An Introduction to Clique Minimal Separator Decomposition
|
|
- Phillip Hicks
- 5 years ago
- Views:
Transcription
1 Alortms 2010, 3, ; o: / Rvw OPEN ACCESS lortms ISSN An Introuton to Clqu Mnml Sprtor Domposton Ann Brry 1,, Romn Poorln 1 n Gnvèv Smont 2 1 LIMOS UMR CNRS 6158, Ensml Sntqu s Cézux, F Auèr, Frn; E-Ml: poorl@sm.r 2 LIRMM, 161 Ru A, F Montpllr, Frn; E-Ml: smont@lrmm.r Autor to wom orrsponn soul rss; E-Ml: rry@sm.r; Tl.: Rv: 7 Aprl 2010 / Apt: 28 Aprl 2010 / Puls: 14 My 2010 Astrt: Ts ppr s rvw w prsnts n xplns t omposton o rps y lqu mnml sprtors. T p s lsurly, w v mny xmpls n urs. Esy lortms r prov to mplmnt ts omposton. T storl n tortl roun s vn, s wll s sts o proos o t struturl rsults nvolv. Kywors: rp omposton; lqu mnml sprtor; mnml trnulton 1. Introuton Ts ppr s sn s prsntton or t not so wll-nown rp omposton w w ll lqu mnml sprtor omposton. In vw o rnt ppltons, ts omposton s promsn tool. A sprtor s st o vrts (o onnt rp), t rmovl o w sonnts t rp, n lqu s st o prws nt vrts, n o ours lqu sprtor s sprtor w s lqu. Clqu mnml sprtor omposton s pross w rs up n unrt rp nto st o surps y opyn t lqu mnml sprtors nto t onnt omponnts ty n, s wll xpln n tl urtr. Hstorlly, lqu sprtor omposton ws stu y rp torsts us som r rp prolms su s vrtx olorn, mxmum lqu n tstn or prton n solv y Dv-n-Conqur ppro y rst solvn tm on t surps n y lqu sprtor omposton, n tn mrn t otn rsults.
2 Alortms 2010, Tr r two mn rws to ts omposton: Frst, not vry rp s lqu sprtor. Son, t surps otn r not sont, w mns tt t ovrlp s lr, lttl s to n y Dv-n-Conqur ppro. Howvr, rnt rsr s molz t y rps (su s txt mnn t [1], op t [2], or ny t rprsnt y symmtr postv mtrx su s stn t). In tos rps, lqu s otn n mportnt lous, sn t rlts mxmum ntrton twn ts lmnts. Ts rps lmost lwys v lqu sprtors. But n ny s, wn ts rps r otn y oosn trsol n stn mtrx, on n oos trsol w ns rp w ontns sunt numr o lqu sprtors. T t tt t surps otn ovrlp n srl proprty n ppltons. For xmpl, wn srn or lustrs o ns, t s n to l to llow n to ntrt wt rnt n roups, w s not t s wt lssl n lustrn. T tory o lqu omposton n lqu mnml sprtor omposton s n stu y svrl utors. T mtmtl nssry to prov t rsults w prsnt r s somwt omplt, n t rsults r strut twn vrous pprs, w s on o t rsons or w ts rp omposton s not s wll-nown s t oul. W wll sr t nown rsults (wl tn t orrsponn rrn pprs wn possl). W lso vot ston to vn t proo (or t lst st o proo) o t mn rsults w us. Our m n ts ppr s to xpln ts omposton s smply s possl; t s pross s not ult to unrstn, n t s not ult to mplmnt. Howvr, t os nvolv som not so sy rp notons su s mnml sprton. W v ornz t rsults so tt rp torsts wll n t tortl roun, n so tt sntsts rom otr rs n us n mplmnt ts omposton, y vn xmpls n xplnn t mplmnttons. T ppr s ornz s ollows: Ston 2 vs som nrl rp notons, som prtulrs on mnml sprton n mnml trnulton. Ston 3 provs prs nton o lqu mnml sprtor omposton, s wll s xmpls; w lso suss ow to n t lqu mnml sprtors o rp ntly, n v som proprts o ts omposton. Ston 4 vs n nt pross or omputn t lqu mnml sprtor omposton o rp. Ston 5 provs r story o lqu omposton, wt t lorp roun s wll s -lvl proos o t rsults w prsnt n ts ppr. W onlu n Ston 6.
3 Alortms 2010, Grp Notons 2.1. Gnrl notons All rps n ts wor r unrt n nt. A rp G = (V, E) s st V o vrts, V = n, n st E o s w r prs o stnt vrts, E = m; n {x, y} s not xy. T omplmnt G = (V, E) o rp G = (V, E) s t rp wr, or ny pr o vrts {x, y}, x y, xy E n only xy E. I X V s st o vrts o G = (V, E), G(X) nots t surp nu y X (w s rp wos vrts r t lmnts o X n su tt xy s n o G(X) x, y X n xy E). Noroos: T noroo o vrtx x n G s N G (x) = {y x xy E}; w omt susrpt G wn t s lr rom t ontxt w rp w wor on. T xtn noroo o vrtx x s N G [x] = N G (x) {x}. W sy tt vrts x n y r nt n only xy E. T noroo o st o vrts A s N G (A) = x A N G (x) A, n ts xtn noroo s N G [A] = N G (A) A. Pts n yls: A pt s squn (x 1, x 2,..., x ) o rnt vrts su tt or <, x s nt to x +1. A or n pt s n x x wr > n +1. A pt s orlss t s no or. A yl s los pt,.., squn x 1, x 2,..., x, x 1 o vrts, wt x 1, x 2,..., x ll rnt, su tt or <, x s nt to x +1 n x s nt to x 1. A orlss yl s yl wt no or. A orlss yl wt 5 or mor vrts s ll ol, t omplmnt o su yl s ll n ntol. Connxty: A rp s onnt tr s pt onntn ny pr o vrts, sonnt otrws ; wn t rp s sonnt, t mxml onnt surps r ll t onnt omponnts o t rp. Clqus: A lqu s st o vrts w r prws nt. An npnnt st s st o vrts wt no s. Prton: A rp s prt t ontns no nu ol or ntol wt n o numr o vrts. Exmpl 2.1 In Fur 1, (,,, ) s orlss yl o lnt 4, {,,, } s lqu, N() = {,,, }, N({, }) = {, }. Fur 1. Grp G, our runnn xmpl.
4 Alortms 2010, Mnml sprton, orl rps, n mnml trnulton Dnton 2.2 A sust S o vrts o onnt rp G s ll sprtor (or somtms utst) G(V S) s not onnt. A sprtor S s ll n -sprtor n l n rnt onnt omponnts o G(V S), mnml -sprtor S s n -sprtor n no propr sust o S s n -sprtor. A sprtor S s mnml sprtor, tr s som pr {, } su tt S s mnml -sprtor. Altrntly, S s mnml sprtor n only G(V S) s t lst 2 onnt omponnts C 1 n C 2 su tt N(C 1 ) = N(C 2 ) = S; su omponnts r ll ull omponnts o S n G. S s mnml xy-sprtor or ny {x, y} wt x C 1 n y C 2. A onnt rp wt no mnml sprtor s lqu. Wn t rp s not onnt, t st o mnml sprtors s t unon o t sts o mnml sprtors o t onnt omponnts. Exmpl 2.3 Lt us llustrt ts notons on tr: tr s two ns o vrts: lvs n rtulton nos (w r ts mnml sprtors). Fur 2 sows ow rmovn rtulton no {} sonnts t rp nto svrl onnt omponnts; {} s -sprtor, s n l n two rnt omponnts. Fur 2. {} s -sprtor. Exmpl 2.4 On t mor omplx rp G o Fur 1: {,,, } s sprtor, ut t s not mnml. {,, } s mnml sprtor, wt ull omponnts {,, } n {,, }. {, } s lso mnml sprtor, wt ull omponnts {, } n {,,,,,, }. Not tt mnml sprtor {, } s nlu n mnml sprtor {,, }. Not tt n n rtrry rp, tr n n xponntl numr o mnml sprtors (O(2 n )). Fur 3 sows n xmpl o ts.
