgt

More information

MONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx

MONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx MONTGOMERY COLLEGE Dpartmt of Mathmatics Rockvill Campus MATH 8 - REVIEW PROBLEMS. Stat whthr ach of th followig ca b itgratd by partial fractios (PF), itgratio by parts (PI), u-substitutio (U), or o of

More information

A Simple Proof that e is Irrational

A Simple Proof that e is Irrational Two of th most bautiful ad sigificat umbrs i mathmatics ar π ad. π (approximatly qual to 3.459) rprsts th ratio of th circumfrc of a circl to its diamtr. (approximatly qual to.788) is th bas of th atural

More information

Chapter Five. More Dimensions. is simply the set of all ordered n-tuples of real numbers x = ( x 1

Chapter Five. More Dimensions. is simply the set of all ordered n-tuples of real numbers x = ( x 1 Chatr Fiv Mor Dimsios 51 Th Sac R W ar ow rard to mov o to sacs of dimsio gratr tha thr Ths sacs ar a straightforward gralizatio of our Euclida sac of thr dimsios Lt b a ositiv itgr Th -dimsioal Euclida

More information

Time : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120

Time : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120 Tim : hr. Tst Papr 8 D 4//5 Bch - R Marks : SINGLE CORRECT CHOICE TYPE [4, ]. If th compl umbr z sisfis th coditio z 3, th th last valu of z is qual to : z (A) 5/3 (B) 8/3 (C) /3 (D) o of ths 5 4. Th itgral,

More information

Law of large numbers

Law of large numbers Law of larg umbrs Saya Mukhrj W rvisit th law of larg umbrs ad study i som dtail two typs of law of larg umbrs ( 0 = lim S ) p ε ε > 0, Wak law of larrg umbrs [ ] S = ω : lim = p, Strog law of larg umbrs

More information

On the approximation of the constant of Napier

On the approximation of the constant of Napier Stud. Uiv. Babş-Bolyai Math. 560, No., 609 64 O th approximatio of th costat of Napir Adri Vrscu Abstract. Startig from som oldr idas of [] ad [6], w show w facts cocrig th approximatio of th costat of

More information

Derivation of a Predictor of Combination #1 and the MSE for a Predictor of a Position in Two Stage Sampling with Response Error.

Derivation of a Predictor of Combination #1 and the MSE for a Predictor of a Position in Two Stage Sampling with Response Error. Drivatio of a Prdictor of Cobiatio # ad th SE for a Prdictor of a Positio i Two Stag Saplig with Rspos Error troductio Ed Stak W driv th prdictor ad its SE of a prdictor for a rado fuctio corrspodig to

More information

Digital Signal Processing, Fall 2006

Digital Signal Processing, Fall 2006 Digital Sigal Procssig, Fall 6 Lctur 9: Th Discrt Fourir Trasfor Zhg-Hua Ta Dpartt of Elctroic Systs Aalborg Uivrsity, Dar zt@o.aau.d Digital Sigal Procssig, I, Zhg-Hua Ta, 6 Cours at a glac MM Discrt-ti

More information

Probability & Statistics,

Probability & Statistics, Probability & Statistics, BITS Pilai K K Birla Goa Campus Dr. Jajati Kshari Sahoo Dpartmt of Mathmatics BITS Pilai, K K Birla Goa Campus Poisso Distributio Poisso Distributio: A radom variabl X is said

More information

STIRLING'S 1 FORMULA AND ITS APPLICATION

STIRLING'S 1 FORMULA AND ITS APPLICATION MAT-KOL (Baja Luka) XXIV ()(08) 57-64 http://wwwimviblorg/dmbl/dmblhtm DOI: 075/МК80057A ISSN 0354-6969 (o) ISSN 986-588 (o) STIRLING'S FORMULA AND ITS APPLICATION Šfkt Arslaagić Sarajvo B&H Abstract:

More information

Iterative Methods of Order Four for Solving Nonlinear Equations

Iterative Methods of Order Four for Solving Nonlinear Equations Itrativ Mods of Ordr Four for Solvig Noliar Equatios V.B. Kumar,Vatti, Shouri Domii ad Mouia,V Dpartmt of Egirig Mamatis, Formr Studt of Chmial Egirig Adhra Uivrsity Collg of Egirig A, Adhra Uivrsity Visakhapatam

