PREDICTABILITY IN DISCRETE-EVENT SYSTEMS UNDER PARTIAL OBSERVATION 1. Sahika Genc, Stéphane Lafortune
|
|
- Delphia McCormick
- 5 years ago
- Views:
Transcription
1 PREDICTABILITY IN DISCRETE-EVENT SYSTEMS UNDER PARTIAL OBSERVATION 1 Shik Gen, Stéhne Lfortune Dertment of Eletril Engineering n Comuter Siene, University of Mihign, 1301 Bel Avenue, Ann Aror, MI , USA sgen,stehne@ees.umih.eu Coyright 2006 IFAC Astrt: This er stuies the rolem of reiting ourrenes of signifint event in isrete-event system. The reitility of ourrenes of n event in system is efine in the ontext of forml lnguges. The reitility of lnguge is stronger onition thn the ignosility of the lnguge. An imlementle neessry n suffiient onition for reitility of ourrenes of n event in systems moele y regulr lnguges is resente. Keywors: Disrete-event systems, reition, ignosis. 1. INTRODUCTION This er resses the rolem of reiting ourrenes of signifint (e.g., fult) event in isrete-event system (DES). The system uner onsiertion is moele y lnguge over n event set. The event set is rtitione into oservle events (e.g., sensor reings, hnges in sensor reings) n unoservle events, i.e., the events tht re not iretly reore y the sensors tthe to the system. The ojetive is to reit ourrenes of ossily unoservle event in the system ehvior, se on the strings of oservle events. If it is ossile to reit ourrenes of n event in the system, then eening on the nture of the event the system oertor n e wrne n the oertor my eie to hlt the system or otherwise tke reventive mesures. 1 This reserh is suorte in rt y NSF grnt CCR n y ONR grnt N The first uthor wishes to knowlege suort from Brour Fellowshi from the Hore H. Rkhm Shool of Grute Stuies t the University of Mihign. To the est of our knowlege, the notion of reitility tht is introue n stuie in this er is ifferent from rior works on other notions of reitility in (Co, 1989; Buss et l., 1991; Shenging n Kumr, 2004; Fel n Hollowy, 1999). For instne, the reition rolem onsiere in (Co, 1989) is relte to the roerties of seil tye of rojetion etween two lnguges (sets of trjetories); this is is muh more generl thn our ojetive, whih is to reit ourrenes of seifi events, ut our work is not seil se. The stte reition of oule utomt stuie in (Buss et l., 1991) is formulte s omuting the stte vetor of n ientil utomt fter T stes in the oertion of the system; the system struture in this work is ifferent from ours. In our se the interest is on single utomton n event reition, not stte, uner rtil oservtion. The notion of reition onsiere in (Shenging n Kumr, 2004) iffers from the one in our work in the sense tht in (Shenging n Kumr, 2004) reitility of system is neessry onition for ignosility of the system while in our work ignosility is neessry onition for
2 reitility. The reition rolem stuie in (Fel n Hollowy, 1999) onsiers issuing wrning when it is likely for fult to hen in the future evolution of the system; in our work, if the ourrene of n event is reitle in lnguge, then it is ertin tht the event will our. Also, in (Fel n Hollowy, 1999), it is ossile tht flse fult reition wrnings re issue; in our work, no flse ositives re issue. The rolem of reition stuie in this er is insire y the rolem of fult ignosis for DES. The rolem of fult ignosis for DES hs reeive onsierle ttention in the lst ee (see the referenes in (Smth et l., 1996)) n ignosis methoologies se on the use of isrete-event moels hve een suessfully use in vriety of tehnologil systems rnging from oument