5 Alortms 2010, Fur 3. Ts rp s n xponntl numr o mnml sprtors, w r t omntons rom t Crtsn prout { 1, 1 } { 2, 2 }... { n, n } n n Corl rps: A rp s orl t s no orlss yl o lnt strtly rtr tn 3; orl rps r xtnsons o trs n v mny smlr proprts. Dr [3] ornlly n t onpt o mnml sprtor n orr to rtrz orl rps, y sown tt rp G s orl n only vry mnml sprtor o G s lqu. In orl rp, tr r lss tn n mnml sprtors [4]. Fur 4 sows orl rp H. Fur 4. Corl rp H, wt mnml sprtors: {, }, {, }, {,, }, {, }, {, }, {, }. Prt lmnton orrns: Anotr ntrstn rtrzton o orl rps s tt ty v smpll orrn on t vrts: vrtx s s to smpll ts noroo s lqu. A rp s orl n only on n rptly n smpll vrtx, n rmov t, untl no vrtx s lt. Sn t stp vrtx s rmov, ts ns srs o trnstory rps: t stp + 1, t trnstory rp s nput rp G rom w t rst vrts v n rmov. Ts pross s ll smpll lmnton sm, n ns n orrn on t vrts ll prt lmnton orrn (po). E mnml sprtor o orl rp H s t noroo o vrtx n t trnstory rp n t smpll lmnton sm [4]. W wll sy tt su vrtx nrts mnml sprtor o H (w.r.t. vn po o H):
6 Alortms 2010, Dnton 2.5 Lt H = (V, E) orl rp, lt α prt lmnton orrn o H. W sy tt vrtx x o numr y α nrts mnml sprtor S w.r.t α S s qul to t st o nors o x o r numr. Tus, to omput t st o mnml sprtors o H, t s sunt to omput po α o H n to slt t vrts tt nrt mnml sprtor o H w.r.t. α. Ts s sy to ompls wt spl n o po n y lortms su s MCS [5], n wll us or our mplmntton n Ston 4. Mnml trnultons: A trnulton s orl omplton o rp: st F o s (ll t ll s)s to t rp n orr to otn orl rp. Dnton 2.6 Lt G = (V, E) rp. A orl rp H = (V, E + F ) s ll trnulton o G, n F s ll t ll. T trnulton s s to : mnml or no propr sust F o F, H = (V, E + F ) s orl. mnmum no otr mnml trnulton s lss ll s. Exmpl 2.7 Grp H rom Fur 4 s mnml trnulton o Grp G rom Fur 1 (s Fur 5). Fur 5. H s mnml trnulton o G. T ll s r rprsnt y ott lns. Computn mnmum trnulton s NP omplt [6], ut omputn mnml trnulton n on n O(nm) tm (or lttl lss or ns rps [7,8]). Ts prolm s vn rs to svrl rnt pprs, so tr r now mny mnml trnulton lortms (s.. [9 12]). W wll us on o tm (MCS-M) n Ston 4 wr w sr n mplmntton. Mnml lmnton orrns: On wy to omput trnulton o rp G = (V, E) s to or t rp nto vn prt lmnton orrn: n n orrn α on V, rptly p t nxt vrtx y α, ny s mssn n ts noroo (n t surp nu y t not yt rmov vrts), n rmov t, untl no vrtx s lt. Ts wll yl trnulton G + α = (V, E + F ) wos ll F s t st o ll s n ts pross.
7 Alortms 2010, An orrn α on t st o vrts o G s mnml lmnton orrn (mo) o G t trnulton G + α o G otn s mnml trnulton o G. Alortm LEX M [13] ws vs to omput n mo. In Ston 4, w wll us smplr vrson o LEX M, MCS-M [9]. Bot ts lortms yl mnml trnulton H o t nput rp G n n orrn α tt s ot mo o G n po o H, n ms t sy to omput t st o vrts nrtn t mnml sprtors o H. 3. Dnn lqu mnml sprtor omposton 3.1. Dntons n xmpls T omposton y lqu mnml sprtors n n y t ollown lortm pross on nput rp G: n ollton o surps (w t t nnn ontns only G) y rptly pplyn t ollown omposton stp on surp w s lqu mnml sprtor, untl non o t surps s lqu mnml sprtor. Domposton Stp 3.1 Gvn rp G, n lqu mnml sprtor S o G n ull omponnt C o S; rpl G wt t ollown 2 surps: G 1 = G (S C), G 2 = G (V C). T omposton s t st o surps otn n t n, w r ll toms. T omposton s unqu, t rsultn st o toms os not pn o t orr n w t omposton stps r xut. Ts s us o t ollown proprty o lqu mnml sprtor omposton: Proprty 3.2 Lt S t st o mnml sprtors o rp G, lt S lqu mnml sprtor o G ; tr pplton o on omposton Stp 3.1, otr mnml sprtor s mnml sprtor o tr G 1 or o G 2. Tus n prtulr, ny lqu mnml sprtor wll lqu mnml sprtor o G 1 or o G 2. Not tt t lqu mnml sprtor w ws us, S, my or my not stll mnml sprtor o G 2, pnn on wtr S mor tn two or only two ull omponnts. T toms otn r rtrz s ollows: Crtrzton 3.3 An tom o rp G s mxml onnt surp ontnn no lqu mnml sprtor. Exmpl 3.4 Fur 6 vs t omposton o tr. On ny orl rp, ts omposton yls t st o mxml lqus o t nput rp. In non-orl rp, som o t toms wll not lqus. Lt us us our rp G rom Fur 1 s n xmpl: T lqu mnml sprtors o G r: {, }, {,}, {,, }. Fur 7 sows omposton tr n t st o toms.
8 Alortms 2010, Fur 6. () A omposton stp usn mnml sprtor {}. T mnml sprtors (xpt or {}) r prtton nto t two sutrs otn. () Totl omposton. () () 3.2. Proprts o t toms T numr o toms s t most n. T ntrston twn toms s lwys lqu (w my mpty), n t s not nssrly mnml sprtor (vn wn t s not mpty). Exmpl 3.5 In our xmpl rom Fur 7, tom {,,, } tom {,,, } = {, }, w s not mnml sprtor; tom {,,, } tom {,,, } = {, }, mnml sprtor An quvlnt pross Anotr wy o on t omposton s usn lqu mnml sprtor S n opyn t n ll t omponnts t ns. For omponnt C w s not ull omponnt, w n to opy only t noroo o C. Ts orrspons to lqu mnml sprtor w s proprly nlu n S. T proprty w us s t ollown: Proprty 3.6 Lt S mnml sprtor, lt (C ) onnt omponnts o G(V S). Tn, N G (C ) s mnml sprtor o G.
9 Alortms 2010, Fur 7. A omposton tr or rp G rom Fur 1 n t st o toms o G. S={,} G({,,,}) G({,,,,,,,,}) G({,,,}) G({,,,,,,}) S={,,} G({,,,}) () Domposton tr G({,,,,,}) () St o toms Ts ls to t ollown omposton stp: Domposton Stp 3.7 Gvn rp G wt lqu mnml sprtor S, lt C 1,..., C t onnt omponnts o G (V S). Rpl G wt t surps G (C N G (C )). Atr su omposton stp usn lqu mnml sprtor S, S n t lqu mnml sprtors susts o S n no lonr mnml sprtor n ny o t surps otn, n ll t otr mnml sprtors o G r prtton nto t surps otn. Exmpl 3.8 Fur 8 sows omposton stp n rp G rom Fur 1 usn Domposton Stp 3.7. An pplton o Domposton Stp 3.7 orrspons to svrl ppltons o Domposton Stp How to omput t lqu mnml sprtors To our nowl, t only nt nown wy to omput t lqu mnml sprtors o rp s to xtrt tm rom mnml trnulton.
10 Alortms 2010, Fur 8. A omposton o G usn Domposton Stp 3.7. S={,,} G({,,,,,}) S={,} G({,,,}) G({,,,,,}) G({,,,}) G({,,,}) Ts mto s s on t ollown proprty: Proprty 3.9 Lt G = (V, E) rp, lt H = (V, E + F ) mnml trnulton o G. T lqu mnml sprtors o G r xtly t mnml sprtors o H tt r lqus n G. Tus n orr to n t lqu mnml sprtors o rp, t nrl pross s s ollows: omput mnml trnulton H o G. omput t mnml sprtors o H. mnml sprtor o H to s wtr t s lqu n G. Computn t mnml sprtors o mnml trnulton o rp n on ntly usn n orrn prov y sr lortm su s MCS-M, n Stps 1 n 2 n mr, s w wll s n Ston 4. Exmpl 3.10 Grp H rom Fur 4 s mnml trnulton o Grp G rom Fur 1. T mnml sprtors o H r: {, }, {, }, {,, }, {, }, {, }, {, }. Tr o tm r lqus n G: {, }, {,, }, {, }, so ty r lqu mnml sprtors o G Som prolms w n solv usn t toms Mnml n mnmum trnulton: mnml trnulton s omput or o t toms o t lqu mnml sprtor omposton o rp, tn t unon o t st o ll s otn ns mnml trnulton or G. Tus or tom mnmum-sz ll s omput, t rsultn ll wll mnmum trnulton o G, sn t sts o ll s n t toms r prws sont. Trwt: t trwt s otn y tn t lrst trwt ovr ll t toms. Prton: Any orlss yl o lnt 4 or mor s prsrv y omposton stp, s wll s ny ntol, so ts omposton prsrvs ols n ntols. Tus rp s prt n only ll ts toms r prt. Colorn: An optml olorn s otn y mrn optml olorns o t toms.