More information

Thomas J. Osler. 1. INTRODUCTION. This paper gives another proof for the remarkable simple

Thomas J. Osler. 1. INTRODUCTION. This paper gives another proof for the remarkable simple 5/24/5 A PROOF OF THE CONTINUED FRACTION EXPANSION OF / Thomas J Oslr INTRODUCTION This ar givs aothr roof for th rmarkabl siml cotiud fractio = 3 5 / Hr is ay ositiv umbr W us th otatio x= [ a; a, a2,

More information

Restricted Factorial And A Remark On The Reduced Residue Classes

Restricted Factorial And A Remark On The Reduced Residue Classes Applid Mathmatics E-Nots, 162016, 244-250 c ISSN 1607-2510 Availabl fr at mirror sits of http://www.math.thu.du.tw/ am/ Rstrictd Factorial Ad A Rmark O Th Rducd Rsidu Classs Mhdi Hassai Rcivd 26 March

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

Solution to 1223 The Evil Warden.

Solution to 1223 The Evil Warden. Solutio to 1 Th Evil Ward. This is o of thos vry rar PoWs (I caot thik of aothr cas) that o o solvd. About 10 of you submittd th basic approach, which givs a probability of 47%. I was shockd wh I foud

More information

ln x = n e = 20 (nearest integer)

ln x = n e = 20 (nearest integer) H JC Prlim Solutios 6 a + b y a + b / / dy a b 3/ d dy a b at, d Giv quatio of ormal at is y dy ad y wh. d a b () (,) is o th curv a+ b () y.9958 Qustio Solvig () ad (), w hav a, b. Qustio d.77 d d d.77

More information

NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES

NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES Digst Joural of Naomatrials ad Biostructurs Vol 4, No, March 009, p 67-76 NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES A IRANMANESH a*, O KHORMALI b, I NAJAFI KHALILSARAEE c, B SOLEIMANI

More information

Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform

Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform. Discrete Fourier Transform Discrt Fourir Trasform Dfiitio - T simplst rlatio btw a lt- squc x dfid for ω ad its DTFT X ( ) is ω obtaid by uiformly sampli X ( ) o t ω-axis btw ω < at ω From t dfiitio of t DTFT w tus av X X( ω ) ω

More information

Linear Algebra Existence of the determinant. Expansion according to a row.

Linear Algebra Existence of the determinant. Expansion according to a row. Lir Algbr 2270 1 Existc of th dtrmit. Expsio ccordig to row. W dfi th dtrmit for 1 1 mtrics s dt([]) = (1) It is sy chck tht it stisfis D1)-D3). For y othr w dfi th dtrmit s follows. Assumig th dtrmit

More information

APPENDIX: STATISTICAL TOOLS

APPENDIX: STATISTICAL TOOLS I. Nots o radom samplig Why do you d to sampl radomly? APPENDI: STATISTICAL TOOLS I ordr to masur som valu o a populatio of orgaisms, you usually caot masur all orgaisms, so you sampl a subst of th populatio.

More information

Review Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2

Review Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2 MATHEMATIS --RE Itgral alculus Marti Huard Witr 9 Rviw Erciss. Evaluat usig th dfiitio of th dfiit itgral as a Rima Sum. Dos th aswr rprst a ara? a ( d b ( d c ( ( d d ( d. Fid f ( usig th Fudamtal Thorm

More information

Chapter 10. The singular integral Introducing S(n) and J(n)

Chapter 10. The singular integral Introducing S(n) and J(n) Chaptr Th singular intgral Our aim in this chaptr is to rplac th functions S (n) and J (n) by mor convnint xprssions; ths will b calld th singular sris S(n) and th singular intgral J(n). This will b don

More information

Triple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling

Triple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling Tripl Play: From D Morga to Stirlig To Eulr to Maclauri to Stirlig Augustus D Morga (186-1871) was a sigificat Victoria Mathmaticia who mad cotributios to Mathmatics History, Mathmatical Rcratios, Mathmatical

