1 Ovrviw In this ppr w onsir two istint, ut intrtwin, thms. Th rst is nighorhoo xpnsion grmmrs whih onstitut onsirl hng rom mor tritionl phrs strutur
|
|
- Eunice Briggs
- 6 years ago
- Views:
Transcription
1 Nighorhoo Expnsion Grmmrs John L. Pltz Dpt. o Computr Sin Univrsity o Virgini Chrlottsvill, VA Mrh 1, 1999 Dpt. o Computr Sin Thnil Rport, TR Astrt Phrs strutur grmmrs, in whih non-trminl symols on th lt si o proution n rwrittn y th string on th right si, togthr with thir Chomsky hirrh lssition, r milir to omputr sintists. But, ths grmmrs r most tiv only to gnrt, n prs, strings. In this rport, w introu nw kin o grmmr in whih th right si o th proution is simply ppn to th intrmit strutur in suh wy tht th lt si oms its "nighorhoo" in th nw strutur. This prmits th grmmtil nition o mny irnt kins o "n-imnsionl" isrt struturs. Svrl xmpls r givn. Morovr, ths grmmrs yil orml thory groun in ntimtroi losur sps. For xmpl, w show tht rstrit nighorhoo xpnsion grmmrs ptur th ssn o nit stt n ontxt r phrs strutur grmmrs. Rsrh support in prt y DOE grnt DE-FG05-95ER
2 1 Ovrviw In this ppr w onsir two istint, ut intrtwin, thms. Th rst is nighorhoo xpnsion grmmrs whih onstitut onsirl hng rom mor tritionl phrs strutur grmmrs in tht intrmit symols r not rwrittn. Inst, ompltly nw pis r simply to th isrt systm ing gnrt. Suh isrt systms w mol y grphs, G k, in this ppr. Th son thm is tht o losur sps n thir ssoit lttis [19]. I th lss o isrt systm ing gnrt is losur sp, w will l to n \goo" grmmrs s thos whih homomorphilly prsrv th inu ltti strutur o th systm with h stp o th gnrtion. Finlly, w will l to vlop hirrhy o grmmrs tht inlus th Chomsky hirrhy, n y whih w n qulittivly msur th omplxity o isrt systms. 1.1 Nighorhoo Expnsion Grmmrs In phrs strutur grmmr, sustring, or mor usully singl non-trminl symol A, is rwrittn y som othr longr string. Whn phrs strutur rwriting is ppli to mor omplx, non-linr systms, sugrph H, or singl no, o G is rwrittn s lrgr sugrph H 0 whih must thn m into G 0 = G? H. Dsriing th ming pross is not lwys sy [20]. Nighorhoo xpnsion grmmrs o not rwrit ny portion o th xisting intrmit systm. Inst, nw portions r simply to th xisting systm G. Som sugrph H o G is signt to om th nighorhoo o this nw strutur. In proution orm, th right si H 0 nots th nw strutur, otn singl point, n th lt si nots th sugrph H o G whih will th nighorhoo o H 0 in G 0. This pross is mor sily visuliz y smll xmpl. A grmmr G horl to gnrt horl grphs n sri y singl proution: K n := p tht is, ny liqu o orr k in G n srv s th nighorhoo o nw point p. Evry point in K n will jnt to p in G 0. 1 Figur 1 illustrts rprsnttiv gnrtion squn. Eh xpn nighorhoo (in this s liqu) hs n m ol; n th xpnsion point irl. Th sh gs init thos whih n th liqu s th nighorhoo o th xpnsion point p. It is not hr to s tht ny grph gnrt in this shion must horl. Bus xtrm points r simpliil (nighorhoo is 1 I w rwrit th proution so tht th right si is oth th nighorhoo n th nwly rt point p within it, th proution oms K n := K n+1 tht is, to ny liqu on n lmnts n nw lmnt to rt liqu on n + 1 lmnts. 2
3 Figur 1: A squn o nighorhoo xpnsions gnrting horl grphs liqu), n us vry horl grph must hv t lst two xtrm points [8, 6], vry horl grph n so gnrt. I th lt si o th xpnsion rul o G horl is rstrit to only K 1, i.. singl point, thn G gnrts ll, n only, unirt trs. Ths two grmmrs lrly illustrt th ssntil tr-lik strutur o horl grphs. This lttr rsult is wll known, sin vry horl grph is th intrstion grph o th sutrs o tr [7, 14]. 1.2 Nighorhoos W sy is omplt nighorhoo oprtor i or ll X U, X X:, X Y implis X: Y:, (X [ Y ): = X: [ Y:, (X \ Y ): = X: \ Y:. (possily unnssry) Clrly, nighorhoo oprtor xpns th sust. W r otn mor intrst in th lt nighorhoo,, n X: = X:? X; us it rprsnts this inrmntl ition. Lt us onsir rprsnttiv nighorhoo oprtor. I G is grph, w n n lt nighorhoo y X: j = y 62 Xj9x 2 X jnt to y g. Rily, this is th nighorhoo onpt w us in G horl. It pprs in mny grph-thorti lgorithms. 3
4 2 Othr Expnsion Grmmrs W ll G lok grph i vry mximl 2-onnt sugrph is liqu K n [10]. A simpl grmmr G lok onsisting o only th singl rul p := K n n 1 will gnrt th lok grphs. Figur 2 illustrts on suh rivtion squn in G lok. Hr, h p to xpn is moln n its onntion to th nw K n init Figur 2: A squn o nighorhoo xpnsions gnrting lok grphs y sh lins. Rily, th nighorhoo o h nw xpnsion K n is th singl point. Contrsting G horl with G lok is invitl. Th liqu K n on th lt si o th proution in G horl is just xhng with th nw point p on th right si. Both gnrt tr-lik isrt systms. A grmmr to gnrt tringulr plnr ntworks is mor omplx n introus th us o lll gs. Th us o g lls to ontrol grmmrs is not nw,.. [3, 13]. := * := u u u := 4
5 Th ll inits tht th g is xtrior. Whn th rst proution is ppli nw point is rt in th xtrior in suh wy tht th g is its nighorhoo. Sin, th originl g is no longr xtrior, its ll is rmov n th two onnting gs lll s \xtrior". A nw point my insrt into th intrior o ny tringl, s in th son proution. But, insrtion o two suh points stroys plnrity (xpt in th spil s whn two, or mor, gs r xtrior gs.) Consquntly, h o th thr gs onstituting th nighorhoo o th nw point r lll with u (or us). Ths u lls r nvr rmov. Th son proution n ppli only i two o th gs r unll ( nots on't r onition). Th thir proution is it nomolous; it mois nighorhoo inst o ing point. Only th init g is. 2 Th strt strutur or plnr tringultions onsists o singl tringl, ll o whos gs r xtrior. Figur 3 illustrts on suh rivtion squn in G tringl. u u u u u u Figur 3: A squn o nighorhoo xpnsions gnrting plnr tringulr gris I w onsir isrt prtilly orr systms, thr r two istint nighorhoo onpts: X: < = z 62 Xjz < x n z < y x implis y 2 Xg n X: > = z 62 Xjx < z n x y < z implis y 2 Xg. Th nighorhoo oprtor < is ll th ovring oprtor whn th prtil orr is rgr s ltti. 2 This proution ws to hnl th spil ss ssoit with rul 2. It is not iult to writ two spil nighorhoo xpnsion ruls to o this; ut th rul, s givn, is so usul whn xpning tringultion on th \outsi", n oppos to suiviing it on th \insi", tht it ws rtin in its urrnt orm. 5
6 Consquntly, w hv t lst thr irnt grmmrs to gnrt prtil orrs, pning on whthr on uss <, >, or <> (whih omins thm oth) s th nighorhoo onpt. For xmpl, th grmmr G right tr with th singl proution p := q lrly gnrts th lss o root trs whos orinttion pns on whthr p is to q: < or q: >. I w lt th nighorhoo not y th lt hn o this proution n ritrry sugrph N o G, s in th proution N := q whr q: < is still th nighorhoo oprtor, w gt G lt root gnrting ll lt root yli grphs. Figur 4 illustrts on suh gnrtion squn. I inst o th singlton Figur 4: A squn o nighorhoo xpnsions gnrting lt root yli grphs point o Figur 4, w llow n ritrry ntihin, A n, to th strt strutur, thn rily G lt root oms G yli whih gnrts ll yli grphs or prtil orrs. I inst, w us th nighorhoo oprtor >, th sm proution yils ll right root yli grphs, whih with th ntihin strt strutur gnrts yli grphs s or. Som intrsting sumilis o th yli grphs n vlop i on uss th two-si nighorhoo oprtor, X: <> = X: < [ X: >. Th mjor prolm with ths two-si nighorhoos is tht or n ritrry sust o H o G, it my not vint whih lmnts long to whih si. Suh grmmr w woul ll miguous. An unmiguous grmmr or two trminl, prlll sris ntworks n spi y rquiring th lt hn nighorhoo to singl g. For xmpl, G ttspn hs th two rwrit ruls, p 1 p 2 := q p 1 p 2 := q 1 q 2 A rprsnttiv xmpl o squn o struturs gnrting y G ttspn, givn singl g 6