11 Alortms 2010, Mxmum lqu: Any mxml lqu o t rp s prsrv tr omposton stp, so nn t sz o t lrst lqu o tom wll yl t sz o t lrst lqu o t ornl rp. 4. Alortms n mplmnttons Tr r svrl wys o omputn t omposton o rp nto toms. T smplst s to mplmnt Domposton Stp 3.1. W wll us Alortm MCS-M [9], sr lortm w omputs mnml trnulton H = (V, E + F ) o t nput rp G = (V, E), rprsnt y st F o ll s, s wll s n orrn α o t vrts. MCS-M numrs t vrts rom n to 1, n t orrn α otn s mo o t nput rp G n po o t mnml trnulton H w s omput [14]. On ts orrn n ts trnulton r omput, w wll us tm n son lortm, (Alortm Atoms), w wll nrt t toms y snnn t vrts rom 1 to n. W wll strt y vn t nrl MCS-M lortm, tn n xpn vrson, w w ll MCS-M+, s wll xpln trwrs, n nlly v t lortm w yls t toms. G wll t trnstory surp o G nu y t st o stll unnumr vrts. Alortm MCS-M nput : An unrt rp G = (V, E). output: A mnml lmnton orrn α on V n mnml trnulton H = (V, E + F ) o G. nt: F ; G G; Intlz t lls o ll vrts s 0 ; or =n ownto 1 o Coos vrtx x o G o mxml ll ; Y N G (x) ; or vrtx y o G not lonn to N G [x] o tr s pt rom x to y n G su tt vry ntrnl vrtx on t pt s ll strtly smllr tn ll(y) tn Y Y + {y}; or y n Y o F F + {xy}; ll(y) ll(y) + 1 ; α() x ; Rmov x rom G ; H (V, E + F ); W wll now xpn ts lortm n two wys. Frst, w wll mplmnt tr s pt rom x to y n G su tt vry ntrnl vrtx on t pt s ll strtly smllr tn ll(y). W o ts n smlr wy s n t mplmntton o LEX M vn n [13] y snl sr n G. For ll vlu, st r() ontns t r vrts vn ll, s wll s t vrts vn ll strtly smllr tn r rom vrtx vn ll. Son, w wll omput t st X o vrts tt nrt t mnml sprtors o t trnulton H, s sr n [5]. T n ts s tt s lon s t lls o t osn
12 Alortms 2010, vrts p ttn lrr, w r ns lqu o H; wn sunly t ll o t osn vrtx x stops ttn lrr, x nrts mnml sprtor o H. E su vrtx x s to st X. Alortm MCS-M+ nput : An unrt rp G = (V, E). output: A mnml lmnton orrn α on V, mnml trnulton H = (V, E + F ) o G, n t st X o vrts w nrt mnml sprtor o H. nt: F ; G G ; Intlz t lls o ll vrts s 0 ; s 1 ; X ; or =n ownto 1 o Coos vrtx x o G o mxml ll ; Y N G (x) ; ll(x) s tn X X + {x} ; s ll(x) ; Mr x r n mr ll otr vrts o G unr ; or =0 to n 1 o r() or y n N G (x) o Mr y r; A y to r(ll(y)); or =0 to n 1 o wl r() o Rmov vrtx y rom r() ; or z n N G (y) o z s unr tn Mr z r; ll(z) > tn Y Y + {z}; A z to r(ll(z)); ls A z to r(); or y n Y o F F + {xy}; ll(y) ll(y) + 1 ; α() x ; Rmov x rom G ; H (V, E + F ). On w v otn n MCS-M orrn α, s wll s t orrsponn mnml trnulton H o G n t st X o nrtors o t mnml sprtors o H, w run trou t vrts rom 1 to n. W us t trnstory surps G n H o G n H, ntlz s G n H, rsptvly. At stp prossn vrtx x = α(), w wtr x s n t st X. I t s, t noroo N H (x) o x n H s mnml sprtor o H; w wtr t s lqu n G. I t s, tn S s lqu mnml sprtor o G. In tt s w omput t onnt omponnt C o G(V S)
13 Alortms 2010, w ontns x; G (S C) s n tom [15], n s stor s su; C s tn rmov rom G. In ny s, w tn rmov x rom H. Alortm Atoms nput : A rp G = (V, E), mo α o G, t orrsponn mnml trnulton H = (V, E + F ) o G, t st X o vrts tt nrt mnml sprtor o H. output: T st A o toms o G, t st S H o mnml sprtors o H, t st S o lqu mnml sprtors o G. G G ; H H ; A ; S H ; S ; or =1 to n o x α() ; x X tn S N H (x) ; S H S H {S} ; S s lqu n G tn S S {S}; C t onnt omponnt o G S ontnn x ; A A + {G (S C)}; G G C ; Rmov x rom H ; A A + {G }. 5. Tortl n lorpl roun 5.1. A r story o lqu mnml sprtor omposton In 1976, Gvrl [16] sr t lss o lqu sprl rps n t ontxt o solvn n polynoml tm t r prolms o mnmum olorn n mxmum lqu. In 1980, t prolm o nn lqu sprtor n n rtrry rp ws rss y Wtss [17], wo prsnt n O(n 3 ) lortm to n on lqu sprtor. In 1983, Trn [15] rss t prolm o nn omposton o n rtrry rp usn ts lqu sprtors. H not tt usn Wtss lortm, ts woul rqur O(nm 3 ) tm. H propos n O(nm) tm lortm to o ts, y sown tt no ll o mnml trnulton n on two onnt omponnts n y lqu sprtor. Computn n mo rqur O(nm) tm, s sow n [13] (1976), n prov tt usn n mo, lqu sprtor omposton n omput n O(nm) tm. Trn lt opn t quston o nn unqu lqu sprtor omposton. In 1990, Dlus, Krpnsy n Nov [18] propos prlll lortm or lqu sprtor omposton. In 1990, onurrntly, Lmr [19], n ppr snt out or pulton n 1986, sr n vry mtmtl tl ow to otn n optml n unqu omposton usn t lqu mnml sprtors o t rp. Lmr lso sr ow to us LEX M (lso ll t RTL lortm) to n lqu mnml sprtor omposton n O(nm) tm. In 2001, Olsn n Msn [20] ppl lqu mnml sprtor omposton to Bysn ntwors, n prsnt n ppro s on t lqu tr o mnml trnulton to omput
14 Alortms 2010, t toms (w ty ll mxml prm surps) y mrn n t lqu tr ny two nos onnt y n w rprsnts non-lqu mnml sprtor (t rr s rrr to [21] or ull tls on lqu trs) Computn t lqu mnml sprtors o rp W rst prov tt or ny rp G n ny mnml trnulton H o G, t lqu mnml sprtors o G r xtly t mnml sprtors o H tt r lqus n G (proprty 3.9). For ts, t s sunt to sow tt ny lqu o G s t sm numr o ull omponnts n G s n H. Ts ollows rom t ollown proprty, w s n xtnson o Lmm 1 rom [15]. Proprty 5.1 Lt G = (V, E) rp, lt H = (V, E + F ) mnml trnulton o G n lt S lqu o G. Tn G(V S) n H(V S) v t sm onnt omponnts, wt t sm noroos. Proo: Lt H t rp n y H = (V, E + F ), wr F s t st o s n F tt r ontn n N G [C] or som onnt omponnt C o G(V S). By nton o H, G(V S) n H (V S) v t sm onnt omponnts, wt t sm noroos. Lt us sow tt H s orl. Lt µ yl n H o lnt rtr tn 3, n lt us sow tt µ s or n H. As H s orl, µ s or, sy xy, n H. I xy s n H tn t s or o µ n H. Otrws tr s onnt omponnt C o G(V S) su tt x s n C n y s n V N G [C], or onvrsly. Hn tr r two non-onsutv vrts w n z o µ tt r ot n N G (C), n tror ot n lqu S o H. It ollows tt wz s or o µ n H, w omplts t proo tt H s orl. As G H H, wt H orl n H mnml trnulton o G, H = H, n tror G(V S) n H(V S) v t sm onnt omponnts, wt t sm noroos. Corollry 5.2 (Proprty 3.9) Lt G = (V, E) rp, lt H = (V, E+F ) mnml trnulton o G. T lqu mnml sprtors o G r xtly t mnml sprtors o H tt r lqus n G. T t tt mnml sprtor o orl rp H s nrt y vrtx o H w.r.t. po o H [4] s wll-nown. A wy o sltn t xt vrts tt nrt mnml sprtor s suss n [5]. T ollown lortm s s on t xpn vrson o MCS prsnt n [21] to nrt t mxml lqus n lqu tr. Ts pross s ntrt n t mplmntton vn n Ston 4.
