Depth First Search. Yufei Tao. Department of Computer Science and Engineering Chinese University of Hong Kong
|
|
- Brittany Cook
- 6 years ago
- Views:
Transcription
1 Dprtmnt o Computr Sn n Ennrn Cns Unvrsty o Hon Kon
2 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. DFS s surprsnly powrul lortm, n solvs svrl lss prolms lntly. In ts ltur, w wll s on su prolm ttn wtr t nput rp ontns yls.
3 Pts n Cyls Lt G = (V, E) rt rp. Rll: A pt n G s squn o s (v 1, v 2 ), (v 2, v 3 ),..., (v l, v l+1 ), or som ntr l 1. W my lso not t pt s v 1 v 2... v l+1. W now n: A pt v 1 v 2... v l+1 s ll yl v l+1 = v 1.
4 Exmpl A yl:. Anotr on:.
5 Drt Ayl/Cyl Grps I rt rp ontns no yls, w sy tt t s rt yl rp (DAG). Otrws, G s yl. Exmpl Cyl DAG
6 T Cyl Dtton Prolm Lt G = (V, E) rt rp. Dtrmn wtr t s DAG.
7 Nxt, w wll sr t pt rst sr (DFS) lortm to solv t prolm n O( V + E ) tm, w s optml (us ny lortm must t lst s vry vrtx n vry on n t worst s). Just lk BFS, t DFS lortm lso outputs tr, ll t DFS-tr. Ts tr ontns vtl normton out t nput rp tt llows us to wtr t nput rp s DAG.
8 DFS At t nnn, olor ll vrts n t rp wt. An rt n mpty DFS tr T. Crt stk S. Pk n rtrry vrtx v. Pus v nto S, n olor t ry (w mns n t stk ). Mk v t root o T.
9 Exmpl Suppos tt w strt rom. DFS tr S = ().
10 DFS Rpt t ollown untl S s mpty. 1 Lt v t vrtx tt urrntly tops t stk S (o not rmov v rom S). 2 Dos v stll v wt out-nor? 2.1 I ys: lt t u. Pus u nto S, n olor u ry. Mk u l o v n t DFS-tr T. 2.2 I no, pop v rom S, n olor v lk (mnn v s on). I tr r stll wt vrts, rpt t ov y rstrtn rom n rtrry wt vrtx v, rtn nw DFS-tr root t v. DFS vs lk xplorn t w on lk t tm, s w wll s nxt.
11 Runnn Exmpl Top o stk:, w s wt out-nors,. Suppos w ss rst. Pus nto S. DFS tr S = (, ).
12 Runnn Exmpl Atr pusn nto S: DFS tr S = (,, ).
13 Runnn Exmpl Now tops t stk. It s wt out-nors n. Suppos w vst rst. Pus nto S. DFS tr S = (,,, ).
14 Runnn Exmpl Atr pusn nto S: DFS tr S = (,,,, ).
15 Runnn Exmpl Suppos w vst wt out-nor o rst. Pus nto S DFS tr S = (,,,,, ).
16 Runnn Exmpl Atr pusn nto S: DFS tr S = (,,,,,, ).
17 Runnn Exmpl s no wt out-nors. So pop t rom S, n olor t lk. Smlrly, s no wt out-nors. Pop t rom S, n olor t lk. DFS tr S = (,,,, ).
18 Runnn Exmpl Now tops t stk n. It stll s wt out-nor. So, pus nto S. DFS tr S = (,,,,, ).
19 Runnn Exmpl Atr poppn,,,,, : DFS tr S = ().
20 Runnn Exmpl Now tr s stll wt vrtx. So w prorm notr DFS strtn rom. DFS orst S = ().
21 Runnn Exmpl Pop. T n. DFS orst S = (). Not tt w v rt DFS-orst, w onssts o 2 DFS-trs.
22 Tm Anlyss DFS n mplmnt ntly s ollows. Stor G n t jny lst ormt. For vry vrtx v, rmmr t out-nor to xplor nxt. O( V + E ) stk oprtons. Us n rry to rmmr t olors o ll vrts. Hn, t totl runnn tm s O( V + E ).
23 Rll tt w s rlr tt t DFS-tr (wll, prps DFSorst) nos vlul normton out t nput rp. Nxt, w wll mk ts pont sp, n solv t tton prolm.
24 E Clsston Suppos tt w v lry ult DFS-orst T. Lt (u, v) n n G (rmmr tt t s rt rom u to v). It n lss nto 1 Forwr : u s propr nstor o v n DFS-tr o T. 2 Bkwr : u s snnt o v n DFS-tr o T. 3 Cross : I ntr o t ov ppls.