7 s th strt strutur is shown in Figur 5. Agin, nw points o th xpnsion r not Figur 5: A squn o two trminl, prlll sris ntworks gnrt y, G ttspn y irls with sh lins initing th onntion to thir nighorhoos. Purists my osrv tht nighorhoo xpnsion grmmrs r xpt to only nlrg th intrmit struturs. G ttspn lts th g on th lt si tr ing th right hn lmnts or whih it is to th nighorhoo. Isn't this rlly phrs strutur grmmr in whih gs r rwrittn inst o symols? Although on oul opt this intrprttion, it is mor urt to osrv tht i w rtin th lt hn g tr th xpnsion, th rsulting strutur is simply th trnsitiv losur o TTSPN, so thir rsur is not rlly hnging nything. 3 Closur Sps Whn phs strutur proution is ppli to string it prsrvs th strutur o th string. Evry intrmit orm is string. W liv tht ll grmmrs shoul prsrv th ssntil strutur o thir unrlying ojts. But wht is th ssntil strutur o mily o isrt ojts? W liv uniquly gnrt losur oprtors rprsnt si wy o sriing th strutur o isrt systm. Nighorhoo xpnsions hv n n so s to homomorphilly prsrv this onpt o strutur. Any losur oprtor ' must stsiy th xioms: X X:', X Y implis X:' Y:', n X:':' = X:', whr X; Y U r ritrry susts in univrs U o intrst [12]. I in ition, X:' = Y:' implis (X \Y ):' = X:', w sy tht ' is uniquly gnrt. For xmpl, monophoni losur [6], in whih X:' nots ll points lying on horlss pths twn istint points p; q 2 X is uniquly gnrt ovr horl grphs. A vtor sp, or mtroi M, is th losur (or spn ) o st o sis vtors [21]. M must stisy th xhng xiom: p; q 62 X:, n q 2 (X [ p): imply tht 7
8 p 2 (X [ q):. 3 It n shown [19] tht uniquly gnrt losur sps must stisy th nti-xhng xiom: p; q 62 X:', n q 2 (X [ p):' imply tht p 62 (X [ q):'. From this oms th jtiv ntimtroi losur sp. Closur sps orm kin o ul to vtor sps. I th sts o losur sp (U; ') r prtilly orr y X ' Y i n only i Y \ X:' X Y:' w otin losur ltti [19], in whih th sultti o los susts is lowr smimoulr. 4 W hv ssrt tht this losur ltti L (U;') sris th strutur o th unrlying isrt systm. Figur 6() illustrts th losur ltti o th sixth horl grph gnrt in Figur 1. This is omplx igrm; ut thr r signint rgulritis () Ø () Figur 6: A horl grph n its losur ltti tht mk it mnl to nlysis. For xmpl, th sultti o los susts (thos whih r onnt y soli lins) n shown to lowr smi-moulr ltti [15]. Consir th los sust g whih ovrs th los susts g; g; g. Thy, in turn, ovr thir pirwis in's, g; g; g, whih in turn ovr thir ommon in, g, to orm istriutiv sultti. This is gnrl proprty o lowr smi-moulrity, s shown in [4]. Th los sust g is gnrt y th sust g, whih is ov, to th lt, n onnt y sh lin. Suh gnrtors, not X:, r th uniqu miniml susts with givn losur. 5 Th susts ontin twn ny los st X:' 3 This prmits th milir hng o sis o vtor sp. 4 Th ltti o vtor susps prtilly orr y inlusion is uppr smi-moulr. 5 Mny trms r oun in th litrtur or ths gnrting sts pning on ons pproh. With onvx losur in isrt gomtry on spks o xtrm points [5]. With rspt to trnsitiv losurs in 8
9 n its gnrtor X: ompris ooln lgr, [X:'; X:], whih w skth in with sh imon. A w o th orring rltionships twn non-los susts hv n init y ott lins. Although ths losur lttis grow xponntilly, or xmpl, th nl horl grph gnrt in Figur 1 on 9 points hs 146 los sts, on n still rson out thm. W will s this prsntly. But, thy om too lrg to illustrt sily. Although thr r similritis, nighorhoo oprtor is not in gnrl losur oprtor us (1) nighorhoo oprtor n not impotnt, X: X::, n (2) losur oprtor n not union prsrving, X:' [ Y:' (X [ Y ):'. Thr n mny irnt losur oprtors, '. Similrly, thr n mny nighorhoo oprtors,. W sy tht n ' r omptil i X los implis X: is los. It is not hr to show tht i G is horl thn j n ' monophoni r omptil on horl grphs. Similrly, j n ' gosi r omptil on lok grphs. W know o no uniquly gnrt, losur oprtor on tringult plnr gris. But on my xist. In [17] it is shown tht t lst n n istint oprtors n n ovr ny n lmnt systm with n 10. Howvr, suh losur oprtor nnot omptil with th nighorhoo oprtor. Figur 7 inits why. Assum tht vry point is los, so p: j is los or Ø Figur 7: Clos sts o non-horl grph ll p. Consquntly, th our quriltrls ; ;, n r los. Bus los sts r los unr intrstion, th tringls ; ;, n must los s wll. This trmins th uppr portion o th ltti 6 whih nnot losur ltti. rltionl lgrs on lls thm th irruil krnl [1]. In [19], w ll thm gnrtors, ut not thm with th symol, suggstiv o sis th gnrtors o mtroi sp. 6 In Figur 7, ll gs r lso los. Bus los sts r los unr intrstion, th gs ; ;, n must los. On oul ssum tht th rmining 4 gs r not los, in whih s oms th gnrtor o, t. But, this will not hng th ssn o this ountr xmpl. 9
10 A unmntl proprty o uniquly gnrt losur lttis n oun in [19] Lmm 3.1 I ' is uniquly gnrt, n i Z 6= is los, p 2 Z: i n only i Z? pg is los, in whih s Z:? pg (Z? pg):. Using this proprty on n u tht g: = g, g: = g, g: = g, n g: = g. But, this is impossil. Th st g nnot gnrt two irnt los sts! Nithr n g. Bus Figur 7 is th simplst non-horl grph, w hv Thorm 3.2 Lt th iniviul lmnts o n unirt strutur G los. A losur oprtor ' n omptil with th jny nighorhoo oprtor, j i n only i G is horl. Proo: I G is horl, thn th monophoni losur oprtor ' monophoni stiss th thorm. Only i ollows or th xmpl ov. 2 Conjtur 3.3 Lt F mily o isrt unirt systms G. I thr xists nighorhoo oprtor n omptil losur oprtor ' in whih vry singlton is los, thn G is ssntilly tr-lik. For \tr-lik", w xpt nition s on intrstion grphs [14]. In [19], thr irnt losur oprtors r n ovr prtilly orr systms. Thy r Y:' L = xj9y 2 Y; x yg, Y:' R = zj9y 2 Y; y zg, Y:' C = xj9y 1 ; y 2 2 Y; y 1 x y 2 g. On prtilly orr systms, ' L, n ' R r il losur oprtors, ' C is n intrvl, or onvx, losur oprtor. 7 It is not iult to show tht < is omptil with oth ' L n ' R, s is >. Th inu losur ltti rsulting rom th losur oprtor ' L on th 7 point post o Figur 4 is shown in Figur 8. As in Figur 6, th sultti o los susts is not y soli lins; n th ooln intrvls oun y th los susts X:' n thir gnrting sts X: r not y sh lins whih hv n orint towr th uppr lt. This xmpl is lss luttr, so th hrtristi losur ltti strutur is mor vint. For instn, th sust g is th uniqu gnrtor or th los st g. All 2 4 susts in th ooln ltti 7 Prtil orrs my strutur with rspt to t lst ths thr irnt losur oprtors, ' L ; ' R or ' C. Th ility to intrprt isrt systms with rspt to irnt losur onpts n quit powrul. S [18]. 10