15 Alortms 2010, Alortm MCS-Mnsps nput : A orl rp H = (V, E). output: T st S o mnml sprtors o H. nt: V NUM ; H NUM H(V NUM ); H ELIM H; S ; Intlz t lls o ll vrts s 0 ; s 1 ; or =n ownto 1 o Coos vrtx x o H ELIM o mxmum ll ; V NUM V NUM + {x}; H NUM H(V NUM ); ll(x) s tn S S {N HNUM (x)} ; s ll(x) ; or y N HELIM (x) o ll(y) ll(y) + 1; Rmov x rom H ELIM ; 5.3. Domposn rp nto toms Domposton Stp 3.1 n Alortm Atoms o Ston 4 r lrly nspr rom t omposton o rp y lqu sprtors sr y Trn [15]. Trn onsrs lqu sprtors nst o lqu mnml sprtors, wt t rw tt t st o toms otn s not unqu (s Suston 5.4). H lso omputs mo o G n t orrsponn mnml trnulton o G, ut slts t vrts tt nrt lqu sprtor nst o lqu mnml sprtor o G. T proo o t lqu sprtor omposton lortm vn n [15] n sly mo nto proo o Alortm Atoms. W wll v n o ts proo. Torm 5.3 Alortm Atoms omputs lqu mnml sprtor omposton o nput rp G. Proo: ( o t proo) T proo wors y nuton on = X, wr X s t st o vrts o X tt nrt lqu o G w.r.t. α,.., t st o vrts o G tt nrt lqu mnml sprtor o G w.r.t. α. I = 0 tn t omput omposton s {G}, w s orrt sn G s no lqu mnml sprtor. W suppos tt t omposton s orrt X. Lt us sow tt t s stll orrt X = + 1. Lt x t rst vrtx o X n orrn α, lt S t lqu mnml sprtor o G nrt y x w.r.t. α, lt C t onnt omponnt o G(V S) ontnn x, lt G 1 = G(S C) n G 2 = G(V C). For n {1, 2}, lt V t vrtx st o G, lt α t rstrton o α to V, lt H = H(V ) n X = X V. It n sown tt or n {1, 2}, α s mo o G, wt H s orrsponn mnml trnulton o G. Morovr, vrtx o V 2 nrts t sm st n G 2 w.r.t. α 2 s n G w.r.t. α, w s mnml sprtor o H 2 n only t s mnml sprtor o H. Hn X 2 s xtly t st o vrts o G 2 tt nrt lqu mnml sprtor o G 2 w.r.t. α 2, wt X 2 sn X 2 X {x}. It ollows y nuton ypotss tt G 2 s orrtly ompos. It rmns to sow tt G 1 s n tom o G. It n sown tt vrtx o C {x} prs x n orrn α, n nrts t sm st n G 1 w.r.t. α 1 s n G w.r.t. α, w s mnml sprtor o H 1 n only t s mnml sprtor o H. As no vrtx o C {x} nrts
16 Alortms 2010, lqu mnml sprtor o G w.r.t. α (sn x s t rst vrtx tt os), no vrtx o C {x} nrts lqu mnml sprtor o G 1 w.r.t. α 1 tr. Now vrtx o S {x} nrts sust o S, w s not sprtor o G 1, w.r.t. α 1. Hn G 1 s no lqu mnml sprtor, n s tror n tom o G T unty o lqu mnml sprtor omposton Trn [15] ornlly n t omposton stp o rp y lqu sprtor s ollows: Domposton Stp 5.4 Lt S lqu sprtor o G = (V, E ), lt (S, A, B) prtton o V su tt no vrtx n A s nt to vrtx n B. Rpl G y G 1 = G (S A) n G 2 = G (S B). H rmr tt t st o toms otn y rptly pplyn ts omposton stp s not unqu, vn ountrxmpl tt s rll n Fur 9, n lt t prolm o t unty o t omposton opn. Lmr [19] solv ts prolm, sown tt usn lqu mnml sprtors nst o lqu sprtors nsurs unty o t omposton (wt t tonl onton tt on o A n B ontns ull omponnt o S n G n t s o Domposton Stp 5.4). W prsnt som lmnts o t proo o ts rsult, w s ssot n [19] wt proos o mor omplx rsults w m t ult or non-splsts to ollow. W rst rll som ntons vn n [19]. Fur 9. A rp wt rnt ompostons y lqu sprtors. () Grp. () On omposton, w s t unqu omposton y lqu mnml sprtors. () Anotr omposton. {,} {,,} {,,,} {,,} {,,,} {,} () () () {,,} {,,} Dnton 5.5 A rp s prm t s onnt n s no lqu sprtor (or quvlntly, no lqu mnml sprtor). A mp-surp o rp G s mxml prm surp o G. Lmr prov tt t lqu mnml sprtor omposton o rp G s t st o mp-surps o G (Crtrzton 3.3). T proo o ts rtrzton rls on t ollown proprty. Proprty 5.6 Lt G = (V, E) rp, lt S lqu o G vn t lst on ull omponnt n G. Tn tr s sust A o V su tt S A n G(A) s prm.
17 Alortms 2010, Proo: ( o t proo) T proprty ols G s orl sn n tt s, s S s lqu o G vn ull omponnt, sy C, n G, tr s vrtx x o C su tt S N G (x) (ts ollows rom t rsults n [4]), n tror S {x} s lqu n nus prm rp. Lt us sow tt t ols or ny rp G. Lt G t rp otn rom G y mn mp-surp o G nto lqu. G s orl n s t sm mp-surps s G [19]. Tr s sust A o V su tt S A n G (A) s prm. Lt B sust o V su tt A B n G (B) s mp-surp o G. Tn S B n G(B) s prm. H lso sow t ollown rtrzton, w s Crtrzton 3.3: Crtrzton 5.7 T lqu mnml sprtor omposton o rp G s t st o mp-surps o G. Proo: W suppos tt t omposton stp w s us s Domposton Stp 5.4 wt t tonl onton tt on o A n B ontns ull omponnt o S n G, w s mor nrl tn Domposton Stp 3.1. T proo os y nuton on t numr n o vrts o t rp. T proprty trvlly ols n = 1. Suppos tt t ols or ny rp wt t most n vrts. Lt us sow tt t ols or rp G = (V, E) wt n + 1 vrts. T proprty trvlly ols G s no lqu mnml sprtor. W suppos tt G s lqu mnml sprtor S. Lt (S, A, B) prtton o V su tt no vrtx n A s nt to vrtx n B n on o A n B ontns ull omponnt o S n G. Lt G 1 = G(S A) n G 2 = G(S B). Lt us sow tt t st toms(g) o toms otn y rpln G y G 1 n G 2 n urtr omposn G 1 n G 2 s qul to t st mp-surps(g) o mp-surps o G. Clrly tom(g) = toms(g 1 ) toms(g 2 ). As y nuton ypotss toms(g 1 ) = mp-surps(g 1 ) n toms(g 2 ) = mp-surps(g 2 ), t s sunt to sow tt mp-surps(g) = mp-surps(g 1 ) mp-surps(g 2 ). Lt us rst sow tt mp-surps(g) mp-surps(g 1 ) mp-surps(g 2 ). Lt G(M) n mp-surps(g). Tn M S A or M S B (otrws M S woul lqu sprtor o G(M)) n tror G(M) mp-surps(g 1 ) mp-surps(g 2 ). Lt us sow now tt mp-surps(g 1 ) mp-surps(g 2 ) mp-surps(g). Lt G(M) mp-surps(g 1 ) mp-surps(g 2 ), sy G(M) mp-surps(g 1 ). By Proprty 5.6, s A ontns ull omponnt o S n G, no sust o S nus mp-surp o G 1. Hn M A. Lt G(M ) mp-surp o G wt M M. As mp-surps(g) mp-surps(g 1 ) mp-surps(g 2 ), G(M ) mp-surps(g 1 ) mp-surps(g 2 ), n s M A (sn M A n M M ), G(M ) mp-surps(g 1 ). As G(M) n G(M ) r ot mp-surps o G 1 wt M M, M = M. Hn G(M) mp-surps(g). It ollows tt mp-surps(g) = mp-surps(g 1 ) mp-surps(g 2 ), w omplts t proo y nuton. Corollry 5.8 T omposton y lqu mnml sprtors s unqu.