More information

Journal of Modern Applied Statistical Methods

Journal of Modern Applied Statistical Methods Joural of Modr Applid Statistical Mthods Volum Issu Articl 6 --03 O Som Proprtis of a Htrogous Trasfr Fuctio Ivolvig Symmtric Saturatd Liar (SATLINS) with Hyprbolic Tagt (TANH) Trasfr Fuctios Christophr

More information

NET/JRF, GATE, IIT JAM, JEST, TIFR

NET/JRF, GATE, IIT JAM, JEST, TIFR Istitut for NET/JRF, GATE, IIT JAM, JEST, TIFR ad GRE i PHYSICAL SCIENCES Mathmatical Physics JEST-6 Q. Giv th coditio φ, th solutio of th quatio ψ φ φ is giv by k. kφ kφ lφ kφ lφ (a) ψ (b) ψ kφ (c) ψ

More information

The Interplay between l-max, l-min, p-max and p-min Stable Distributions

The Interplay between l-max, l-min, p-max and p-min Stable Distributions DOI: 0.545/mjis.05.4006 Th Itrplay btw lma lmi pma ad pmi Stabl Distributios S Ravi ad TS Mavitha Dpartmt of Studis i Statistics Uivrsity of Mysor Maasagagotri Mysuru 570006 Idia. Email:ravi@statistics.uimysor.ac.i

More information

BOUNDS FOR THE COMPONENTWISE DISTANCE TO THE NEAREST SINGULAR MATRIX

BOUNDS FOR THE COMPONENTWISE DISTANCE TO THE NEAREST SINGULAR MATRIX SIAM J. Matrix Aal. Appl. (SIMAX), 8():83 03, 997 BOUNDS FOR THE COMPONENTWISE DISTANCE TO THE NEAREST SINGULAR MATRIX S. M. RUMP Abstract. Th ormwis distac of a matrix A to th arst sigular matrix is wll

More information

Chapter (8) Estimation and Confedence Intervals Examples

Chapter (8) Estimation and Confedence Intervals Examples Chaptr (8) Estimatio ad Cofdc Itrvals Exampls Typs of stimatio: i. Poit stimatio: Exampl (1): Cosidr th sampl obsrvatios, 17,3,5,1,18,6,16,10 8 X i i1 17 3 5 118 6 16 10 116 X 14.5 8 8 8 14.5 is a poit

More information

Discrete Fourier Transform (DFT)

Discrete Fourier Transform (DFT) Discrt Fourir Trasorm DFT Major: All Egirig Majors Authors: Duc guy http://umricalmthods.g.us.du umrical Mthods or STEM udrgraduats 8/3/29 http://umricalmthods.g.us.du Discrt Fourir Trasorm Rcalld th xpotial

More information

Calculus & analytic geometry

Calculus & analytic geometry Calculus & aalytic gomtry B Sc MATHEMATICS Admissio owards IV SEMESTER CORE COURSE UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION CALICUT UNIVERSITYPO, MALAPPURAM, KERALA, INDIA 67 65 5 School of Distac

More information

Folding of Hyperbolic Manifolds

Folding of Hyperbolic Manifolds It. J. Cotmp. Math. Scics, Vol. 7, 0, o. 6, 79-799 Foldig of Hyprbolic Maifolds H. I. Attiya Basic Scic Dpartmt, Collg of Idustrial Educatio BANE - SUEF Uivrsity, Egypt hala_attiya005@yahoo.com Abstract

More information

Limiting value of higher Mahler measure

Limiting value of higher Mahler measure Limiting valu of highr Mahlr masur Arunabha Biswas a, Chris Monico a, a Dpartmnt of Mathmatics & Statistics, Txas Tch Univrsity, Lubbock, TX 7949, USA Abstract W considr th k-highr Mahlr masur m k P )

More information

On a problem of J. de Graaf connected with algebras of unbounded operators de Bruijn, N.G.

On a problem of J. de Graaf connected with algebras of unbounded operators de Bruijn, N.G. O a problm of J. d Graaf coctd with algbras of uboudd oprators d Bruij, N.G. Publishd: 01/01/1984 Documt Vrsio Publishr s PDF, also kow as Vrsio of Rcord (icluds fial pag, issu ad volum umbrs) Plas chck

More information

Technical Support Document Bias of the Minimum Statistic

Technical Support Document Bias of the Minimum Statistic Tchical Support Documt Bias o th Miimum Stattic Itroductio Th papr pla how to driv th bias o th miimum stattic i a radom sampl o siz rom dtributios with a shit paramtr (also kow as thrshold paramtr. Ths

More information

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.