11 g g g g g g g g () () Ø Figur 8: A losur ltti L G;' L thy limit (inluing g), hv g s thir losur. Th orring twn ths ooln gnrtor su-lttis, whih hv n suggst y w ott lins, mirror th orring o th los sts low thm. 4 Strutur Prsrvtion Why shoul on opt pross tht gnrts lmily o isrt struturs y ing som ompltly nw portion within nighorhoo rthr thn rwriting n xisting lmnt, whih o ours must hv nighorhoo? A prtil nswr ws givn in stions 1 n 2. Th nighorhoo xpnsion pproh n us to gnrt svrl milis o intrsting isrt systms. In Stion 5, w will monstrt tht th lsss o rgulr n ontxt r lngugs in th Chomsky hirrhy o th phrs strutur grmmrs n susum y nighorhoo xpnsion lsss. In this stion w xmin mor sutl rgumnt s on th homomorphi prsrvtion o isrt systm strutur. Homomorphi (strutur prsrving) gnrtion is most sily n in trms o its invrs, homomorphi prsing. In this s prsing onsists o simply lting th point 11
12 n ll its inint gs. Figur 9() illustrts th ltion o th lmnt rom th horl grph o Figur 2(). W lt, whih is suggstiv o \striking out", not th ltion oprtor. Th susript nots th lmnt, or st, ing lt. In th χ Ø Ø Figur 9: A \ltion" trnsormtion, sour ltti L G, pr-img quivln sts r init y ott lins. Th lmnt is mpp onto in th trgt ltti, n mny sts ontining, suh s g, r mpp onto th st otin y rmoving. But, s w n s rom th mortly omplx pr-img prtition in L G o Figur 9, ltion is not just simpl st xtnsion o point untion. 8 For xmpl, th st g mps onto th st g. This is nssry i th th trnsormtion is to prsrv th strutur o ll th susts, tht is, i th ltti o G:, not L G:, is to smi-homomorphi ontrtion o L G. For isrt systm with n lmnts, its losur ltti will hv 2 n lmnts. Consquntly, ruing th siz o systm grtly rus its stuturl omplxity, s is lr in Figur 9. 8 Dltion o lmnts mk littl sns within th usul nition o isrt untions us lt lmnt hs no img in th oomin. Howvr, in th ontxt o ltti ovr ll susts o isrt sp, lt lmnt or susp n simply mpp onto th mpty st,, in th oomin. 12
13 W now hv mor orml wy o ning wht homomorphi nighorhoo xpnsion, N, rlly is. Lt G (n)?! p G (n?1) ny ltion in isrt systm with n points. By n xpnsion N with rspt to th nighorhoo N w mn n invrs oprtor to p, whr N is th img in G (n?1) o th nighorhoo N o p not p:n in G (n). Thus, w lwys hv G (n)?! p G (n?1)?! N G (n) An, sin ltions lwys inu homomorphi mppings twn th orrsponing losur lttis, nighorhoo xpnsion n rgr s homomorphi s wll. Lmm 4.1 I thr xists losur oprtor, ' tht is omptil with th nighorhoo oprtor,, us y nighorhoo xpnsion grmmr G, thn ny squn o ltions or xpnsions homomorphilly prsrvs th intrnl strutur o h intrmit systm. Th sns o this lmm is illustrt y Figur 10. As w hv sn with G tringl, not ll εn ε ε N N G G G G χ χ χ (1) (2) (3) (4) N ϕ p p p p ε χ... ϕ ϕ ϕ ϕ LG LG LG LG (1) (2) (3) (4)... Figur 10: A squn o ltions/xpnsions xpnsion grmmrs hv omptil losur oprtors. But, i on xists it nors kin o rgulrity in th grmmr's rivtions. 5 Expnsion Grmmrs n th Chomsky Hirrhy How irnt r nighorhoo xpnsion grmmrs rom mor ustomry phrs strutur grmmrs? W will lim thy r vry similr, xpt tht nighorhoo xpnsion sms mor xil. Thorm 5.1 Lt L ny rgulr lngug. Thr xists nighorhoo xpnsion grmmr G in whih th lt si (nighorhoo) o vry proution is los singlton lmnt, suh tht L(G) = L. Proo: Lt G rgulr ny rgulr, or nit stt, n st into ithr lt, or right rursiv orm. W ssum G rgulr is right rursiv, tht is ll proutions r o th orm V := V 0 j, so only th rightmost lmnt o th string is vril. W us < n ' R s our nighorhoo n losur oprtors rsptivly. Th rightmost lmnt 13
14 is los, s r ll rightmost intrvls. This rightmost lmnt provis th nighorhoo, <, or th xpnsion. I < D is ll with V, it is ithr rll with n th nw xpnsion point ll with V 0, or ls < D is just rll with th trminl symol, thry ning th gnrtion. I G rgulr is lt rursiv, w woul us > n ' L s th nisghorhoo n losur oprtors to otin th sm rsult. 2 Th only istintion is tht xpnsion grmmrs with ths proprtis n lso gnrt lngugs o root trs s wll. Thorm 5.2 Lt L ny ontxt r lngug. Thr xists nighorhoo xpnsion grmmr G in whih th lt si o vry proution is los, suh tht L(G) = L. Proo: Bus ontxt r grmmr G prmits non-trminl symols to rwrittn nywhr in th string, w rquir onvx losur ' C whr X:' C = qjp q r; p; r 2 Xg, to mult it. W lso ssum Chomsky norml orm [2, 9], in whih vry proution is o th orm V := V 1 V 2 or V :=. Agin, it is pprnt tht th nighorhoo ll with V n rll with V 1 n th xpnsion lmnt ll V 2. 2 By thir vry ntur, w woul ssum tht nighorhoo xpnsion grmmrs n mult ny ontxt-snsitiv grmmr, whih must non-rsing. Nighorhoo xpnsion grmmrs too must non-rsing, n th nighorhoo pnnt proutions woul sm to xtly ptur th ontxt snsitiv qulity. W liv this to tru. But, s yt, w hv oun no onvining proo. It is possil to tlog nighorhoo xpnsion grmmrs oring to whthr th lt si (nighorhoo) o vry proution is: simpl los st, los st, singlton lmnt, or hs som othr wll n proprty, whih w ll nighorhoo ritri; n whthr th right si (nighorhoo) o vry proution is: singlton lmnt, or hs som othr wll n proprty, whih w ll rplmnt ritri. W osrv tht th lt si o th proution o G horl is los nighorhoo in th intrmit strutur, s in G lok s wll. But, in th lttr grmmr vry lt si is lso singlton lmnt. Th lngug L lok is sust o L horl [11]. I this proution is urthr rstrit to hv only singlton lmnts on th right si, s in G tr, it lngug is L tr whih is sust o L lok. Th grmmr G lt root with hrtristi gnrtion s illustrt in Figur 4, stiss non o th nighorhoo ritri sri ov. I in ition to th nighorhoo 14
15 oprtor <, w hoos ' L (s illustrt in Figur 8) to its omptil losur oprtor, n w rquir h lt si nighorhoo to los, w otin rivtions suh s Figur 11. Rily, rquiring th lt si nighorhoo to los gnrts lngug Figur 11: Anothr squn o nighorhoo xpnsions gnrting lt root yli grphs o trnsitivly los yli grphs. Simply swithing th omptil losur oprtor to ' R inlus th st o ll si rprsnttions o th prtil orr, tht is i x < y n y < z thn th g (x; z) is not in G [16]. I urthr, w rquir th lt si nighorhoo to los ntihin, G lt root gnrts only ths si rprsnttions o prtil orr. In ny s, prtilly orr systms r mor omplx thn irt, or unirt, trs with rspt to th nighorhoo xpnsion hirrhy. This ors with our lgorithmi intuition. Morovr, th st o ll trs is omprl to rgulr lngug whil th st o ll prtil orrs is omprl to ontxt r lngug. Agin, this sms intuitivly orrt. Thus w gin to s linguisti hirrhy mrging y whih w n qulittivly ompr th omplxity o irt n unirt isrt systms. 6 Nighorhoo Oprtors So r w hv only onsir two kins o nighorhoo oprtor simpl no jny, j, n th omprtiv nighorhoos, < ; > ; <> in prtil orrs. Ths r milir, sy to work with, n mk goo illustrtiv xmpls. Howvr, thr xist mny mor wys o ning nighorhoo oprtors n thir mhnisms or ining nw lmnts to n xpning ongurtion. Th xmpls w vlop is this stion r suggstiv o th wy toms my on to orm lrgr moluls, th wy smll prours with som 15