18 Alortms 2010, Conlusons Clqu mnml sprtor omposton s smpl to mplmnt n prtulrly wll-sut to ppltons nvolvn rps osn rom stn mtrx. Tou t tortl roun s somwt omplt, t s not nssry to mstr t n orr to us ts omposton. Clqu mnmum sprtor omposton s lso n us rntly s tool to solv t mxmum wt stl st prolm or spl rps lsss [22], n s n ppl to trwt y usn sprtors w r lqus or lmost lqus [23]. On o t promsn spts o ts omposton s tt on trsol s osn, t lustrs w r orm s toms o t orrsponn rp r unquly n, pnn solly on t strutur o t t. Rrn rp vsulzton, t st o toms n ornz nto mt-rp wr t vrts r t toms. For nstn [2], tr n n twn two toms wn tr ntrston s lqu mnml sprtor. Ts yls mor lol vw o t rp, wl splyn som o ts struturl proprts. Rrns 1. D B, M.; K, B.; Murs, M.J.; SnJun, E. Grp omposton ppros or trmnoloy rps. Pro. MICAI 2007, K, B.; Pnt, N.; Llns, G.; Syrt, A.; Brry, A. Clustrn n xprsson t usn rp sprtors. In Slo Bol. 2007, 7, Dr, G.A. On r rut rps. A. Mt. Sm. Unv. Hmur 1961, 25, Ros, D.J. Trnult rps n t lmnton pross. J. Mt. Anl. Appl. 1970, 32, Brry A.; Poorln, R. A smpl lortm to nrt t mnml sprtors o orl rp. Rsr Rport LIMOS RR LIMOS UMR CNRS: Auèr, Frn, Ynns, M. Computn t mnmum ll-n s NP-omplt. SIAM J. Alr. Dsrt Mto 1981, 2, Krts, D.; Spnr, J. Mnml ll n O(n 2.69 ) tm. Dsrt Mt. 2006, 306, Hrns, P.; Tll, J.A.; Vllnr, Y. Computn mnml trnultons n tm O(n α lon) = o(n ). SIAM J. Dsrt Mt. 2005, 19, Brry, A.; Blr, J.R.S.; Hrns, P. Mxmum rnlty sr or omputn mnml trnultons o rps. Alortm 2004, 39, Brry, A.; Bort, J.P.; Hrns, P.; Smont, G.; Vllnr, Y. A w-rn lortm or mnml trnulton rom n rtrry orrn. J. Alor. 2006, 58, Brry, A.; Hrns, P.; Vllnr, Y. A vrtx nrmntl ppro or mntnn orlty. Dsrt Mt. 2006, 306, Hrns, P. Mnml trnultons o rps: A survy. Dsrt Mt. 2006, 306, Ros, D.J.; Trn, R.E.; Lur, G.S. Alortm spts o vrtx lmnton on rps. SIAM J. Comput. 1976, 5,
19 Alortms 2010, Brry, A.; Krur, R.; Smont, G. Mxml ll sr lortms to omput prt n mnml lmnton orrns. SIAM J. Dsrt Mt., , Trn, R.E. Domposton y lqu sprtors. Dsrt Mt. 1985, 55, Gvrl, F. Alortms on lqu sprl rps. Dsrt Mt. 1977, 19, Wtss, S. An lortm or nn lqu utsts. In. Pross. Ltt. 1981, 12, Dlus, E.; Krpns, M.; Nov, M.B. Fst prlll lortms or t lqu sprtor omposton. In Prons o t Frst Annul ACM-SIAM Symposum on Dsrt Alortms: SODA 90, Pllp, PA, USA, Jnury 1990; pp Lmr, H.G. Optml omposton y lqu sprtors. Dsrt Mt. 1993, 113, Olsn, K.G.; Msn, A.L. Mxml prm surp omposton o Bysn ntwors. IEEE Trns. Syst. Mn Cyrnt. B 2002, 32, Blr, J.R.S.; Pyton, B.W. An ntrouton to orl rps n lqu trs. Grp Tory Sprs Mtrx Comput. 1993, 84, Brnstät, A.; Hoàn, C.T. On lqu sprtors, nrly orl rps, n t Mxmum Wt Stl St Prolm. Tor. Comput. S. 2007, 389, Bolnr, H.L.; Kostr, A.M.C.A. S sprtors or trwt. Dsrt Mt. 2006, 306, y t utors; lns MDPI, Bsl, Swtzrln. Ts rtl s n Opn Ass rtl strut unr t trms n ontons o t Crtv Commons Attruton lns ttp://rtvommons.or/lnss/y/3.0/.
The University of Sydney MATH 2009
T Unvrsty o Syny MATH 2009 APH THEOY Tutorl 7 Solutons 2004 1. Lt t sonnt plnr rp sown. Drw ts ul, n t ul o t ul ( ). Sow tt s sonnt plnr rp, tn s onnt. Du tt ( ) s not somorp to. ( ) A onnt rp s on n
More informationLecture 20: Minimum Spanning Trees (CLRS 23)
Ltur 0: Mnmum Spnnn Trs (CLRS 3) Jun, 00 Grps Lst tm w n (wt) rps (unrt/rt) n ntrou s rp voulry (vrtx,, r, pt, onnt omponnts,... ) W lso suss jny lst n jny mtrx rprsntton W wll us jny lst rprsntton unlss
More informationWeighted Graphs. Weighted graphs may be either directed or undirected.
1 In mny ppltons, o rp s n ssot numrl vlu, ll wt. Usully, t wts r nonntv ntrs. Wt rps my tr rt or unrt. T wt o n s otn rrr to s t "ost" o t. In ppltons, t wt my msur o t lnt o rout, t pty o ln, t nry rqur
More informationMinimum Spanning Trees (CLRS 23)
Mnmum Spnnn Trs (CLRS 3) T prolm Rll t nton o spnnn tr: Gvn onnt, unrt rp G = (V, E), sust o s o G su tt ty onnt ll vrts n G n orm no yls s ll spnnn tr (ST) o G. Any unrt, onnt rp s spnnn tr. Atully, rp
More informationSpanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1
Spnnn Trs BFS, DFS spnnn tr Mnmum spnnn tr Mr 28, 2018 Cn Hrn / Gory Tn 1 Dpt-rst sr Vsts vrts lon snl pt s r s t n o, n tn ktrks to t rst junton n rsums own notr pt Mr 28, 2018 Cn Hrn / Gory Tn 2 Dpt-rst
More informationCMSC 451: Lecture 4 Bridges and 2-Edge Connectivity Thursday, Sep 7, 2017
Rn: Not ovr n or rns. CMSC 451: Ltr 4 Brs n 2-E Conntvty Trsy, Sp 7, 2017 Hr-Orr Grp Conntvty: (T ollown mtrl ppls only to nrt rps!) Lt G = (V, E) n onnt nrt rp. W otn ssm tt or rps r onnt, t somtms t
More informationDepth First Search. Yufei Tao. Department of Computer Science and Engineering Chinese University of Hong Kong
Dprtmnt o Computr Sn n Ennrn Cns Unvrsty o Hon Kon W v lry lrn rt rst sr (BFS). Toy, w wll suss ts sstr vrson : t pt rst sr (DFS) lortm. Our susson wll on n ous on rt rps, us t xtnson to unrt rps s strtorwr.
More information5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees
/1/018 W usully no strns y ssnn -lnt os to ll rtrs n t lpt (or mpl, 8-t on n ASCII). Howvr, rnt rtrs our wt rnt rquns, w n sv mmory n ru trnsmttl tm y usn vrl-lnt non. T s to ssn sortr os to rtrs tt our
More information(Minimum) Spanning Trees
(Mnmum) Spnnn Trs Spnnn trs Kruskl's lortm Novmr 23, 2017 Cn Hrn / Gory Tn 1 Spnnn trs Gvn G = V, E, spnnn tr o G s onnt surp o G wt xtly V 1 s mnml sust o s tt onnts ll t vrts o G G = Spnnn trs Novmr
More informationCMPS 2200 Fall Graphs. Carola Wenk. Slides courtesy of Charles Leiserson with changes and additions by Carola Wenk
CMPS 2200 Fll 2017 Grps Crol Wnk Sls ourtsy o Crls Lsrson wt ns n tons y Crol Wnk 10/23/17 CMPS 2200 Intro. to Alortms 1 Grps Dnton. A rt rp (rp) G = (V, E) s n orr pr onsstn o st V o vrts (snulr: vrtx),
More informationMinimum Spanning Trees (CLRS 23)
Mnmum Spnnn Trs (CLRS 3) T prolm Gvn onnt, unrt rp G = (V, E), sust o s o G su tt ty onnt ll vrts n G n orm no yls s ll spnnn tr (ST) o G. Clm: Any unrt, onnt rp s spnnn tr (n nrl rp my v mny spnnn trs).