More information

Cramér-Rao Inequality: Let f(x; θ) be a probability density function with continuous parameter

Cramér-Rao Inequality: Let f(x; θ) be a probability density function with continuous parameter WHEN THE CRAMÉR-RAO INEQUALITY PROVIDES NO INFORMATION STEVEN J. MILLER Abstract. W invstigat a on-paramtr family of probability dnsitis (rlatd to th Parto distribution, which dscribs many natural phnomna)

More information

On the irreducibility of some polynomials in two variables

On the irreducibility of some polynomials in two variables ACTA ARITHMETICA LXXXII.3 (1997) On th irrducibility of som polynomials in two variabls by B. Brindza and Á. Pintér (Dbrcn) To th mmory of Paul Erdős Lt f(x) and g(y ) b polynomials with intgral cofficints

More information

An Introduction to Asymptotic Expansions

An Introduction to Asymptotic Expansions A Itroductio to Asmptotic Expasios R. Shaar Subramaia Asmptotic xpasios ar usd i aalsis to dscrib th bhavior of a fuctio i a limitig situatio. Wh a fuctio ( x, dpds o a small paramtr, ad th solutio of

More information

CDS 101: Lecture 5.1 Reachability and State Space Feedback

CDS 101: Lecture 5.1 Reachability and State Space Feedback CDS, Lctur 5. CDS : Lctur 5. Rachability ad Stat Spac Fdback Richard M. Murray ad Hido Mabuchi 5 Octobr 4 Goals: Di rachability o a cotrol systm Giv tsts or rachability o liar systms ad apply to ampls

More information

Hadamard Exponential Hankel Matrix, Its Eigenvalues and Some Norms

Hadamard Exponential Hankel Matrix, Its Eigenvalues and Some Norms Math Sci Ltt Vol No 8-87 (0) adamard Exotial al Matrix, Its Eigvalus ad Som Norms İ ad M bula Mathmatical Scics Lttrs Itratioal Joural @ 0 NSP Natural Scics Publishig Cor Dartmt of Mathmatics, aculty of

More information

UNIVERSALITY LIMITS INVOLVING ORTHOGONAL POLYNOMIALS ON AN ARC OF THE UNIT CIRCLE

UNIVERSALITY LIMITS INVOLVING ORTHOGONAL POLYNOMIALS ON AN ARC OF THE UNIT CIRCLE UNIVERSALITY LIMITS INVOLVING ORTHOGONAL POLYNOMIALS ON AN ARC OF THE UNIT CIRCLE DORON S. LUBINSKY AND VY NGUYEN A. W stablish uivrsality limits for masurs o a subarc of th uit circl. Assum that µ is

More information

Discrete Fourier Transform. Nuno Vasconcelos UCSD

Discrete Fourier Transform. Nuno Vasconcelos UCSD Discrt Fourir Trasform uo Vascoclos UCSD Liar Shift Ivariat (LSI) systms o of th most importat cocpts i liar systms thory is that of a LSI systm Dfiitio: a systm T that maps [ ito y[ is LSI if ad oly if

More information

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013

Introduction to Arithmetic Geometry Fall 2013 Lecture #20 11/14/2013 18.782 Introduction to Arithmtic Gomtry Fall 2013 Lctur #20 11/14/2013 20.1 Dgr thorm for morphisms of curvs Lt us rstat th thorm givn at th nd of th last lctur, which w will now prov. Thorm 20.1. Lt φ:

More information

Predator Population Dynamics Involving Exponential Integral Function When Prey Follows Gompertz Model

Predator Population Dynamics Involving Exponential Integral Function When Prey Follows Gompertz Model Op Joral of Modllig ad Simlatio, 25, 3, 7-8 Pblishd Oli Jly 25 i SciRs. http://www.scirp.org/joral/ojmsi http://dx.doi.org/.4236/ojmsi.25.338 Prdator Poplatio Dyamics Ivolvig Expotial Itgral Fctio Wh Pry