roessing systems to intelligent trnsorttion systems. A isrete-event roess lle ignoser introue in (Smth et l., 1996) is of rtiulr relevne to the resent work. Lter in the er, the ignoser is use to erive neessry n suffiient onition for reitility in systems moele y regulr lnguges. The rest of the er is orgnize s follows. In Setion 2, the nottion n frequently use terms re introue. In Setion 3, the reitility of ourrenes of n event in system is efine in the ontext of forml lnguges. The reitility roerty of lnguge is stronger onition thn the ignosility of the lnguge s efine in (Smth et l., 1996). In Setion 4, it is shown tht in the se of regulr lnguges, there exists neessry n suffiient onition for reiting ourrenes of n event in the lnguge in the form of test on ignosers. In Setion 5, summry of the results in the er is resente, n onluing remrks re given. Omitte roofs re ville in (Gen, 2006). 2. PRELIMINARIES Let Σ e finite set of events. A string is finite-length sequene of events in Σ. The set of ll strings forme y events in Σ is enote y Σ. The set Σ is lso lle the Kleene-losure of Σ. Any suset of Σ is lle lnguge over Σ. The refix-losure of lnguge L is enote y L n efine s L = {s Σ : t L suh tht st L}. Given string s L, L/s is lle the ost-lnguge of L fter s n efine s L/s = {t Σ : st L}. L is live if every string in L n e extene to nother string in L. Let L e lnguge over Σ = Σ o Σ uo, where Σ o n Σ uo enote the oservle n unoservle events, resetively. The rojetion of strings from L to Σ o is enote y P. Given string s L, P (s) is otine y removing unoservle events (elements of Σ uo ) in s. The inverse rojetion of string s o Σ o with reset to L is the set of strings in L whose rojetion is equl to s o. Given n event σ Σ n string s Σ, we use the set nottion σ s to sy tht σ ers t lest one in s. Let L e refix-lose n live lnguge over Σ. Given n event σ Σ n L, S(σ, L) is the set of strings in L tht ens with σ. Formlly, S(σ, L) = {sσ L : s Σ, σ Σ}. 3. PROBLEM STATEMENT In this setion, we efine the rolem of reiting ourrenes of n event in system tht is uner rtil oservtion. We moel the system s lnguge L over n event set Σ. The event to e reite my e n unoservle event or n oservle one. First, we resent n illustrtive exmle to introue the notion of reitility. Then, we give the forml efinition for reitility of the ourrene of n event. We onlue the setion y omring the ignosility of lnguge L s efine in (Smth et l., 1996) to the reitility of L. Roughly seking, the ourrene of n event in lnguge is reitle if it is ossile to infer out future ourrenes of the event se on the oservle reor of strings tht o not ontin the event to e reite. Consier ny string s in S(σ, L) where σ is the event to e reite. We wish to fin refix t of s suh tht t oes not ontin σ n ll the long-enough ontinutions in L of the strings with the sme rojetion s t ontin σ. If there is t lest one suh t, then the ourrene of σ is reitle in L. Consier the refix-lose, live lnguge generte y the utomton shown in Fig. 1. The lnguge generte is L = + + +, (1) where Σ uo = {, } n Σ o = {, }. Let e the event to e reite. The set of strings tht en with is S(, L) = {,, }. (2) In orer to show tht is reitle in L, we must fin n n N n t s for ll s S(, L) suh tht / t n for ll u n its ontinutions v L/u if u reors the sme string of oservle events s t, i.e., P (t) = P (u), n u oes not ontin, i.e. / u, n v is of length greter thn n N, i.e. v n,