More information2 Trees and Their Applications
Trs n Tr Appltons. Proprts o trs.. Crtrzton o trs Dnton. A rp s ll yl (or orst) t ontns no yls. A onnt yl rp s ll tr. Quston. Cn n yl rp v loops or prlll s? Notton. I G = (V, E) s rp n E, tn G wll not
More informationHaving a glimpse of some of the possibilities for solutions of linear systems, we move to methods of finding these solutions. The basic idea we shall
Hvn lps o so o t posslts or solutons o lnr systs, w ov to tos o nn ts solutons. T s w sll us s to try to sply t syst y lntn so o t vrls n so ts qutons. Tus, w rr to t to s lnton. T prry oprton nvolv s
More information4.1 Interval Scheduling. Chapter 4. Greedy Algorithms. Interval Scheduling: Greedy Algorithms. Interval Scheduling. Interval scheduling.
Cptr 4 4 Intrvl Suln Gry Alortms Sls y Kvn Wyn Copyrt 005 Prson-Ason Wsly All rts rsrv Intrvl Suln Intrvl Suln: Gry Alortms Intrvl suln! Jo strts t s n nss t! Two os omptl ty on't ovrlp! Gol: n mxmum sust
More informationTheorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices.
Cptr 11: Trs 11.1 - Introuton to Trs Dnton 1 (Tr). A tr s onnt unrt rp wt no sp ruts. Tor 1. An unrt rp s tr n ony tr s unqu sp pt twn ny two o ts vrts. Dnton 2. A root tr s tr n w on vrtx s n snt s t
More informationLecture II: Minimium Spanning Tree Algorithms
Ltur II: Mnmum Spnnn Tr Alortms Dr Krn T. Hrly Dprtmnt o Computr Sn Unvrsty Coll Cork Aprl 0 KH (/0/) Ltur II: Mnmum Spnnn Tr Alortms Aprl 0 / 5 Mnmum Spnnn Trs Mnmum Spnnn Trs Spnnn Tr tr orm rom rp s
More informationImproving Union. Implementation. Union-by-size Code. Union-by-Size Find Analysis. Path Compression! Improving Find find(e)
POW CSE 36: Dt Struturs Top #10 T Dynm (Equvln) Duo: Unon-y-Sz & Pt Comprsson Wk!! Luk MDowll Summr Qurtr 003 M! ZING Wt s Goo Mz? Mz Construton lortm Gvn: ollton o rooms V Conntons twn t rooms (ntlly
More informationIn which direction do compass needles always align? Why?
AQA Trloy Unt 6.7 Mntsm n Eltromntsm - Hr 1 Complt t p ll: Mnt or s typ o or n t s stronst t t o t mnt. Tr r two typs o mnt pol: n. Wrt wt woul ppn twn t pols n o t mnt ntrtons low: Drw t mnt l lns on
More informationCOMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017
COMP 250 Ltur 29 rp trvrsl Nov. 15/16, 2017 1 Toy Rursv rp trvrsl pt rst Non-rursv rp trvrsl pt rst rt rst 2 Hs up! Tr wr w mstks n t sls or S. 001 or toy s ltur. So you r ollown t ltur rorns n usn ts
More informationThe Constrained Longest Common Subsequence Problem. Rotem.R and Rotem.H
T Constrn Lonst Common Susqun Prolm Rotm.R n Rotm.H Prsntton Outln. LCS Alortm Rmnr Uss o LCS Alortm T CLCS Prolm Introuton Motvton For CLCS Alortm T CLCS Prolm Nïv Alortm T CLCS Alortm A Dynm Prormmn
More informationSingle Source Shortest Paths (with Positive Weights)
Snl Sour Sortst Pts (wt Postv Wts) Yuf To ITEE Unvrsty of Qunslnd In ts ltur, w wll rvst t snl sour sortst pt (SSSP) problm. Rll tt w v lrdy lrnd tt t BFS lortm solvs t problm ffntly wn ll t ds v t sm
More information(4, 2)-choosability of planar graphs with forbidden structures
(4, )-ooslty o plnr rps wt orn struturs Znr Brkkyzy 1 Crstopr Cox Ml Dryko 1 Krstn Honson 1 Mot Kumt 1 Brnr Lký 1, Ky Mssrsmt 1 Kvn Moss 1 Ktln Nowk 1 Kvn F. Plmowsk 1 Drrk Stol 1,4 Dmr 11, 015 Astrt All
More informationDivided. diamonds. Mimic the look of facets in a bracelet that s deceptively deep RIGHT-ANGLE WEAVE. designed by Peggy Brinkman Matteliano
RIGHT-ANGLE WEAVE Dv mons Mm t look o ts n rlt tt s ptvly p sn y Py Brnkmn Mttlno Dv your mons nto trnls o two or our olors. FCT-SCON0216_BNB66 2012 Klm Pulsn Co. Ts mtrl my not rprou n ny orm wtout prmsson
More informationGraph Search (6A) Young Won Lim 5/18/18
Grp Sr (6A) Youn Won Lm Copyrt () 2015 2018 Youn W. Lm. Prmon rnt to opy, trut n/or moy t oumnt unr t trm o t GNU Fr Doumntton Ln, Vron 1.2 or ny ltr vron pul y t Fr Sotwr Founton; wt no Invrnt Ston, no
More information23 Minimum Spanning Trees
3 Mnmum Spnnn Trs Eltron rut sns otn n to mk t pns o svrl omponnts ltrlly quvlnt y wrn tm totr. To ntronnt st o n pns, w n us n rrnmnt o n wrs, onntn two pns. O ll su rrnmnts, t on tt uss t lst mount o
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 informationThe R-Tree. Yufei Tao. ITEE University of Queensland. INFS4205/7205, Uni of Queensland
Yu To ITEE Unvrsty o Qunsln W wll stuy nw strutur ll t R-tr, w n tout o s mult-mnsonl xtnson o t B-tr. T R-tr supports ntly vrty o qurs (s w wll n out ltr n t ours), n s mplmnt n numrous ts systms. Our
More informationExam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms
CS 542 Avn Dt Stutu n Alotm Exm 2 Soluton Jontn Tun 4/2/202. (5 ont) Con n oton on t tton t tutu n w t n t 2 no. Wt t mllt num o no tt t tton t tutu oul ontn. Exln you nw. Sn n mut n you o u t n t, t n
More informationStrongly connected components. Finding strongly-connected components
Stronly onnt omponnts Fnn stronly-onnt omponnts Tylr Moor stronly onnt omponnt s t mxml sust o rp wt rt pt twn ny two vrts SE 3353, SMU, Dlls, TX Ltur 9 Som sls rt y or pt rom Dr. Kvn Wyn. For mor normton
More informationClosed Monochromatic Bishops Tours
Cos Monoromt Bsops Tours Jo DMo Dprtmnt o Mtmts n Sttsts Knnsw Stt Unvrsty, Knnsw, Gor, 0, USA mo@nnsw.u My, 00 Astrt In ss, t sop s unqu s t s o to sn oor on t n wt or. Ts ms os tour n w t sop vsts vry
More informationA Simple Method for Identifying Compelled Edges in DAGs
A Smpl Mto or Intyn Compll Es n DAGs S.K.M. Won n D. Wu Dprtmnt o Computr Sn Unvrsty o Rn Rn Ssktwn Cn S4S 0A2 Eml: {won, nwu}@s.urn. Astrt Intyn ompll s s mportnt n lrnn t strutur (.., t DAG) o Bysn ntwork.