16 wll-n intrs my inorport into lrgr tsk, or how iniviul prts my omin to rt lrgr ssmlis. Our xmpl is surly simpl. Th lmnts r quiltrl tringls with gs ll (in lokwis orr) ; ; or ; ; s show in Figur 12. W hv suprimpos Figur 12: Two sptil lmnts n rrow to mk th orinttion vint in our gurs; ut thy r not tully prt o th grmmr or lngug. W suppos tht ths lmnts r sujt to th n trnsormtions, trnsltion n rottion, in th pln. Now suppos tht nighorhoo oprtor 1 spis tht n ut, n ut, n n ut. W lt th grmmr G 1 onsist o th singl rul p := q Now, pning on th initil orinttion o th initil lmnt rivtion must yil uniorm pttrn suh s Figur 13. Figur 13: A uniorm l in th lngug L(G 1 ) Th rigiity o th nighorhoo oprtor llows no xiility in G 1. Suppos w join th possiility tht n lso ut to th oprtor 1 to otin 2 n grmmr G 2. Rily L(G 1 ) L(G 2 ), ut L(G 2 ) hs mny itionl ongurtions. 16
17 I, using th nw nighorhoo rul, ntrl hxgonl \rottor" s shown in th ntr o Figur 14 is initilly onstrut, n i this is xpn in \rth-rst" shion, thn rigily rotting pttrn must gnrt. This ollows us th only g lls tht Figur 14: A \rotting" l in th lngug L(G 2 ) otin y xpning th ntrl hxgonl ongurtion n ppr on ny onvx xtrior ounry r ; ;, n whih uniquly trmin th orrsponing orinttion o th xpnsion lmnts s thy xpn out rom th ntrl or. O ours, thr xist mor irrgulr ongurtions in th lngug L(G 2 ) whih n gnrt y ltrntly ltting n gs nighors o g. Figur 15 illustrts on suh ongurtion. Not tht nithr o th tringls not y x n y x y Figur 15: A irrgulr rivtion in th lngug L(G 2 ) n oupi in nl ongurtion. It woul ppr tht L(G 2 ) n ritrrily irrgulr; ut this is not tru. W osrv tht, o th 6 possil orinttions o th two lmnts, only 2 ppr in Figur 15, n only 1 mor oul ppr. Similrly, w osrv tht only 3 orinttions ppr in Figur 14; n thy r not thos o Figur 15. Th nighorhoo xpnsion grmmr onpt hs ptur notion o symmtri prity in this vry simpl hxgonl sp. W r xploring wht othr proprtis it n sri. 17
18 Rrns [1] Chris Brink, Wolrm Khl, n Gunthr Shmit. Rltionl Mthos in Computr Sin. Springr Vrlg, Win, [2] Nom Chomsky. Forml Proprtis o Grmmrs. In R.D. Lu, R.R. Bush, n E. Glntr, itors, Hnook o Mthmtil Psyhology. Wily, Nw York, [3] M.J.M. Bor n A. Linnmyr. Mp 0L-systms with g ll ontrol, Comprison o mrkr n yli systm. In Hrtmut Ehrig, Mnr Ngl, Grzgorz Roznrg, n A. Rosnl, itors, Grph-Grmmrs n Thir Applition to Computr Sin, Ltur Nots in Computr Sin 291, pgs 378{392. Springr-Vrlg, D [4] Pul H. Elmn. Mt-istriutiv lttis n th nti-xhng losur. Algr Univrslis, 10(3):290{299, [5] Pul H. Elmn n Rort E. Jmison. Th Thory o Convx Gomtris. Gomtri Dit, 19(3):247{270, D [6] Mrtin Frr n Rort E. Jmison. Convxity in Grphs n Hyprgrphs. SIAM J. Algr n Disrt Mthos, 7(3):433{444, July [7] Fni Gvril. Th Intrstion Grphs o Sutrs in Trs r xtly th Chorl Grphs. J. Comintoril Thory B, 16:47{56, [8] Mrtin Chrls Golumi. Algorithmi Grph Thory n Prt Grphs. Ami Prss, Nw York, [9] John E. Hoprot n Jry D. Ullmn. Introution to Automt Thory, Lngugs, n Computtion. Aison-Wsly, Ring, MA, [10] Rort E. Jmison-Wlnr. Convxity n Blok Grphs. Congrssus Numrntium, 33:129{ 142, D [11] Rort E. Jmison-Wlnr. Prtition Numrs or Trs n Orr Sts. Pi J. o Mth., 96(1):115{140, Spt [12] Kzimirz Kurtowski. Introution to St Thory n Topology. Prgmon Prss, [13] J. Luk n H.B. Luk. From 0L n 1L mp systms to intrmint n trmint growth in plnt morphognsis. In Hrtmut Ehrig, Mnr Ngl, Grzgorz Roznrg, n A. Rosnl, itors, Grph-Grmmrs n Thir Applition to Computr Sin, Ltur Nots in Computr Sin 291, pgs 392{410. Springr-Vrlg, D [14] Trry A. MK n Fr R. MMorris. Topis in Intrstion Grph Thory. SIAM Monogrphs on Disrt Mthmtis n Applitions. Soity or Inustril n Appli Mth., Phillphi, PA, [15] B. Monjrt. A us or rquntly risovring onpt. Orr, 1:415{416, [16] John L. Pltz. Computr Dt Struturs. MGrw-Hill, F
19 [17] John L. Pltz. Evluting th inry prtition untion whn N = 2 n. Congrss Numrntium, 109:3{12, [18] John L. Pltz. Prtition oints o yli grphs. In Mnr Ngl, itor, Pro. WG 95, Grph-Thorti Conpts in Computr Sin, Ltur Nots in Comp. Si., #1017, pgs 318{332. Springr-Vrlg, [19] John L. Pltz. Closur Lttis. Disrt Mthmtis, 154:217{236, [20] John L. Pltz n Azril Rosnl. W Grmmrs. In Pro. Intn'l Joint Con on AI, pgs 609{619, Wshington, DC, My [21] W. T. Tutt. Introution to th Thory o Mtrois. Amr. Elsvir,
, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management
nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o
More informationConstructive Geometric Constraint Solving
Construtiv Gomtri Constrint Solving Antoni Soto i Rir Dprtmnt Llngutgs i Sistms Inormàtis Univrsitt Politèni Ctluny Brlon, Sptmr 2002 CGCS p.1/37 Prliminris CGCS p.2/37 Gomtri onstrint prolm C 2 D L BC
More informationGraph Isomorphism. Graphs - II. Cayley s Formula. Planar Graphs. Outline. Is K 5 planar? The number of labeled trees on n nodes is n n-2
Grt Thortil Is In Computr Sin Vitor Amhik CS 15-251 Ltur 9 Grphs - II Crngi Mllon Univrsity Grph Isomorphism finition. Two simpl grphs G n H r isomorphi G H if thr is vrtx ijtion V H ->V G tht prsrvs jny
More informationb. How many ternary words of length 23 with eight 0 s, nine 1 s and six 2 s?
MATH 3012 Finl Exm, My 4, 2006, WTT Stunt Nm n ID Numr 1. All our prts o this prolm r onrn with trnry strings o lngth n, i.., wors o lngth n with lttrs rom th lpht {0, 1, 2}.. How mny trnry wors o lngth
More informationOutline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example
Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim's Alorithm Introution Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #33 3 Alorithm Gnrl Constrution Mik Joson (Univrsity o Clry)
More informationMath 61 : Discrete Structures Final Exam Instructor: Ciprian Manolescu. You have 180 minutes.
Nm: UCA ID Numr: Stion lttr: th 61 : Disrt Struturs Finl Exm Instrutor: Ciprin nolsu You hv 180 minuts. No ooks, nots or lultors r llow. Do not us your own srth ppr. 1. (2 points h) Tru/Fls: Cirl th right
More informationCOMPLEXITY OF COUNTING PLANAR TILINGS BY TWO BARS
OMPLXITY O OUNTING PLNR TILINGS Y TWO RS KYL MYR strt. W show tht th prolm o trmining th numr o wys o tiling plnr igur with horizontl n vrtil r is #P-omplt. W uil o o th rsults o uquir, Nivt, Rmil, n Roson
More informationTrees as operads. Lecture A formalism of trees
Ltur 2 rs s oprs In this ltur, w introu onvnint tgoris o trs tht will us or th inition o nroil sts. hs tgoris r gnrliztions o th simpliil tgory us to in simpliil sts. First w onsir th s o plnr trs n thn
More information(2) If we multiplied a row of B by λ, then the value is also multiplied by λ(here lambda could be 0). namely
. DETERMINANT.. Dtrminnt. Introution:I you think row vtor o mtrix s oorint o vtors in sp, thn th gomtri mning o th rnk o th mtrix is th imnsion o th prlllppi spnn y thm. But w r not only r out th imnsion,
More informationCycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!
Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik
More informationAn undirected graph G = (V, E) V a set of vertices E a set of unordered edges (v,w) where v, w in V
Unirt Grphs An unirt grph G = (V, E) V st o vrtis E st o unorr gs (v,w) whr v, w in V USE: to mol symmtri rltionships twn ntitis vrtis v n w r jnt i thr is n g (v,w) [or (w,v)] th g (v,w) is inint upon
More information1 Introduction to Modulo 7 Arithmetic
1 Introution to Moulo 7 Arithmti Bor w try our hn t solvin som hr Moulr KnKns, lt s tk los look t on moulr rithmti, mo 7 rithmti. You ll s in this sminr tht rithmti moulo prim is quit irnt rom th ons w
More informationAlgorithmic and NP-Completeness Aspects of a Total Lict Domination Number of a Graph
Intrntionl J.Mth. Comin. Vol.1(2014), 80-86 Algorithmi n NP-Compltnss Aspts of Totl Lit Domintion Numr of Grph Girish.V.R. (PES Institut of Thnology(South Cmpus), Bnglor, Krntk Stt, Ini) P.Ush (Dprtmnt
More informationPaths. Connectivity. Euler and Hamilton Paths. Planar graphs.
Pths.. Eulr n Hmilton Pths.. Pth D. A pth rom s to t is squn o gs {x 0, x 1 }, {x 1, x 2 },... {x n 1, x n }, whr x 0 = s, n x n = t. D. Th lngth o pth is th numr o gs in it. {, } {, } {, } {, } {, } {,
More informationPlanar Upward Drawings
C.S. 252 Pro. Rorto Tmssi Computtionl Gomtry Sm. II, 1992 1993 Dt: My 3, 1993 Sri: Shmsi Moussvi Plnr Upwr Drwings 1 Thorm: G is yli i n only i it hs upwr rwing. Proo: 1. An upwr rwing is yli. Follow th
More informationCSE 373: More on graphs; DFS and BFS. Michael Lee Wednesday, Feb 14, 2018
CSE 373: Mor on grphs; DFS n BFS Mihl L Wnsy, F 14, 2018 1 Wrmup Wrmup: Disuss with your nighor: Rmin your nighor: wht is simpl grph? Suppos w hv simpl, irt grph with x nos. Wht is th mximum numr of gs
More informationWhy the Junction Tree Algorithm? The Junction Tree Algorithm. Clique Potential Representation. Overview. Chris Williams 1.
Why th Juntion Tr lgorithm? Th Juntion Tr lgorithm hris Willims 1 Shool of Informtis, Univrsity of Einurgh Otor 2009 Th JT is gnrl-purpos lgorithm for omputing (onitionl) mrginls on grphs. It os this y
More informationGarnir Polynomial and their Properties
Univrsity of Cliforni, Dvis Dprtmnt of Mthmtis Grnir Polynomil n thir Proprtis Author: Yu Wng Suprvisor: Prof. Gorsky Eugny My 8, 07 Grnir Polynomil n thir Proprtis Yu Wng mil: uywng@uvis.u. In this ppr,
More informationGraphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1
CSC 00 Disrt Struturs : Introuon to Grph Thory Grphs Grphs CSC 00 Disrt Struturs Villnov Univrsity Grphs r isrt struturs onsisng o vrs n gs tht onnt ths vrs. Grphs n us to mol: omputr systms/ntworks mthml
More informationThe University of Sydney MATH2969/2069. Graph Theory Tutorial 5 (Week 12) Solutions 2008
Th Univrsity o Syny MATH2969/2069 Grph Thory Tutoril 5 (Wk 12) Solutions 2008 1. (i) Lt G th isonnt plnr grph shown. Drw its ul G, n th ul o th ul (G ). (ii) Show tht i G is isonnt plnr grph, thn G is
More informationOutline. Computer Science 331. Computation of Min-Cost Spanning Trees. Costs of Spanning Trees in Weighted Graphs
Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim s Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #34 Introution Min-Cost Spnnin Trs 3 Gnrl Constrution 4 5 Trmintion n Eiiny 6 Aitionl
More informationExam 1 Solution. CS 542 Advanced Data Structures and Algorithms 2/14/2013
CS Avn Dt Struturs n Algorithms Exm Solution Jon Turnr //. ( points) Suppos you r givn grph G=(V,E) with g wights w() n minimum spnning tr T o G. Now, suppos nw g {u,v} is to G. Dsri (in wors) mtho or
More information0.1. Exercise 1: the distances between four points in a graph
Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 pg 1 Mth 707 Spring 2017 (Drij Grinrg): mitrm 3 u: W, 3 My 2017, in lss or y mil (grinr@umn.u) or lss S th wsit or rlvnt mtril. Rsults provn in th nots, or in
More informationV={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)}
Introution Computr Sin & Enginring 423/823 Dsign n Anlysis of Algorithms Ltur 03 Elmntry Grph Algorithms (Chptr 22) Stphn Sott (Apt from Vinohnrn N. Vriym) I Grphs r strt t typs tht r pplil to numrous
More informationGraphs. CSC 1300 Discrete Structures Villanova University. Villanova CSC Dr Papalaskari
Grphs CSC 1300 Disrt Struturs Villnov Univrsity Grphs Grphs r isrt struturs onsis?ng of vr?s n gs tht onnt ths vr?s. Grphs n us to mol: omputr systms/ntworks mthm?l rl?ons logi iruit lyout jos/prosss f
More informationCSC Design and Analysis of Algorithms. Example: Change-Making Problem
CSC 801- Dsign n Anlysis of Algorithms Ltur 11 Gry Thniqu Exmpl: Chng-Mking Prolm Givn unlimit mounts of oins of nomintions 1 > > m, giv hng for mount n with th lst numr of oins Exmpl: 1 = 25, 2 =10, =
More informationV={A,B,C,D,E} E={ (A,D),(A,E),(B,D), (B,E),(C,D),(C,E)}
s s of s Computr Sin & Enginring 423/823 Dsign n Anlysis of Ltur 03 (Chptr 22) Stphn Sott (Apt from Vinohnrn N. Vriym) s of s s r strt t typs tht r pplil to numrous prolms Cn ptur ntitis, rltionships twn
More information1. Determine whether or not the following binary relations are equivalence relations. Be sure to justify your answers.
Mth 0 Exm - Prti Prolm Solutions. Dtrmin whthr or not th ollowing inry rltions r quivln rltions. B sur to justiy your nswrs. () {(0,0),(0,),(0,),(,),(,),(,),(,),(,0),(,),(,),(,0),(,),(.)} on th st A =
More informationPresent state Next state Q + M N
Qustion 1. An M-N lip-lop works s ollows: I MN=00, th nxt stt o th lip lop is 0. I MN=01, th nxt stt o th lip-lop is th sm s th prsnt stt I MN=10, th nxt stt o th lip-lop is th omplmnt o th prsnt stt I
More informationCS 241 Analysis of Algorithms
CS 241 Anlysis o Algorithms Prossor Eri Aron Ltur T Th 9:00m Ltur Mting Lotion: OLB 205 Businss HW6 u lry HW7 out tr Thnksgiving Ring: Ch. 22.1-22.3 1 Grphs (S S. B.4) Grphs ommonly rprsnt onntions mong
More informationCSE 373. Graphs 1: Concepts, Depth/Breadth-First Search reading: Weiss Ch. 9. slides created by Marty Stepp
CSE 373 Grphs 1: Conpts, Dpth/Brth-First Srh ring: Wiss Ch. 9 slis rt y Mrty Stpp http://www.s.wshington.u/373/ Univrsity o Wshington, ll rights rsrv. 1 Wht is grph? 56 Tokyo Sttl Soul 128 16 30 181 140
More information12/3/12. Outline. Part 10. Graphs. Circuits. Euler paths/circuits. Euler s bridge problem (Bridges of Konigsberg Problem)
12/3/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 Ciruits Cyl 2 Eulr
More informationCS 461, Lecture 17. Today s Outline. Example Run
Prim s Algorithm CS 461, Ltur 17 Jr Si Univrsity o Nw Mxio In Prim s lgorithm, th st A mintin y th lgorithm orms singl tr. Th tr strts rom n ritrry root vrtx n grows until it spns ll th vrtis in V At h
More information5/9/13. Part 10. Graphs. Outline. Circuits. Introduction Terminology Implementing Graphs
Prt 10. Grphs CS 200 Algorithms n Dt Struturs 1 Introution Trminology Implmnting Grphs Outlin Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 2 Ciruits Cyl A spil yl
More informationModule graph.py. 1 Introduction. 2 Graph basics. 3 Module graph.py. 3.1 Objects. CS 231 Naomi Nishimura
Moul grph.py CS 231 Nomi Nishimur 1 Introution Just lik th Python list n th Python itionry provi wys of storing, ssing, n moifying t, grph n viw s wy of storing, ssing, n moifying t. Bus Python os not
More informationSimilarity Search. The Binary Branch Distance. Nikolaus Augsten.