More information

Minimax Rényi Redundancy

Minimax Rényi Redundancy 07 IEEE Itratioal Symposium o Iformatio Thory ISIT Miimax Réyi Rdudacy Smih Yagli Pricto Uivrsity Yücl Altuğ Natra, Ic Srgio Vrdú Pricto Uivrsity Abstract Th rdudacy for uivrsal losslss comprssio i Campbll

More information

Minimax Rényi Redundancy

Minimax Rényi Redundancy Miimax Réyi Rdudacy Smih Yagli Pricto Uivrsity Yücl Altuğ Natra, Ic Srgio Vrdú Pricto Uivrsity Abstract Th rdudacy for uivrsal losslss comprssio i Campbll s sttig is charactrizd as a miimax Réyi divrgc,

More information

Session : Plasmas in Equilibrium

Session : Plasmas in Equilibrium Sssio : Plasmas i Equilibrium Ioizatio ad Coductio i a High-prssur Plasma A ormal gas at T < 3000 K is a good lctrical isulator, bcaus thr ar almost o fr lctros i it. For prssurs > 0.1 atm, collisio amog

More information

CDS 101: Lecture 5.1 Reachability and State Space Feedback

CDS 101: Lecture 5.1 Reachability and State Space Feedback CDS, Lctur 5. CDS : Lctur 5. Rachability ad Stat Spac Fdback Richard M. Murray 7 Octobr 3 Goals: Di rachability o a cotrol systm Giv tsts or rachability o liar systms ad apply to ampls Dscrib th dsig o

More information

International Journal of Advanced and Applied Sciences

International Journal of Advanced and Applied Sciences Itratioal Joural of Advacd ad Applid Scics x(x) xxxx Pags: xx xx Cotts lists availabl at Scic Gat Itratioal Joural of Advacd ad Applid Scics Joural hompag: http://wwwscic gatcom/ijaashtml Symmtric Fuctios

More information

FORBIDDING RAINBOW-COLORED STARS

FORBIDDING RAINBOW-COLORED STARS FORBIDDING RAINBOW-COLORED STARS CARLOS HOPPEN, HANNO LEFMANN, KNUT ODERMANN, AND JULIANA SANCHES Abstract. W cosidr a xtrmal problm motivatd by a papr of Balogh [J. Balogh, A rmark o th umbr of dg colorigs

More information

Chapter Taylor Theorem Revisited

Chapter Taylor Theorem Revisited Captr 0.07 Taylor Torm Rvisitd Atr radig tis captr, you sould b abl to. udrstad t basics o Taylor s torm,. writ trascdtal ad trigoomtric uctios as Taylor s polyomial,. us Taylor s torm to id t valus o

More information

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES. 1. Statement of results

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES. 1. Statement of results BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES DONALD M. DAVIS Abstract. If p is a prim and n a positiv intgr, lt ν p (n dnot th xponnt of p in n, and u p (n n/p νp(n th unit part of n. If α

More information

DFT: Discrete Fourier Transform

DFT: Discrete Fourier Transform : Discrt Fourir Trasform Cogruc (Itgr modulo m) I this sctio, all lttrs stad for itgrs. gcd m, = th gratst commo divisor of ad m Lt d = gcd(,m) All th liar combiatios r s m of ad m ar multils of d. a b

More information

A Note on Quantile Coupling Inequalities and Their Applications

A Note on Quantile Coupling Inequalities and Their Applications A Not o Quatil Couplig Iqualitis ad Thir Applicatios Harriso H. Zhou Dpartmt of Statistics, Yal Uivrsity, Nw Hav, CT 06520, USA. E-mail:huibi.zhou@yal.du Ju 2, 2006 Abstract A rlatioship btw th larg dviatio

More information

Deift/Zhou Steepest descent, Part I

Deift/Zhou Steepest descent, Part I Lctur 9 Dift/Zhou Stpst dscnt, Part I W now focus on th cas of orthogonal polynomials for th wight w(x) = NV (x), V (x) = t x2 2 + x4 4. Sinc th wight dpnds on th paramtr N N w will writ π n,n, a n,n,