25 Exmpl DFS orst Forwr s: (, ), (, ), (, ), (, ), (, ), (, ), (, ), (, ), (, ). Bkwr : (, ). Cross s: (, ), (, ), (, ).
26 Atr t DFS-orst T s n otn, w n trmn typ o (u, v) n onstnt tm. All tt s rqur s to umnt t DFS lortm sltly y rmmrn wn vrtx ntrs n lvs t stk.
27 Aumntn DFS Sltly Mntn ountr, w s ntlly 0. Evry tm pus or pop s prorm on t stk, w nrmnt y 1. For vry vrtx v, n: Its sovry tm -tm(v) to t vlu o rt tr v s pus nto t stk. Its ns tm -tm(v) to t vlu o rt tr v s popp rom t stk. Dn I (v) = [-tm(v), -tm(v)]. It s strtorwr to otn I (v) or ll v V y pyn O( V ) xtr tm on top o DFS s runnn tm. (Tnk: Wy?)
28 Exmpl DFS orst I () = [1, 16] I () = [2, 15] I () = [3, 14] I () = [4, 13] I () = [5, 12] I ( ) = [6, 9] I () = [7, 8] I () = [10, 11] I () = [17, 18]
29 Prntss Torm Torm: All t ollown r tru: I u s propr nstor o v n DFS-tr o T, tn I (u) ontns I (v). I u s propr snnt o v n DFS-tr o T, tn I (u) s ontn n I (v). Otrws, I (u) n I (v) r sjont. Proo: Follows rtly rom t rst-n-lst-out proprty o t stk.
30 Cyl Torm Torm: Lt T n rtrry DFS-orst. G ontns yl n only tr s kwr wt rspt to T. Proo: T -rton s ovous. Provn t only- rton s mor nvolv, n wll on ltr.
31 Cyl Dtton Equpp wt t yl torm, w know tt w n tt wtr G s yl sly tr vn otn DFS-orst T : For vry (u, v), trmn wtr t s kwr n O(1) tm. I no kwr s r oun, G to DAG; otrws, G s t lst yl. Only O( E ) xtr tm s n. W now onlu tt t yl tton prolm n solv n O( V + E ) tm.
32 It rmns to prov t yl torm. W wll rst prov notr mportnt torm, n tn stls t yl torm s orollry.
33 Wt Pt Torm Torm: Lt u vrtx n G. Consr t momnt wn u s pus nto t stk n t DFS lortm. Tn, vrtx v oms propr snnt o u n t DFS-orst n only t ollown s tru: W n o rom u to v y trvln only on wt vrts. Proo: Wll lt s n xrs (wt soluton prov). Prs rntly, t torm sys tt t sr t u wll t stuk only tr sovrn ll t vrts tt n stll sovr.
34 Exmpl Consr t momnt n our prvous xmpl wn just ntr t stk. S = (,,,, ). DFS tr W n s tt n r,, y oppn on only wt vrts. Tror,,, r ll propr snnts o n t DFS-orst; n s no otr snnts.
35 Provn t Only-I Drton o t Cyl Torm W wll now prov tt G s yl, tn tr must kwr n t DFS-orst. Suppos tt t yl s v 1 v 2... v l v 1. Lt v, or som [1, l], t vrtx n t yl tt s t rst to ntr t stk. Tn, y t wt pt torm, ll t otr vrts n t yl must propr snnts o v n t DFS-orst. Ts mns tt t pontn to v n t yl s k. W tus v omplt t wol proo o t yl torm.
Lecture 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 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 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 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 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 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 informationThe 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 informationMinimum Spanning Trees
Mnmum Spnnng Trs Spnnng Tr A tr (.., connctd, cyclc grph) whch contns ll th vrtcs of th grph Mnmum Spnnng Tr Spnnng tr wth th mnmum sum of wghts 1 1 Spnnng forst If grph s not connctd, thn thr s spnnng
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 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 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 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 informationMaximum Matching Width: new characterizations and a fast algorithm for dominating set
Maxmum Matcn Wdt: nw caractrzatons and a ast alortm or domnatn st 정지수 (KAIST) jont work wt Sv Hortmo Sætr and Jan Arn Tll (Unvrsty o Brn) 1st Koran Worksop on Grap Tory 2015.8.27. KAIST Grap wdt paramtrs
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 informationMinimum Spanning Trees
Yufi Tao ITEE Univrsity of Qunslan In tis lctur, w will stuy anotr classic prolm: finin a minimum spannin tr of an unirct wit rap. Intrstinly, vn tou t prolm appars ratr iffrnt from SSSP (sinl sourc sortst
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 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 informationGraphs Breadth First Search
Grp Brdt Frt Sr SFO ORD LAX DFW - 1 - Outo Ø By undrtndn t tur, you oud to: q L rp ordn to t ordr n w vrt r dovrd n rdt-rt r. q Idnty t urrnt tt o rdt-rt r n tr o vrt tt r prvouy dovrd, ut dovrd or undovrd.