Similrity Srh Th Binry Brnh Distn Nikolus Augstn nikolus.ugstn@sg..t Dpt. of Computr Sins Univrsity of Slzurg http://rsrh.uni-slzurg.t Vrsion Jnury 11, 2017 Wintrsmstr 2016/2017 Augstn (Univ. Slzurg) Similrity
More informationNumbering Boundary Nodes
Numring Bounry Nos Lh MBri Empori Stt Univrsity August 10, 2001 1 Introution Th purpos of this ppr is to xplor how numring ltril rsistor ntworks ffts thir rspons mtrix, Λ. Morovr, wht n lrn from Λ out
More informationA 4-state solution to the Firing Squad Synchronization Problem based on hybrid rule 60 and 102 cellular automata
A 4-stt solution to th Firing Squ Synhroniztion Prolm s on hyri rul 60 n 102 llulr utomt LI Ning 1, LIANG Shi-li 1*, CUI Shung 1, XU Mi-ling 1, ZHANG Ling 2 (1. Dprtmnt o Physis, Northst Norml Univrsity,
More informationSection 10.4 Connectivity (up to paths and isomorphism, not including)
Toy w will isuss two stions: Stion 10.3 Rprsnting Grphs n Grph Isomorphism Stion 10.4 Conntivity (up to pths n isomorphism, not inluing) 1 10.3 Rprsnting Grphs n Grph Isomorphism Whn w r working on n lgorithm
More informationSeven-Segment Display Driver
7-Smnt Disply Drivr, Ron s in 7-Smnt Disply Drivr, Ron s in Prolm 62. 00 0 0 00 0000 000 00 000 0 000 00 0 00 00 0 0 0 000 00 0 00 BCD Diits in inry Dsin Drivr Loi 4 inputs, 7 outputs 7 mps, h with 6 on
More informationProperties of Hexagonal Tile local and XYZ-local Series
1 Proprtis o Hxgonl Til lol n XYZ-lol Sris Jy Arhm 1, Anith P. 2, Drsnmik K. S. 3 1 Dprtmnt o Bsi Sin n Humnitis, Rjgiri Shool o Enginring n, Thnology, Kkkn, Ernkulm, Krl, Ini. jyjos1977@gmil.om 2 Dprtmnt
More informationECE COMBINATIONAL BUILDING BLOCKS - INVEST 13 DECODERS AND ENCODERS
C 24 - COMBINATIONAL BUILDING BLOCKS - INVST 3 DCODS AND NCODS FALL 23 AP FLZ To o "wll" on this invstition you must not only t th riht nswrs ut must lso o nt, omplt n onis writups tht mk ovious wht h
More informationCS September 2018
Loil los Distriut Systms 06. Loil los Assin squn numrs to msss All ooprtin prosss n r on orr o vnts vs. physil los: rport tim o y Assum no ntrl tim sour Eh systm mintins its own lol lo No totl orrin o
More informationQUESTIONS BEGIN HERE!
Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt o Computr n Inormtion Sins CSCI 2710 (Trno) Disrt Struturs TEST or Sprin Smstr, 2005 R this or strtin! This tst is los ook
More informationComplete Solutions for MATH 3012 Quiz 2, October 25, 2011, WTT
Complt Solutions or MATH 012 Quiz 2, Otor 25, 2011, WTT Not. T nswrs ivn r r mor omplt tn is xpt on n tul xm. It is intn tt t mor omprnsiv solutions prsnt r will vlul to stunts in stuyin or t inl xm. In
More informationOutline. Binary Tree
Outlin Similrity Srh Th Binry Brnh Distn Nikolus Austn nikolus.ustn@s..t Dpt. o Computr Sins Univrsity o Slzur http://rsrh.uni-slzur.t 1 Binry Brnh Distn Binry Rprsnttion o Tr Binry Brnhs Lowr Boun or
More informationS i m p l i f y i n g A l g e b r a SIMPLIFYING ALGEBRA.
S i m p l i y i n g A l g r SIMPLIFYING ALGEBRA www.mthltis.o.nz Simpliying SIMPLIFYING Algr ALGEBRA Algr is mthmtis with mor thn just numrs. Numrs hv ix vlu, ut lgr introus vrils whos vlus n hng. Ths
More informationDesigning A Concrete Arch Bridge
This is th mous Shwnh ri in Switzrln, sin y Rort Millrt in 1933. It spns 37.4 mtrs (122 t) n ws sin usin th sm rphil mths tht will monstrt in this lsson. To pro with this lsson, lik on th Nxt utton hr
More informationAnnouncements. Not graphs. These are Graphs. Applications of Graphs. Graph Definitions. Graphs & Graph Algorithms. A6 released today: Risk
Grphs & Grph Algorithms Ltur CS Spring 6 Announmnts A6 rls toy: Risk Strt signing with your prtnr sp Prlim usy Not grphs hs r Grphs K 5 K, =...not th kin w mn, nywy Applitions o Grphs Communition ntworks
More informationCSE303 - Introduction to the Theory of Computing Sample Solutions for Exercises on Finite Automata
CSE303 - Introduction to th Thory of Computing Smpl Solutions for Exrciss on Finit Automt Exrcis 2.1.1 A dtrministic finit utomton M ccpts th mpty string (i.., L(M)) if nd only if its initil stt is finl
More informationOutline. Circuits. Euler paths/circuits 4/25/12. Part 10. Graphs. Euler s bridge problem (Bridges of Konigsberg Problem)
4/25/12 Outlin Prt 10. Grphs CS 200 Algorithms n Dt Struturs Introution Trminology Implmnting Grphs Grph Trvrsls Topologil Sorting Shortst Pths Spnning Trs Minimum Spnning Trs Ciruits 1 2 Eulr s rig prolm
More informationUsing the Printable Sticker Function. Using the Edit Screen. Computer. Tablet. ScanNCutCanvas
SnNCutCnvs Using th Printl Stikr Funtion On-o--kin stikrs n sily rt y using your inkjt printr n th Dirt Cut untion o th SnNCut mhin. For inormtion on si oprtions o th SnNCutCnvs, rr to th Hlp. To viw th
More informationCSE 373: AVL trees. Warmup: Warmup. Interlude: Exploring the balance invariant. AVL Trees: Invariants. AVL tree invariants review
rmup CSE 7: AVL trs rmup: ht is n invrint? Mihl L Friy, Jn 9, 0 ht r th AVL tr invrints, xtly? Disuss with your nighor. AVL Trs: Invrints Intrlu: Exploring th ln invrint Cor i: xtr invrint to BSTs tht
More informationMAT3707. Tutorial letter 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS. Semester 1. Department of Mathematical Sciences MAT3707/201/1/2017
MAT3707/201/1/2017 Tutoril lttr 201/1/2017 DISCRETE MATHEMATICS: COMBINATORICS MAT3707 Smstr 1 Dprtmnt o Mtmtil Sins SOLUTIONS TO ASSIGNMENT 01 BARCODE Din tomorrow. univrsity o sout ri SOLUTIONS TO ASSIGNMENT
More informationSteinberg s Conjecture is false
Stinrg s Conjtur is als arxiv:1604.05108v2 [math.co] 19 Apr 2016 Vinnt Cohn-Aa Mihal Hig Danil Král Zhntao Li Estan Salgao Astrat Stinrg onjtur in 1976 that vry planar graph with no yls o lngth our or
More informationProblem solving by search
Prolm solving y srh Tomáš voo Dprtmnt o Cyrntis, Vision or Roots n Autonomous ystms Mrh 5, 208 / 3 Outlin rh prolm. tt sp grphs. rh trs. trtgis, whih tr rnhs to hoos? trtgy/algorithm proprtis? Progrmming
More informationCS61B Lecture #33. Administrivia: Autograder will run this evening. Today s Readings: Graph Structures: DSIJ, Chapter 12
Aministrivi: CS61B Ltur #33 Autogrr will run this vning. Toy s Rings: Grph Struturs: DSIJ, Chptr 12 Lst moifi: W Nov 8 00:39:28 2017 CS61B: Ltur #33 1 Why Grphs? For xprssing non-hirrhilly rlt itms Exmpls:
More informationQUESTIONS BEGIN HERE!