More information

Further Results on Pair Sum Graphs

Further Results on Pair Sum Graphs Applid Mathmatis, 0,, 67-75 http://dx.doi.org/0.46/am.0.04 Publishd Oli Marh 0 (http://www.sirp.org/joural/am) Furthr Rsults o Pair Sum Graphs Raja Poraj, Jyaraj Vijaya Xavir Parthipa, Rukhmoi Kala Dpartmt

More information

Chapter 4 - The Fourier Series

Chapter 4 - The Fourier Series M. J. Robrts - 8/8/4 Chaptr 4 - Th Fourir Sris Slctd Solutios (I this solutio maual, th symbol,, is usd for priodic covolutio bcaus th prfrrd symbol which appars i th txt is ot i th fot slctio of th word

More information

Lectures 9 IIR Systems: First Order System

Lectures 9 IIR Systems: First Order System EE3054 Sigals ad Systms Lcturs 9 IIR Systms: First Ordr Systm Yao Wag Polytchic Uivrsity Som slids icludd ar xtractd from lctur prstatios prpard by McCllla ad Schafr Lics Ifo for SPFirst Slids This work

More information

LINEAR DELAY DIFFERENTIAL EQUATION WITH A POSITIVE AND A NEGATIVE TERM

LINEAR DELAY DIFFERENTIAL EQUATION WITH A POSITIVE AND A NEGATIVE TERM Elctronic Journal of Diffrntial Equations, Vol. 2003(2003), No. 92, pp. 1 6. ISSN: 1072-6691. URL: http://jd.math.swt.du or http://jd.math.unt.du ftp jd.math.swt.du (login: ftp) LINEAR DELAY DIFFERENTIAL

More information

Exercise 1. Sketch the graph of the following function. (x 2

Exercise 1. Sketch the graph of the following function. (x 2 Writtn tst: Fbruary 9th, 06 Exrcis. Sktch th graph of th following function fx = x + x, spcifying: domain, possibl asymptots, monotonicity, continuity, local and global maxima or minima, and non-drivability

More information

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES

BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES BINOMIAL COEFFICIENTS INVOLVING INFINITE POWERS OF PRIMES DONALD M. DAVIS Abstract. If p is a prim (implicit in notation and n a positiv intgr, lt ν(n dnot th xponnt of p in n, and U(n n/p ν(n, th unit

More information

Supplementary Materials

Supplementary 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 information

New Sixteenth-Order Derivative-Free Methods for Solving Nonlinear Equations

New Sixteenth-Order Derivative-Free Methods for Solving Nonlinear Equations Amrica Joural o Computatioal ad Applid Mathmatics 0 (: -8 DOI: 0.59/j.ajcam.000.08 Nw Sixtth-Ordr Drivativ-Fr Mthods or Solvig Noliar Equatios R. Thukral Padé Rsarch Ctr 9 Daswood Hill Lds Wst Yorkshir

More information

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.

22/ 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 information

ONLINE SUPPLEMENT Optimal Markdown Pricing and Inventory Allocation for Retail Chains with Inventory Dependent Demand

ONLINE SUPPLEMENT Optimal Markdown Pricing and Inventory Allocation for Retail Chains with Inventory Dependent Demand Submittd to Maufacturig & Srvic Opratios Maagmt mauscript MSOM 5-4R2 ONLINE SUPPLEMENT Optimal Markdow Pricig ad Ivtory Allocatio for Rtail Chais with Ivtory Dpdt Dmad Stph A Smith Dpartmt of Opratios

More information

ECE594I Notes set 6: Thermal Noise

ECE594I Notes set 6: Thermal Noise C594I ots, M. odwll, copyrightd C594I Nots st 6: Thrmal Nois Mark odwll Uivrsity of Califoria, ata Barbara rodwll@c.ucsb.du 805-893-344, 805-893-36 fax frcs ad Citatios: C594I ots, M. odwll, copyrightd

More information

Ordinary Differential Equations

Ordinary Differential Equations Ordiary Diffrtial Equatio Aftr radig thi chaptr, you hould b abl to:. dfi a ordiary diffrtial quatio,. diffrtiat btw a ordiary ad partial diffrtial quatio, ad. Solv liar ordiary diffrtial quatio with fid