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 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 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 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 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 informationGraph Search Algorithms CSE
Grp Src Aortms 1 Grp b No ~ cty or computr E ~ ro or t cb c Unrct or Drct A surprsny r numbr o computton probms cn b xprss s rp probms. 2 Drct n Unrct Grps () A rct rp G = (V, E), wr V = {1,2,3,4,5,6}
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 informationDOCUMENT STATUS: LA-S5302-XXXXS LA, SSS, TRICEPS EXTENSION VERY
RVSON STORY RV T SRPTON O Y //0 RLS OR PROUTON T LN MR ----- L /0/0 UPT SN N OMPONNTS US: S 3-03 (*N TWO PLS ONLY) WS 3-5, PRT 3-00 TO SSMLY. T OLLOWN UPT: 3-30, 3-403, 3-403, 3-40, 3-45, 3-4, 3-5. 30
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 informationMinimum Spanning Trees
Minimum Spnning Trs Minimum Spnning Trs Problm A town hs st of houss nd st of rods A rod conncts nd only houss A rod conncting houss u nd v hs rpir cost w(u, v) Gol: Rpir nough (nd no mor) rods such tht:
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 informationH NT Z N RT L 0 4 n f lt r h v d lt n r n, h p l," "Fl d nd fl d " ( n l d n l tr l t nt r t t n t nt t nt n fr n nl, th t l n r tr t nt. r d n f d rd n t th nd r nt r d t n th t th n r lth h v b n f
More informationAn Introduction to Clique Minimal Separator Decomposition
Alortms 2010, 3, 197-215; o:10.3390/3020197 Rvw OPEN ACCESS lortms ISSN 1999-4893 www.mp.om/ournl/lortms An Introuton to Clqu Mnml Sprtor Domposton Ann Brry 1,, Romn Poorln 1 n Gnvèv Smont 2 1 LIMOS UMR
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 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 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 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 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 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 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 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 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 informationAquauno Video 6 Plus Page 1
Connt th timr to th tp. Aquuno Vio 6 Plus Pg 1 Usr mnul 3 lik! For Aquuno Vio 6 (p/n): 8456 For Aquuno Vio 6 Plus (p/n): 8413 Opn th timr unit y prssing th two uttons on th sis, n fit 9V lklin ttry. Whn
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 informationA New Interface to Render Graphs Using Rgraphviz
A Nw Intr to Rnr Grps Usn Rrpvz Florn Hn Otor 30, 2017 Contnts 1 Ovrvw 1 2 Introuton 1 3 Dult rnrn prmtrs 3 3.1 Dult no prmtrs....................... 4 3.2 Dult prmtrs....................... 6 3.3 Dult
More informationCHELOURANYAN CALENDAR FOR YEAR 3335 YEAR OF SAI RHAVË
CHELOURANYAN CALENDAR FOR YEAR YEAR OF SAI RHAVË I tou woust n unon wt our Motr, now tt tou st nvr t Hr. I tou woust sp t v o mttr, now tt tr s no mttr n no v. ~Cry Mry KEY TO CALENDAR T Dys o t W In t
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 information12/3/12. 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 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 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 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 informationPreview. Graph. Graph. Graph. Graph Representation. Graph Representation 12/3/2018. Graph Graph Representation Graph Search Algorithms
/3/0 Prvw Grph Grph Rprsntton Grph Srch Algorthms Brdth Frst Srch Corrctnss of BFS Dpth Frst Srch Mnmum Spnnng Tr Kruskl s lgorthm Grph Drctd grph (or dgrph) G = (V, E) V: St of vrt (nod) E: St of dgs
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 informationDOCUMENT STATUS: CORE HEALTH & FITNESS, LLC IL-D2002-XXAAX IP,DUAL ADJUSTIBLE PULLEY MATERIAL SEE BOM FINISH N/A N/A SHEET SIZE: B SCALE: 1:33.
NOTS: RVSON STORY RV T SRPTON O Y //04 RLS OR PROUTON 433 P 34 55 033 OUMNT STTUS: NOT O PROPRTRY NORMTON TS OUMNT SLL NOT RPROU NOR SLL T NORMTON ONTN RN US Y OR SLOS TO OTR XPT S XPRSSLY UTORZ Y OR LT
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 information