3 then v ontins. Let us strt with s = S(, L). Then t. Suose tht t =. Then, P 1 () (Σ \ {}) L = {ɛ,, }. If u =, then L/u = + +. Sine /, there is ontinution of u tht oes not ontin. Then, there exists string whih reors the sme string of oservle events s t n not ll of its ontinutions ontin. Thus, t = is wrong hoie to rove the reitility of. Suose tht t =. For ll u P 1 () (Σ \ {}) L = {,, } n for ll v L/u suh tht v 2, then v ontins. Thus, t = is right hoie for s S(, L). Similrly, it n e verifie tht t = n t = work for s = n s = in S(, L), resetively Fig. 1. G N,8N,3N 9N,6F1,5F1 10F1,6F1,5F1 0N Fig. 2. D G. Bse on the ove isussion, we formlly efine the notion of reitility. Definition 1. Given L refix-lose, live lnguge over Σ, ourrenes of event σ Σ re reitle in L with reset to P if ( n N)( s S(σ, L))( t s)[(σ / t) P] where P : ( u L)( v L/u)[(P (u) = P (t)) (σ / u) ( v n) (σ v)]. 3.1 Dignosility vs. Preitility The reitility of ourrenes of n event σ in refix lose n live lnguge L is stronger thn the ignosility of L with reset to σ. We onsier the ignosility s efine in (Smth et l., 1996) in the ontext of forml lnguges. Roughly seking, L is ignosle with reset to σ if it is ossile to etet ourrenes of σ with finite ely. For the ske of omleteness, we rell in Definition 2 the forml efinition of ignosility. Definition 2. A refix-lose n live lnguge is ignosle with reset to P n σ if ( n N)( s S(σ, L))( t L/s)[ t n D] 11N where D : ω P 1 P (st) L σ ω. We now resent n illustrtive exmle where lnguge is ignosle with reset to n event ut the ourrene of the event is not reitle. We onsier the lnguge generte y the utomton shown in Fig. 3. The lnguge is L = e + e + + e (3) where Σ o = {,,, } n Σ uo = {e, }. In this se, the ourrene of is not reitle. Let s = e S(, L). Then, t e. For ny t e, we lwys hve hve the string n where n 0, whih oes not ontin. Thus, there oes not exist t so tht Definition 1 is stisfie for. However, the ourrene of (n unoservle event) n e etete with finite ely. After the oservtion of, we re ertin tht hs ourre t lest one. Thus, L is ignosle with reset to σ ut the ourrene of σ is not reitle in L e 8 Fig. 3. G. 0 e e N 6N,3N Fig. 4. D G. 0N 1N,10N 10N 8F1,5F1 The following roosition follows iretly from the ove efinitions. Proosition 3. Given refix-lose n live lnguge L Σ, if ourrenes of σ Σ re reitle in L with reset to P, then L is ignosle with reset to P n σ. 4. VERIFICATION OF PREDICTABILITY FOR REGULAR LANGUAGES In this setion, we onsier systems moele y regulr lnguges. Regulr lnguges re the lnguges tht re ete (or generte) y Finite Stte Automt (FSA). An FSA is four-tule G = (Q, Σ, δ, q 0 ) (4) where Q is the set of sttes, Σ is the finite set of events, δ : Q Σ Q is the stte trnsition funtion n q 0 is the initil stte.
4 The neessry n suffiient onition (resente lter in this setion) for reitility is se on isrete-event roess lle ignoser. The ignoser is n FSA uilt for the system with reset to rojetion P onto the set of oservle events n to given event. Let G = (Q, Σ, δ, q 0 ) e n FSA tht genertes lnguge L. We enote y D G the ignoser uilt for G n σ Σ. The ignoser D G is of the form D G = (Q D, Σ o, δ D, q D,0, σ ), (5) where Q D is the set of ignoser sttes, δ D : Q D Σ o Q D is the ignoser stte trnsition funtion, q D,0 Q D is the initil ignoser stte. The ignoser stte se Q D is suset of 2 Q {N,F 1}. Stte q D Q D is of the form q D = {(q 1, l 1 ),..., (q n, l n )}, (6) where q i Q n l i {N, F 1} for i = 1,..., n. Let q D n q D e two ignoser sttes in Q D suh tht q D is rehe from q D y σ o Σ o, i.e., q D = δ D(q D, σ o ) is efine. Let q D = {(q 1, l 1 ),..., (q m, l m )} n q D = {(q 1, l 1),..., (q n, l n)}. For ll i {1,..., n}, there exists j {1, 2,..., m} suh tht q i = δ(q j, s), (7) where s = tσ o n t Σ uo, n { l i F 1, if lj = F 1 or (σ = s), (8) N, if l j = N n (σ / s). We sy tht ignoser stte q D = {(q 1, l 1 ),..., (q m, l m )} Q D for m N is norml if l j = N for ll j = 1,..., m; ertin if l j = F 1 for ll j = 1,..., m; n unertin if there exist l j = N n l i = F 1 for some i, j {1,..., m}. We enote y Q N D Q D the set of ignoser sttes tht re norml, y Q U D Q D the set of ignoser sttes tht re unertin, n y Q C D Q D the set of ignoser sttes tht re ertin. Consier FSA G in Fig. 1. Let Σ uo = {, }. The ignoser 2 for G n is s shown in Fig. 2. The ignoser stte {1N, 8N, 3N} is norml, {9N, 6F 1, 5F 1} is unertin, n {10F 1, 6F 1, 5F 1} is ertin. We efine n essiility oertion on n FSA to fin the essile rt of n FSA from stte. Definition 4. Let G = (Q, Σ, δ, q 0 ) n q Q. The essile rt of G with reset to q is enote y A(G, q) n is A(G, q) = (Q, Σ, δ, q), (9) where Q = {q Q : ( s Σ )(δ(q, s) = q is efine)}, n δ = δ Q Σ Q. 2 Dignosers shown in this er re uilt using UMDES- LIB softwre (Lfortune, n..). Let G = (Q, Σ, δ, q 0 ). We sy tht set of sttes {q 1, q 2,..., q n } Q n string σ 1 σ 2... σ n Σ form yle if q i+1 = δ(q i, σ i ), i = 1, 2,..., n 1 n q 1 = δ(q n, σ n ). In the rest of this setion, we ssume the system stisfies the following: If {q 1, q 2,..., q n } Q n σ 1 σ 2... σ n Σ form yle, then there exists t lest one oservle event σ j in {σ 1,..., σ n } Σ. Tht is, G oes not ontin yle in whih sttes re onnete with unoservle events only. Lemm 5 elow sttes tht if there is yle in D G tht ontins ertin ignoser stte, then ll the ignoser sttes in the yle re ertin (sine the F 1 lel rogtes). Lemm 6 sttes tht if there is yle in D G tht is forme y unertin or norml sttes, then there exists orresoning yle in G suh tht ll the sttes in the yle hve norml lels in the yle in D G. Lemm 5. Let G = (Q, Σ, δ, q 0 ) e n FSA tht genertes L suh tht L is refix-lose n live n let D G = (Q D, Σ o, δ D, q D,0, σ ) e the ignoser for G n σ. Suose {q D,1,..., q D,n } Q D n σ o,1... σ o,n Σ o form yle in D G where n N. If there exists i {1, 2,..., n} suh tht q D,i Q C D, then q D,j Q C D for ll j = 1, 2,..., n. Lemm 6. Let G = (Q, Σ, δ, q 0 ) e n FSA tht genertes L suh tht L is refix-lose n live, n let D G = (Q D, Σ o, δ D, q D,0, σ ) e the ignoser for G n σ. Suose {q D,1,..., q D,n } Q D n σ o,1... σ o,n Σ o form yle in D G where n N n q D,i is in Q U D or QN D for ll i = 1, 2,..., n. Then, there exists (q i, l i ) q D,i for i = 1, 2,..., n, suh tht q i+1 = δ(q i, s i ) for i = 1, 2,..., n 1 n q 1 = δ(q n, s n ) where s i Σ, P (s i ) = σ o,i, n l i = N for i = 1, 2,..., n. Let F D e the set of norml ignoser sttes tht ossess n immeite suessor tht is not norml. Formlly, F D = {x D Q N D : y D = δ D (x D, σ o ) suh tht σ o Σ o n y D / Q N D }. Lemm 7 sttes tht ny unertin or ertin ignoser stte is rehe from ignoser stte in F D. Lemm 7. Let G = (Q, Σ, δ, q 0 ) e n FSA tht genertes L suh tht L is refix-lose n live, n let D G = (Q D, Σ o, δ D, q D,0, σ f ) e the ignoser for G n σ. Let x D,i = δ D (x D,i 1, σ o,i ) for i = 1, 2,..., m where m N, x D,i is ignoser stte, σ o,i is n oservle event for i = 1, 2,..., m, n x D,0 is the initil ignoser stte. If x D,m is in Q U D or QC D, then there exists M m suh tht x D,M F D. Proof 8. The roof is y inution on the sequene of oservle events.