More information

Recall that by Theorems 10.3 and 10.4 together provide us the estimate o(n2 ), S(q) q 9, q=1

Recall that by Theorems 10.3 and 10.4 together provide us the estimate o(n2 ), S(q) q 9, q=1 Chaptr 11 Th singular sris Rcall that by Thorms 10 and 104 togthr provid us th stimat 9 4 n 2 111 Rn = SnΓ 2 + on2, whr th singular sris Sn was dfind in Chaptr 10 as Sn = q=1 Sq q 9, with Sq = 1 a q gcda,q=1

More information

HOMOGENIZATION OF DIFFUSION PROCESSES ON SCALE-FREE METRIC NETWORKS

HOMOGENIZATION OF DIFFUSION PROCESSES ON SCALE-FREE METRIC NETWORKS Elctroic Joural of Diffrtial Equatios, Vol. 26 (26), No. 282, pp. 24. ISSN: 72-669. URL: http://jd.math.txstat.du or http://jd.math.ut.du HOMOGENIZATION OF DIFFUSION PROCESSES ON SCALE-FREE METRIC NETWORKS

More information

Section 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.

Section 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 information

Basic Polyhedral theory

Basic Polyhedral theory Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist

More information

Hardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R.

Hardy-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 information

cycle that does not cross any edges (including its own), then it has at least

cycle 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 information

Problem Set 6 Solutions

Problem Set 6 Solutions 6.04/18.06J Mathmatics for Computr Scinc March 15, 005 Srini Dvadas and Eric Lhman Problm St 6 Solutions Du: Monday, March 8 at 9 PM in Room 3-044 Problm 1. Sammy th Shark is a financial srvic providr

More information

Asymptotic Behaviors for Critical Branching Processes with Immigration

Asymptotic Behaviors for Critical Branching Processes with Immigration Acta Mathmatica Siica, Eglih Sri Apr., 9, Vol. 35, No. 4, pp. 537 549 Publihd oli: March 5, 9 http://doi.org/.7/4-9-744-6 http://www.actamath.com Acta Mathmatica Siica, Eglih Sri Sprigr-Vrlag GmbH Grmay

More information

Gaps in samples of geometric random variables

Gaps in samples of geometric random variables Discrt Mathmatics 37 7 871 89 Not Gaps i sampls of gomtric radom variabls William M.Y. Goh a, Pawl Hitczko b,1 a Dpartmt of Mathmatics, Drxl Uivrsity, Philadlphia, PA 1914, USA b Dpartmts of Mathmatics

More information

1973 AP Calculus BC: Section I

1973 AP Calculus BC: Section I 97 AP Calculus BC: Scio I 9 Mius No Calculaor No: I his amiaio, l dos h aural logarihm of (ha is, logarihm o h bas ).. If f ( ) =, h f ( ) = ( ). ( ) + d = 7 6. If f( ) = +, h h s of valus for which f

More information

15/03/1439. Lectures on Signals & systems Engineering

15/03/1439. Lectures on Signals & systems Engineering Lcturs o Sigals & syms Egirig Dsigd ad Prd by Dr. Ayma Elshawy Elsfy Dpt. of Syms & Computr Eg. Al-Azhar Uivrsity Email : aymalshawy@yahoo.com A sigal ca b rprd as a liar combiatio of basic sigals. Th

More information

A GENERALIZED RAMANUJAN-NAGELL EQUATION RELATED TO CERTAIN STRONGLY REGULAR GRAPHS

A GENERALIZED RAMANUJAN-NAGELL EQUATION RELATED TO CERTAIN STRONGLY REGULAR GRAPHS #A35 INTEGERS 4 (204) A GENERALIZED RAMANUJAN-NAGELL EQUATION RELATED TO CERTAIN STRONGLY REGULAR GRAPHS B d Wgr Faculty of Mathmatics ad Computr Scic, Eidhov Uivrsity of Tchology, Eidhov, Th Nthrlads

More information

ω (argument or phase)