Points miss: Stunt's Nm: Totl sor: /100 points Est Tnnss Stt Univrsity Dprtmnt of Computr n Informtion Sins CSCI 710 (Trnoff) Disrt Struturs TEST for Fll Smstr, 00 R this for strtin! This tst is los ook
More information12. Traffic engineering
lt2.ppt S-38. Introution to Tltrffi Thory Spring 200 2 Topology Pths A tlommunition ntwork onsists of nos n links Lt N not th st of nos in with n Lt J not th st of nos in with j N = {,,,,} J = {,2,3,,2}
More informationSolutions for HW11. Exercise 34. (a) Use the recurrence relation t(g) = t(g e) + t(g/e) to count the number of spanning trees of v 1
Solutions for HW Exris. () Us th rurrn rltion t(g) = t(g ) + t(g/) to ount th numr of spnning trs of v v v u u u Rmmr to kp multipl gs!! First rrw G so tht non of th gs ross: v u v Rursing on = (v, u ):
More informationCS200: Graphs. Graphs. Directed Graphs. Graphs/Networks Around Us. What can this represent? Sometimes we want to represent directionality:
CS2: Grphs Prihr Ch. 4 Rosn Ch. Grphs A olltion of nos n gs Wht n this rprsnt? n A omputr ntwork n Astrtion of mp n Soil ntwork CS2 - Hsh Tls 2 Dirt Grphs Grphs/Ntworks Aroun Us A olltion of nos n irt
More informationA Simple Code Generator. Code generation Algorithm. Register and Address Descriptors. Example 3/31/2008. Code Generation
A Simpl Co Gnrtor Co Gnrtion Chptr 8 II Gnrt o for singl si lok How to us rgistrs? In most mhin rhitturs, som or ll of th oprnsmust in rgistrs Rgistrs mk goo tmporris Hol vlus tht r omput in on si lok
More informationarxiv: v1 [cs.ds] 20 Feb 2008
Symposium on Thortil Aspts of Computr Sin 2008 (Borux), pp. 361-372 www.sts-onf.org rxiv:0802.2867v1 [s.ds] 20 F 2008 FIXED PARAMETER POLYNOMIAL TIME ALGORITHMS FOR MAXIMUM AGREEMENT AND COMPATIBLE SUPERTREES
More informationFormal Concept Analysis
Forml Conpt Anlysis Conpt intnts s losd sts Closur Systms nd Implitions 4 Closur Systms 0.06.005 Nxt-Closur ws dvlopd y B. Gntr (984). Lt M = {,..., n}. A M is ltilly smllr thn B M, if B A if th smllst
More informationGraph Contraction and Connectivity
Chptr 17 Grph Contrtion n Conntivity So r w hv mostly ovr thniqus or solving prolms on grphs tht wr vlop in th ontxt o squntil lgorithms. Som o thm r sy to prllliz whil othrs r not. For xmpl, w sw tht
More informationRegister Allocation. Register Allocation. Principle Phases. Principle Phases. Example: Build. Spills 11/14/2012
Rgistr Allotion W now r l to o rgistr llotion on our intrfrn grph. W wnt to l with two typs of onstrints: 1. Two vlus r liv t ovrlpping points (intrfrn grph) 2. A vlu must or must not in prtiulr rhitturl
More informationFSA. CmSc 365 Theory of Computation. Finite State Automata and Regular Expressions (Chapter 2, Section 2.3) ALPHABET operations: U, concatenation, *
CmSc 365 Thory of Computtion Finit Stt Automt nd Rgulr Exprssions (Chptr 2, Sction 2.3) ALPHABET oprtions: U, conctntion, * otin otin Strings Form Rgulr xprssions dscri Closd undr U, conctntion nd * (if
More informationDEVELOPING COMPUTER PROGRAM FOR COMPUTING EIGENPAIRS OF 2 2 MATRICES AND 3 3 UPPER TRIANGULAR MATRICES USING THE SIMPLE ALGORITHM
Fr Est Journl o Mthtil Sins (FJMS) Volu 6 Nur Pgs 8- Pulish Onlin: Sptr This ppr is vill onlin t http://pphjo/journls/jsht Pushp Pulishing Hous DEVELOPING COMPUTER PROGRAM FOR COMPUTING EIGENPAIRS OF MATRICES
More informationarxiv: v1 [math.mg] 5 Oct 2015
onvx pntgons tht mit i-lok trnsitiv tilings sy Mnn, Jnnifr MLou-Mnn, vi Von ru rxiv:1510.01186v1 [mth.mg] 5 Ot 2015 strt Univrsity of Wshington othll Univrsity of Wshington othll Univrsity of Wshington
More informationCan transitive orientation make sandwich problems easier?
Disrt Mthmtis 07 (007) 00 04 www.lsvir.om/lot/is Cn trnsitiv orinttion mk snwih prolms sir? Mihl Hi, Dvi Klly, Emmnull Lhr,, Christoph Pul,, CNRS, LIRMM, Univrsité Montpllir II, 6 ru A, 4 9 Montpllir C,
More information# 1 ' 10 ' 100. Decimal point = 4 hundred. = 6 tens (or sixty) = 5 ones (or five) = 2 tenths. = 7 hundredths.
How os it work? Pl vlu o imls rprsnt prts o whol numr or ojt # 0 000 Tns o thousns # 000 # 00 Thousns Hunrs Tns Ons # 0 Diml point st iml pl: ' 0 # 0 on tnth n iml pl: ' 0 # 00 on hunrth r iml pl: ' 0
More informationMore Foundations. Undirected Graphs. Degree. A Theorem. Graphs, Products, & Relations
Mr Funtins Grphs, Pruts, & Rltins Unirt Grphs An unirt grph is pir f 1. A st f ns 2. A st f gs (whr n g is st f tw ns*) Friy, Sptmr 2, 2011 Ring: Sipsr 0.2 ginning f 0.4; Stughtn 1.1.5 ({,,,,}, {{,}, {,},
More informationOrganization. Dominators. Control-flow graphs 8/30/2010. Dominators, control-dependence. Dominator relation of CFGs
Orniztion Domintors, ontrol-pnn n SSA orm Domintor rltion o CFGs postomintor rltion Domintor tr Computin omintor rltion n tr Dtlow lorithm Lnur n Trjn lorithm Control-pnn rltion SSA orm Control-low rphs
More informationCOMP108 Algorithmic Foundations
Grdy mthods Prudn Wong http://www.s.liv..uk/~pwong/thing/omp108/01617 Coin Chng Prolm Suppos w hv 3 typs of oins 10p 0p 50p Minimum numr of oins to mk 0.8, 1.0, 1.? Grdy mthod Lrning outoms Undrstnd wht
More informationA 43k Kernel for Planar Dominating Set using Computer-Aided Reduction Rule Discovery
A 43k Krnl for Plnr Dominting St using Computr-Ai Rution Rul Disovry John Torås Hlsth Dprtmnt of Informtis Univrsity of Brgn A thsis sumitt for th gr of Mstr of Sin Suprvisor: Dnil Lokshtnov Frury 2016
More informationGraph Theory. Vertices. Vertices are also known as nodes, points and (in social networks) as actors, agents or players.