5 Bse (m = 1): In this se, x D,m = x D,1 / Q N D n x D,1 = δ D (x D,0, σ o,1 ). Sine x D,0 is the initil ignoser stte, y efinition it is norml. If the immeite suessor x D,1 of x D,0 is not norml ignoser stte, then x D,0 F D. This omletes the roof of inution se. Hyothesis (m = M ): If x D,M / Q N D, then there exists M M suh tht x D,M F D. Ste (m=m +1): We nee to show tht if x D,M +1 / Q N D, then there exists M M + 1 suh tht x D,M F D. We onsier two ses: (i) x D,M Q N D, n (ii) x D,M / QN D. In the first se, if x D,M Q N D, then x D,M is in F D y efinition. For the other se, if x D,M / Q N D, then y the inution hyothesis there exists M M < M + 1 suh tht x D,M is in F D. This omletes the roof of the inution ste. In the following theorem, we stte the neessry n suffiient onition for reitility of ourrenes of n event. The onition is se on nlyzing the yles in the ignoser. Theorem 9. Let G = (Q, Σ, δ, q 0 ) e n FSA tht genertes L where L is refix-lose n live. Let D G = (Q D, Σ o, δ D, q D,0, σ ) e the ignoser for G n σ. The ourrenes of σ re reitle in L with reset to P iff for ll q D F D, onition C hols, where C : ll yles in A(D G, q D ) re yles of ertin ignoser sttes. Proof 10. The roof is in two rts. ( ): We rove tht if σ is reitle in L, then for ll q D F D the only yles in A(D G, q D ) re yles of ertin ignoser sttes. The roof is y ontrition. Suose tht there exists q D F D suh tht A(D G, q D ) ontins yle forme y {x D,1,..., x D,m } n σ o,1... σ o,m Σ o where x D,i / Q C D for some i {1, 2,..., m}. By Lemm 5, if there exists ignoser stte x D,i in the yle suh tht x D,i is not ertin ignoser stte, then none of the other ignoser sttes in the yle re ertin. Thus, x D,i / Q C D for ll i = 1, 2,..., m. By Lemm 6, orresoning to the yle of ignoser sttes in the ignoser, there exists yle in G suh tht eh stte in tht yle is lele with N in the yle in the ignoser. Suose tht the yle in G is forme y {x 1,..., x m } n s 1... s m Σ where (x i, N) x D,i n s i Σ suh tht P (s i ) = σ o,i for i = 1, 2,..., m. Let q D F D e rehe from the initil ignoser stte q D,0 y s o Σ o. Sine q D is in F D, then there exists s S(σ, L) suh tht P (s) = s o. Moreover, sine σ is reitle in L, then y efinition of reitility, there exists t s suh tht (σ / t) P. We now rove tht there exists u suh tht P (u) = P (t) n σ / u, n for ll ontinutions v of u if v is of length greter thn ny n N, then v oes not ontin σ. Pik ignoser stte in the yle. Without loss of generlity ik x D,1. Then, we ik the stte in the ignoser stte whih hs lel N n is rt of the orresoning yle in G. Let (x 1, l 1 ) e tht stte in x D,1, with l 1 = N. Suose tht x D,1 is rehe from q D y exeuting s o Σ o. Then, x D,1 = δ D (q D,0, s o s o). Let u n u L/u e suh tht P (uu ) = s o s o n x 1 = δ(q 0, uu ). Sine l 1 = N, then neither u nor u ontin σ. Sine x 1 is in the orresoning yle in G, then x 1 = δ(q 0, uu (s 1 s 2... s m ) k ) for k N. Let v = u (s 1 s 2... s m ) k where k is n integer suh tht v n. Then, there exists u n v L/u suh tht P (u) = P (t) (sine P (t) = s o ), σ / u, v n n σ / v (sine l 1 = N). This violtes the onition P in the efinition of reitility. Thus, there is ontrition. This omletes one rt of the roof. ( ): We rove tht if for ll q D F D the only yles in A(D G, q D ) re yles of ertin ignoser sttes, then σ is reitle in L. Pik ny s S(σ, L). Let q = δ(q 0, s) Q. Then, ik ny s uo σ o L/s suh tht s uo Σ uo n σ o Σ o. Let y = δ(q, s uo σ o ) Q. Suose tht P (s) = s o Σ o. Then, let x D = δ D (q D,0, s o ) n