ω (argument or phase) Imagiary uit: i ( i Complx umbr: z x+ i y Cartsia coordiats: x (ral part y (imagiary part Complx cougat: z x i y Absolut valu: r z x + y Polar coordiats: r (absolut valu or modulus ω (argumt or phas x

More information

[ ] Review. For a discrete-time periodic signal xn with period N, the Fourier series representation is

[ ] Review. For a discrete-time periodic signal xn with period N, the Fourier series representation is Discrt-tim ourir Trsform Rviw or discrt-tim priodic sigl x with priod, th ourir sris rprsttio is x + < > < > x, Rviw or discrt-tim LTI systm with priodic iput sigl, y H ( ) < > < > x H r rfrrd to s th

More information

SECTION where P (cos θ, sin θ) and Q(cos θ, sin θ) are polynomials in cos θ and sin θ, provided Q is never equal to zero.

SECTION where P (cos θ, sin θ) and Q(cos θ, sin θ) are polynomials in cos θ and sin θ, provided Q is never equal to zero. SETION 6. 57 6. Evaluation of Dfinit Intgrals Exampl 6.6 W hav usd dfinit intgrals to valuat contour intgrals. It may com as a surpris to larn that contour intgrals and rsidus can b usd to valuat crtain

More information

Chapter 11.00C Physical Problem for Fast Fourier Transform Civil Engineering

Chapter 11.00C Physical Problem for Fast Fourier Transform Civil Engineering haptr. Physical Problm for Fast Fourir Trasform ivil Egirig Itroductio I this chaptr, applicatios of FFT algorithms [-5] for solvig ral-lif problms such as computig th dyamical (displacmt rspos [6-7] of

More information

Ordinary Differential Equations

Ordinary Differential Equations Basi Nomlatur MAE 0 all 005 Egirig Aalsis Ltur Nots o: Ordiar Diffrtial Equatios Author: Profssor Albrt Y. Tog Tpist: Sakurako Takahashi Cosidr a gral O. D. E. with t as th idpdt variabl, ad th dpdt variabl.

More information

Blackbody Radiation. All bodies at a temperature T emit and absorb thermal electromagnetic radiation. How is blackbody radiation absorbed and emitted?

Blackbody Radiation. All bodies at a temperature T emit and absorb thermal electromagnetic radiation. How is blackbody radiation absorbed and emitted? All bodis at a tmpratur T mit ad absorb thrmal lctromagtic radiatio Blackbody radiatio I thrmal quilibrium, th powr mittd quals th powr absorbd How is blackbody radiatio absorbd ad mittd? 1 2 A blackbody

More information

6. Comparison of NLMS-OCF with Existing Algorithms

6. Comparison of NLMS-OCF with Existing Algorithms 6. Compariso of NLMS-OCF with Eistig Algorithms I Chaptrs 5 w drivd th NLMS-OCF algorithm, aalyzd th covrgc ad trackig bhavior of NLMS-OCF, ad dvlopd a fast vrsio of th NLMS-OCF algorithm. W also mtiod

More information

Normal Form for Systems with Linear Part N 3(n)

Normal Form for Systems with Linear Part N 3(n) Applid Mathmatics 64-647 http://dxdoiorg/46/am7 Publishd Oli ovmbr (http://wwwscirporg/joural/am) ormal Form or Systms with Liar Part () Grac Gachigua * David Maloza Johaa Sigy Dpartmt o Mathmatics Collg

More information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Procssing Prof. Mark Fowlr Dtails of th ot St #19 Rading Assignmnt: Sct. 7.1.2, 7.1.3, & 7.2 of Proakis & Manolakis Dfinition of th So Givn signal data points x[n] for n = 0,, -1

More information

DISTRIBUTION OF DIFFERENCE BETWEEN INVERSES OF CONSECUTIVE INTEGERS MODULO P

DISTRIBUTION OF DIFFERENCE BETWEEN INVERSES OF CONSECUTIVE INTEGERS MODULO P DISTRIBUTION OF DIFFERENCE BETWEEN INVERSES OF CONSECUTIVE INTEGERS MODULO P Tsz Ho Chan Dartmnt of Mathmatics, Cas Wstrn Rsrv Univrsity, Clvland, OH 4406, USA txc50@cwru.du Rcivd: /9/03, Rvisd: /9/04,

More information