Stphn P. Borgtti Grph Thory A lthough grph thory is on o th youngr rnhs o mthmtis, it is unmntl to numr o ppli ils, inluing oprtions rsrh, omputr sin, n soil ntwork nlysis. In this hptr w isuss th si onpts
More informationO n t h e e x t e n s i o n o f a p a r t i a l m e t r i c t o a t r e e m e t r i c
O n t h x t n s i o n o f p r t i l m t r i t o t r m t r i Alin Guénoh, Bruno Llr 2, Vlimir Mkrnkov 3 Institut Mthémtiqus Luminy, 63 vnu Luminy, F-3009 MARSEILLE, FRANCE, gunoh@iml.univ-mrs.fr 2 Cntr
More informationQuartets and unrooted level-k networks
Phylogntis Workshop, Is Nwton Institut or Mthmtil Sins Cmrig 21/06/2011 Qurtts n unroot lvl-k ntworks Philipp Gmtt Outlin Astrt n xpliit phylognti ntworks Lvl-k ntworks Unroot lvl-1 ntworks n irulr split
More informationlearning objectives learn what graphs are in mathematical terms learn how to represent graphs in computers learn about typical graph algorithms
rp loritms lrnin ojtivs loritms your sotwr systm sotwr rwr lrn wt rps r in mtmtil trms lrn ow to rprsnt rps in omputrs lrn out typil rp loritms wy rps? intuitivly, rp is orm y vrtis n s twn vrtis rps r
More informationComputational Biology, Phylogenetic Trees. Consensus methods
Computtionl Biology, Phylognti Trs Consnsus mthos Asgr Bruun & Bo Simonsn Th 16th of Jnury 2008 Dprtmnt of Computr Sin Th univrsity of Copnhgn 0 Motivtion Givn olltion of Trs Τ = { T 0,..., T n } W wnt
More informationMULTIPLE-LEVEL LOGIC OPTIMIZATION II
MUTIPE-EVE OGIC OPTIMIZATION II Booln mthos Eploit Booln proprtis Giovnni D Mihli Don t r onitions Stnfor Univrsit Minimition of th lol funtions Slowr lgorithms, ttr qulit rsults Etrnl on t r onitions
More informationWeighted graphs -- reminder. Data Structures LECTURE 15. Shortest paths algorithms. Example: weighted graph. Two basic properties of shortest paths
Dt Strutur LECTURE Shortt pth lgorithm Proprti of hortt pth Bllmn-For lgorithm Dijktr lgorithm Chptr in th txtook (pp ). Wight grph -- rminr A wight grph i grph in whih g hv wight (ot) w(v i, v j ) >.
More informationNefertiti. Echoes of. Regal components evoke visions of the past MULTIPLE STITCHES. designed by Helena Tang-Lim
MULTIPLE STITCHES Nrtiti Ehos o Rgl omponnts vok visions o th pst sign y Hln Tng-Lim Us vrity o stiths to rt this rgl yt wrl sign. Prt sping llows squr s to mk roun omponnts tht rp utiully. FCT-SC-030617-07
More informationAnnouncements. These are Graphs. This is not a Graph. Graph Definitions. Applications of Graphs. Graphs & Graph Algorithms
Grphs & Grph Algorithms Ltur CS Fll 5 Announmnts Upoming tlk h Mny Crrs o Computr Sintist Or how Computr Sin gr mpowrs you to o muh mor thn o Dn Huttnlohr, Prossor in th Dprtmnt o Computr Sin n Johnson
More informationDiscovering Pairwise Compatibility Graphs
Disovring Pirwis Comptiility Grphs Muhmm Nur Ynhon, M. Shmsuzzoh Byzi, n M. Siur Rhmn Dprtmnt of Computr Sin n Enginring Bnglsh Univrsity of Enginring n Thnology nur.ynhon@gmil.om, shms.yzi@gmil.om, siurrhmn@s.ut..
More informationEE1000 Project 4 Digital Volt Meter
Ovrviw EE1000 Projt 4 Diitl Volt Mtr In this projt, w mk vi tht n msur volts in th rn o 0 to 4 Volts with on iit o ury. Th input is n nlo volt n th output is sinl 7-smnt iit tht tlls us wht tht input s
More informationIEEE TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. TK, NO. TK, MONTHTK YEARTK 1. Hamiltonian Walks of Phylogenetic Treespaces
IEEE TRNSTIONS ON OMPUTTIONL IOLOGY ND IOINFORMTIS, VOL. TK, NO. TK, MONTHTK YERTK Hmiltonin Wlks of Phylognti Trsps Kvughn Goron, Eri For, n Kthrin St. John strt W nswr rynt s omintoril hllng on miniml
More informationCS553 Lecture Register Allocation 1
Low-Lvl Issus Lst ltur Livnss nlysis Rgistr llotion Toy Mor rgistr llotion Wnsy Common suxprssion limintion or PA2 Logistis PA1 is u PA2 hs n post Mony th 15 th, no lss u to LCPC in Orgon CS553 Ltur Rgistr
More informationMultipoint Alternate Marking method for passive and hybrid performance monitoring
Multipoint Altrnt Mrkin mtho or pssiv n hyri prormn monitorin rt-iool-ippm-multipoint-lt-mrk-00 Pru, Jul 2017, IETF 99 Giuspp Fiool (Tlom Itli) Muro Coilio (Tlom Itli) Amo Spio (Politnio i Torino) Riro
More informationXML and Databases. Outline. Recall: Top-Down Evaluation of Simple Paths. Recall: Top-Down Evaluation of Simple Paths. Sebastian Maneth NICTA and UNSW
Smll Pth Quiz ML n Dtss Cn you giv n xprssion tht rturns th lst / irst ourrn o h istint pri lmnt? Ltur 8 Strming Evlution: how muh mmory o you n? Sstin Mnth NICTA n UNSW
More informationECE 407 Computer Aided Design for Electronic Systems. Circuit Modeling and Basic Graph Concepts/Algorithms. Instructor: Maria K. Michael.
0 Computr i Dsign or Eltroni Systms Ciruit Moling n si Grph Conptslgorithms Instrutor: Mri K. Mihl MKM - Ovrviw hviorl vs. Struturl mols Extrnl vs. Intrnl rprsnttions Funtionl moling t Logi lvl Struturl
More informationRegister Allocation. How to assign variables to finitely many registers? What to do when it can t be done? How to do so efficiently?
Rgistr Allotion Rgistr Allotion How to ssign vrils to initly mny rgistrs? Wht to o whn it n t on? How to o so iintly? Mony, Jun 3, 13 Mmory Wll Disprity twn CPU sp n mmory ss sp improvmnt Mony, Jun 3,
More informationDUET WITH DIAMONDS COLOR SHIFTING BRACELET By Leslie Rogalski
Dut with Dimons Brlt DUET WITH DIAMONDS COLOR SHIFTING BRACELET By Lsli Roglski Photo y Anrw Wirth Supruo DUETS TM from BSmith rt olor shifting fft tht mks your work tk on lif of its own s you mov! This
More informationIntegration Continued. Integration by Parts Solving Definite Integrals: Area Under a Curve Improper Integrals
Intgrtion Continud Intgrtion y Prts Solving Dinit Intgrls: Ar Undr Curv Impropr Intgrls Intgrtion y Prts Prticulrly usul whn you r trying to tk th intgrl o som unction tht is th product o n lgric prssion
More informationResearch Article On the Genus of the Zero-Divisor Graph of Z n
Intrntionl Journl o Comintoris, Artil ID 7, pgs http://x.oi.org/.1/14/7 Rsrh Artil On th Gnus o th Zro-Divisor Grph o Z n Huong Su 1 n Piling Li 2 1 Shool o Mthmtil Sins, Gungxi Thrs Eution Univrsity,
More informationGreedy Algorithms, Activity Selection, Minimum Spanning Trees Scribes: Logan Short (2015), Virginia Date: May 18, 2016
Ltur 4 Gry Algorithms, Ativity Sltion, Minimum Spnning Trs Sris: Logn Short (5), Virgini Dt: My, Gry Algorithms Suppos w wnt to solv prolm, n w r l to om up with som rursiv ormultion o th prolm tht woul
More informationNP-Completeness. CS3230 (Algorithm) Traveling Salesperson Problem. What s the Big Deal? Given a Problem. What s the Big Deal? What s the Big Deal?
NP-Compltnss 1. Polynomil tim lgorithm 2. Polynomil tim rution 3.P vs NP 4.NP-ompltnss (som slis y P.T. Um Univrsity o Txs t Dlls r us) Trvling Slsprson Prolm Fin minimum lngth tour tht visits h ity on
More informationThe Plan. Honey, I Shrunk the Data. Why Compress. Data Compression Concepts. Braille Example. Braille. x y xˆ
h ln ony, hrunk th t ihr nr omputr in n nginring nivrsity of shington t omprssion onpts ossy t omprssion osslss t omprssion rfix os uffmn os th y 24 2 t omprssion onpts originl omprss o x y xˆ nor or omprss
More informationAnalysis for Balloon Modeling Structure based on Graph Theory
Anlysis for lloon Moling Strutur bs on Grph Thory Abstrt Mshiro Ur* Msshi Ym** Mmoru no** Shiny Miyzki** Tkmi Ysu* *Grut Shool of Informtion Sin, Ngoy Univrsity **Shool of Informtion Sin n Thnology, hukyo
More informationN=4 L=4. Our first non-linear data structure! A graph G consists of two sets G = {V, E} A set of V vertices, or nodes f
lulu jwtt pnlton sin towr ounrs hpl lpp lu Our irst non-linr t strutur! rph G onsists o two sts G = {V, E} st o V vrtis, or nos st o E s, rltionships twn nos surph G onsists o sust o th vrtis n s o G jnt
More information