More informationCSE 332. Data Structures and Parallelism
Am Blnk Ltur 20 Wntr 2017 CSE 332 Dt Struturs n Prlllsm CSE 332: Dt Struturs n Prlllsm Grps 1: Wt s Grp? DFS n BFS LnkLsts r to Trs s Trs r to... 1 Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus,
More informationCSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2
Am Blnk Ltur 19 Summr 2015 CSE 332: Dt Astrtons CSE 332 Grps 1: Wt s Grp? DFS n BFS Dt Astrtons LnkLsts r to Trs s Trs r to... 1 A Grp s Tny... 2 Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus, Hps,
More informationPlanar convex hulls (I)
Covx Hu Covxty Gv st P o ots 2D, tr ovx u s t sst ovx oyo tt ots ots o P A oyo P s ovx or y, P, t st s try P. Pr ovx us (I) Coutto Gotry [s 3250] Lur To Bowo Co ovx o-ovx 1 2 3 Covx Hu Covx Hu Covx Hu
More informationCSE 332. Graphs 1: What is a Graph? DFS and BFS. Data Abstractions. CSE 332: Data Abstractions. A Graph is a Thingy... 2
Am Blnk Ltur 0 Autumn 0 CSE 33: Dt Astrtons CSE 33 Grps : Wt s Grp? DFS n BFS Dt Astrtons LnkLsts r to Trs s Trs r to... A Grp s Tny... Wr W v Bn Essntl ADTs: Lsts, Stks, Quus, Prorty Quus, Hps, Vnll Trs,
More informationPlatform Controls. 1-1 Joystick Controllers. Boom Up/Down Controller Adjustments
Ston 7 - Rpr Prours Srv Mnul - Son Eton Pltorm Controls 1-1 Joystk Controllrs Mntnn oystk ontrollrs t t propr sttns s ssntl to s mn oprton. Evry oystk ontrollr soul oprt smootly n prov proportonl sp ontrol
More information17 Basic Graph Properties
Ltur 17: Bs Grp Proprts [Sp 10] O look t t sn y o. Tn t t twnty-svn 8 y 10 olor lossy pturs wt t rls n rrows n prrp on t k o on... n tn look t t sn y o. An tn t t twnty-svn 8 y 10 olor lossy pturs wt t
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 informationFace Detection and Recognition. Linear Algebra and Face Recognition. Face Recognition. Face Recognition. Dimension reduction
F Dtto Roto Lr Alr F Roto C Y I Ursty O solto: tto o l trs s s ys os ot. Dlt to t to ltpl ws. F Roto Aotr ppro: ort y rry s tor o so E.. 56 56 > pot 6556- stol sp A st o s t ps to ollto o pots ts sp. F
More information, 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 informationGraphs Depth First Search
Grp Dpt Frt Sr SFO 337 LAX 1843 1743 1233 802 DFW ORD - 1 - Grp Sr Aort - 2 - Outo Ø By unrtnn t tur, you ou to: q L rp orn to t orr n w vrt r ovr, xpor ro n n n pt-rt r. q Cy o t pt-rt r tr,, orwr n ro
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 informationOn Hamiltonian Tetrahedralizations Of Convex Polyhedra
O Ht Ttrrzts O Cvx Pyr Frs C 1 Q-Hu D 2 C A W 3 1 Dprtt Cputr S T Uvrsty H K, H K, C. E: @s.u. 2 R & TV Trsss Ctr, Hu, C. E: q@163.t 3 Dprtt Cputr S, Mr Uvrsty Nwu St. J s, Nwu, C A1B 35. E: w@r.s.u. Astrt
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 informationMINI POST SERIES BALUSTRADE SYSTEM INSTALLATION GUIDE PRODUCT CODE: MPS-RP
MN POST SRS LUSTR SYSTM NSTLLTON U PROUT O: MPS-RP 0 R0 WLL LN 0 RONT LVTON VW R0 N P 0 T RUR LOK LOT ON LSS. SLON SL TYP. OT SS 000 LSS T 0 00 SRS LSS WT 00/00 (0mm NRMNTS VLL) MX. 000 00-0 (ROMMN) 00
More informationGrade 7/8 Math Circles March 4/5, Graph Theory I- Solutions
ulty o Mtmtis Wtrloo, Ontrio N ntr or ution in Mtmtis n omputin r / Mt irls Mr /, 0 rp Tory - Solutions * inits lln qustion. Tr t ollowin wlks on t rp low. or on, stt wtr it is pt? ow o you know? () n
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 informationApplications of trees
Trs Apptons o trs Orgnzton rts Attk trs to syst Anyss o tr ntworks Prsng xprssons Trs (rtrv o norton) Don-n strutur Mutstng Dstnton-s orwrng Trnsprnt swts Forwrng ts o prxs t routrs Struturs or nt pntton
More informationA Gentle Introduction to Matroid Algorithmics
A Gntl Introuton to Mtro Alortms Mtts F. Stllmnn Aprl, 06 Mtro xoms T trm mtro ws rst us n 9 y Hsslr Wtny []. ovrvw oms rom t txtooks o Lwlr [] n Wls []. Most o t mtrl n ts A mtro s n y st o xoms wt rspt
More informationd e c b a d c b a d e c b a a c a d c c e b
FLAT PEYOTE STITCH Bin y mkin stoppr -- sw trou n pull it lon t tr until it is out 6 rom t n. Sw trou t in witout splittin t tr. You soul l to sli it up n own t tr ut it will sty in pl wn lt lon. Evn-Count
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 informationPhylogenetic Tree Inferences Using Quartet Splits. Kevin Michael Hathcock. Bachelor of Science Lenoir-Rhyne University 2010
Pylont Tr Inrns Usn Qurtt Splts By Kvn Ml Htok Blor o Sn Lnor-Ryn Unvrsty 2010 Sumtt n Prtl Fulllmnt o t Rqurmnts or t Dr o Mstr o Sn n Mtmts Coll o Arts n Sns Unvrsty o Sout Croln 2012 Apt y: Év Czrk,
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 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 informationMATERIAL SEE BOM ANGLES = 2 FINISH N/A
9 NOTS:. SSML N NSPT PR SOP 0-9... NSTLL K STKR N X L STKR TO NS O SROU WT TP. 3. PR-PK LNR RNS WT P (XTRM PRSSUR NL R ) RS OR NNRN PPROV QUVLNT. 4. OLOR TT Y T SLS ORR. RRN T MNS OM OR OMPONNTS ONTNN
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 informationSAMPLE CSc 340 EXAM QUESTIONS WITH SOLUTIONS: part 2
AMPLE C EXAM UETION WITH OLUTION: prt. It n sown tt l / wr.7888l. I Φ nots orul or pprotng t vlu o tn t n sown tt t trunton rror o ts pproton s o t or or so onstnts ; tt s Not tt / L Φ L.. Φ.. /. /.. Φ..787.
More informationData-Parallel Primitives for Spatial Operations Using PM. Quadtrees* primitives that are used to construct the data. concluding remarks.
Dt-rlll rmtvs or Sptl Oprtons Usn M Qutrs* Erk G. Hol Hnn Smt Computr Sn Dprtmnt Computr Sn Dprtmnt Cntr or Automton Rsr Cntr or Automton Rsr Insttut or Avn Computr Sns Insttut or Avn Computr Sns Unvrsty
More information23 Minimum Spanning Trees
3 Mnmum Spnnn Trs Eltron rut sns otn n to mk t pns o svrl omponnts ltrlly quvlnt y wrn tm totr. To ntronnt st o n pns, w n us n rrnmnt o n wrs, onntn two pns. O ll su rrnmnts, t on tt uss t lst mount o
More information18 Basic Graph Properties
O look t t sn y o. Tn t t twnty-svn 8 y 10 olor lossy pturs wt t rls n rrows n prrp on t k o on... n tn look t t sn y o. An tn t t twnty-svn 8 y 10 olor lossy pturs wt t rls n rrows n prrp on t k o on
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 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 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 informationDOCUMENT STATUS: RELEASE
RVSON STORY RV T SRPTON O Y 0-4-0 RLS OR PROUTON 5 MM -04-0 NS TRU PLOT PROUTON -- S O O OR TLS 30 MM 03-3-0 3-044 N 3-45, TS S T TON O PROTTV RM OVR. 3 05--0 LT 3-004, NOT, 3-050 3 0//00 UPT ST ROM SN,
More informationMath 166 Week in Review 2 Sections 1.1b, 1.2, 1.3, & 1.4
Mt 166 WIR, Sprin 2012, Bnjmin urisp Mt 166 Wk in Rviw 2 Stions 1.1, 1.2, 1.3, & 1.4 1. S t pproprit rions in Vnn irm tt orrspon to o t ollowin sts. () (B ) B () ( ) B B () (B ) B 1 Mt 166 WIR, Sprin 2012,
More informationIsomorphism In Kinematic Chains
Intrntonl Journl o Rsr n Ennrn n Sn (IJRES) ISSN (Onln): 0-, ISSN (Prnt): 0- www.rs.or Volum Issu ǁ My. 0 ǁ PP.0- Isomorpsm In Knmt Cns Dr.Al Hsn Asstt.Prossor, Dprtmnt o Mnl Ennrn, F/O- Ennrn & Tnoloy,
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 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 information16.unified Introduction to Computers and Programming. SOLUTIONS to Examination 4/30/04 9:05am - 10:00am
16.unii Introution to Computrs n Prormmin SOLUTIONS to Exmintion /30/0 9:05m - 10:00m Pro. I. Kristin Lunqvist Sprin 00 Grin Stion: Qustion 1 (5) Qustion (15) Qustion 3 (10) Qustion (35) Qustion 5 (10)
More informationDental PBRN Study: Reasons for replacement or repair of dental restorations
Dntl PBRN Stuy: Rsons or rplmnt or rpr o ntl rstortons Us ts Dt Collton Form wnvr stuy rstorton s rpl or rpr. For nrollmnt n t ollton you my rpl or rpr up to 4 rstortons, on t sm ptnt, urn snl vst. You
More informationFun sheet matching: towards automatic block decomposition for hexahedral meshes
DOI 10.1007/s00366-010-0207-5 ORIGINAL ARTICLE Fun st mtn: towrs utomt lok omposton or xrl mss Nols Kowlsk Frnk Loux Mttw L. Sttn Stv J. Own Rv: 19 Frury 2010 / Apt: 22 Dmr 2010 Ó Sprnr-Vrl Lonon Lmt 2011
More informationPriority Search Trees - Part I
.S. 252 Pro. Rorto Taassa oputatoal otry S., 1992 1993 Ltur 9 at: ar 8, 1993 Sr: a Q ol aro Prorty Sar Trs - Part 1 trouto t last ltur, w loo at trval trs. or trval pot losur prols, ty us lar spa a optal
More informationTangram Fractions Overview: Students will analyze standard and nonstandard
ACTIVITY 1 Mtrils: Stunt opis o tnrm mstrs trnsprnis o tnrm mstrs sissors PROCEDURE Skills: Dsriin n nmin polyons Stuyin onrun Comprin rtions Tnrm Frtions Ovrviw: Stunts will nlyz stnr n nonstnr tnrms
More informationOne-Dimensional Computational Topology
Wr rltn so n Stz: Dnn un nur nn, wnn s Sm s Grpn I) ur nn Umsltunsoprton U n BZ-R lrt, II) ur Umrunsoprton wr us r BZ-R ntstt, stllt s Sm nn u r Kullä rlsrrn Grpn r. Dmt st n Gusss Prolm ür n llmnstn Grpn
More informationa ( b ) ( a ) a ( c ) ( d )
Lzy Complton o Prtl Orr to t Smllst Ltt Krll Brtt 1, Ml Morvn 1, Lour Nourn 2 1 LITP/IBP - Unvrst Dns Drot Prs 7 Cs 7014 2, pl Jussu 75256 Prs Cx 05 Frn. ml: (rtt,morvn)@ltp.p.r. 2 Dprtmnt 'Inormtqu Fonmntl
More informationCS 103 BFS Alorithm. Mark Redekopp
CS 3 BFS Aloritm Mrk Rkopp Brt-First Sr (BFS) HIGHLIGHTED ALGORITHM 3 Pt Plnnin W'v sn BFS in t ontxt o inin t sortst pt trou mz? S?? 4 Pt Plnnin W xplor t 4 niors s on irtion 3 3 3 S 3 3 3 3 3 F I you
More informationRe-synthesis for Delay Variation Tolerance
49.1 R-sytss or Dly Vrto Tolr S-C C Dprtmt o CS Ntol Ts Hu Uvrsty Hsu, Tw s@s.tu.u.tw C-To Hs Dprtmt o CS Ntol Ts Hu Uvrsty Hsu, Tw s@tu.s.tu.u.tw K-C Wu Dprtmt o CS Ntol Ts Hu Uvrsty Hsu, Tw Alx@tu.s.tu.u.tw
More informationL.3922 M.C. L.3922 M.C. L.2996 M.C. L.3909 M.C. L.5632 M.C. L M.C. L.5632 M.C. L M.C. DRIVE STAR NORTH STAR NORTH NORTH DRIVE
N URY T NORTON PROV N RRONOUS NORTON NVRTNTY PROV. SPY S NY TY OR UT T TY RY OS NOT URNT T S TT T NORTON PROV S ORRT, NSR S POSS, VRY ORT S N ON N T S T TY RY. TS NORTON S N OP RO RORS RT SU "" YW No.
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 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 information( ) ( ) ( ) 0. Conservation of Energy & Poynting Theorem. From Maxwell s equations we have. M t. From above it can be shown (HW)
8 Conson o n & Ponn To Fo wll s quons w D B σ σ Fo bo n b sown (W) o s W w bo on o s l us n su su ul ow ns [W/ ] [W] su P su B W W 4 444 s W A A s V A A : W W R o n o so n n: [/s W] W W 4 44 9 W : W F
More informationCompression of Graphical Structures
Comprsso o Grpl Struturs Yowook Co Wo Szpkowsk Dprtmt o Computr S Puru Uvrsty W. Lytt, IN 47907, U.S.A. Eml: ywo@puru.u, sp@s.puru.u Astrt F. Brooks rus [3] tr s o tory tt vs us mtr or ormto mo strutur.
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 informationb.) v d =? Example 2 l = 50 m, D = 1.0 mm, E = 6 V, " = 1.72 #10 $8 % & m, and r = 0.5 % a.) R =? c.) V ab =? a.) R eq =?
xmpl : An 8-gug oppr wr hs nomnl mtr o. mm. Ths wr rrs onstnt urrnt o.67 A to W lmp. Th nsty o r ltrons s 8.5 x 8 ltrons pr u mtr. Fn th mgntu o. th urrnt nsty. th rt vloty xmpl D. mm,.67 A, n N 8.5" 8
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 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 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 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 informationSheet Title: Building Renderings M. AS SHOWN Status: A.R.H.P.B. SUBMITTAL August 9, :07 pm
1 2 3 4 5 6 7 8 9 1 11 12 13 14 15 16 17 18 19 orthstar expressly reserves its common law copyright and other property rights for all ideas, provisions and plans represented or indicated by these drawings,
More informationStraight-line Grid Drawings of 3-Connected 1-Planar Graphs
Strt-ln Gr Drwns o 3-Connt 1-Plnr Grs M. Jwrul Alm 1, Frnz J. Brnnur 2, n Stn G. Koourov 1 1 Drtmnt o Comutr Sn, Unvrsty o Arzon, USA {mlm, koourov}@s.rzon.u 2 Unvrsty o Pssu, 94030 Pssu, Grmny rnn@normtk.un-ssu.
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 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 informationMATERIAL SEE BOM ANGLES = 2 > 2000 DATE MEDIUM FINISH
NOTS:. LN MTN SUR WT NTUR/SOPROPYL LOOL PROR TO RN L OR LOO. PPLY LOTT 4 ON TRS. TORQU TO. Nm / 00 lb-in 4. TORQU TO 45-50 Nm / - lb-ft 5. TORQU TO Nm / 4.5 lb-ft. TORQU TO 0 Nm / lb-in. TORQU TO 5.5 Nm
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 informationComputer Graphics. Viewing & Projections
Vw & Ovrvw rr : rss r t -vw trsrt: st st, rr w.r.t. r rqurs r rr (rt syst) rt: 2 trsrt st, rt trsrt t 2D rqurs t r y rt rts ss Rr P usuy st try trsrt t wr rts t rs t surs trsrt t r rts u rt w.r.t. vw vu
More informationInstitute for Advanced Computer Sciences. Abstract. are described for building these three data structures that make use of these
Dt-Prlll Prmtvs or Sptl Oprtons Erk G. Holy Computr Sn Dprtmnt Unvrsty o Mryln Coll Prk, Mryln 074 ol@s.um.u Hnn Smt Computr Sn Dprtmnt Cntr or Automton Rsr Insttut or Avn Computr Sns Unvrsty o Mryln Coll
More informationGraph Search Algorithms
Grp Sr Aortms 1 Grp 2 No ~ ty or omputr E ~ ro or t Unrt or Drt A surprsny r numr o omputton proms n xprss s rp proms. 3 Drt n Unrt Grps () A rt rp G = (V, E), wr V = {1,2,3,4,5,6} n E = {(1,2), (2,2),
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 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 informationBASIC CAGE DETAILS D C SHOWN CLOSED TOP SPRING FINGERS INNER WALL TABS ARE COINED OVER BASE AND COVER FOR RIGIDITY
SI TIS SOWN OS TOP SPRIN INRS INNR W TS R OIN OVR S N OVR OR RIIITY. R IMNSIONS O INNR SIN TO UNTION WIT QU SM ORM-TOR (zqsp+) TRNSIVR. R. RR S OPTION (S T ON ST ) TURS US WIT OPTION T SINS. R (INSI TO
More information