y D = δ D (x D, σ o ) in Q D. Then, there exists (y, l y ) y D where l y = F 1. Thus, y D Q U D Q C D. We now onsier the following two ses: (i) x D Q N D, thus, x D F D, n (ii) x D Q U D QC D. Cse (i). Sine x D Q N D n y D / Q N D, then x D F D. We hoose t = s. For ll u suh tht P (u) = P (t), P (u) = s o. Sine the only yles in A(D G, x D ) re yles of ertin sttes, then for ll v L/u, v ontins σ. Cse (ii). If x D Q U D QC D, i.e., x D is not norml, then we wish to fin norml ignoser stte in F D from whih x D is rehe. By Lemm 7, there exists ignoser stte w D rehle from the initil ignoser stte, x D is essile from w D, n w D is in F D. Then, sine F D onsists of norml ignoser sttes, w D is in Q N D. Thus, the roof of Cse (ii) reues to the se of (i) in whih we sustitute w D Q N D for x D Q N D. This omletes the seon rt of the roof. Consier the FSA in Fig. 1 n the orresoning ignoser in Fig. 2 where Σ uo = {, } n Σ o = {, }, n F D = {{1N, 8N, 3N}}. The
6 essile FSA from {1N, 8N, 3N} ontins only one yle forme y {10F 1, 6F 1, 5F 1} whih is ertin ignoser stte. Thus, the ourrene of is reitle. If we onsier the FSA in Fig. 3 n the orresoning ignoser in Fig. 4 where Σ o = {,,, } n Σ uo = {e, }, then, F D = {{6N, 3N}}. The essile FSA from {6N, 3N} ontins two yles one of whih ontins norml ignoser stte. Here, the ourrene of is not reitle. We now show tht it is suffiient to test onition C in Theorem 9 on ertin susets of F D to gurntee tht this onition hols for ll sttes in F D. Corollry 11. Let x D, y D F D suh tht y D = f D (x D, s o ) is efine for some s o Σ o. Then, onition C hols for ll q D F D iff C hols for ll q D F D \ {y D }. F D, thus resulting in omuttionl svings one Min(S ED ) hs een omute. 5. CONCLUSION We hve efine the new roerty of reitility of the ourrene of signifint event (e.g., fult) se on the urrent reor of oservle events. We hve shown neessry n suffiient onition for reitility in the se of systems moele y regulr lnguges. We hve resente test to verify the reitility roerty se on ignosers. An lternte test of olynomiltime omlexity (in the numer of system sttes) is resente in (Gen, 2006). The stuy of reitility is insire n motivte y the stuy of fult ignosis. Our long term gol is to form n integrte theory of ignosis n reition in the frmework of forml lnguges. In view of Corollry 11, let us ll suset of F D C-suffiient if testing onition C in Theorem 9 on this suset is suffiient to gurntee tht C hols for ll q D F D. Denote y S FD the set of ll C-suffiient susets of F D. Let Min(S FD ) enote ll susets of F D in S FD tht hve minimum rinlity. Proosition 12. Min(S FD ) is not singleton in generl. Define reltion etween x D n y D in F D s follows: x D y D s o, t o o suh tht y D = δ D (x D, s o ) n x D = δ D (y D, s o ). Tht is, two sttes in F D re relte if oth of them er in yle in the ignoser. Proosition 13. The reltion is n equivlene reltion. We now work on the equivlene lsses (inue y ) in F D inste of the sttes in F D. Let E D e the equivlene lsses of F D for the reltion. Denote y S ED the set of ll C-suffiient susets of E D. Let Min(S ED ) enote ll sets in S ED tht hve minimum rinlity. Theorem 14 sttes tht there is only one C-suffiient suset of E D with the minimum rinlity. Theorem 14. Min(S ED ) is singleton. We hve eveloe n lgorithm for fining this unique element in Min(S ED ). In view of Corollry 11 n Theorem 14, the neessry n suffiient onition for reitility in Theorem 9 eomes: Conition C hols for ll q D Min(S ED ). In generl, Min(S ED ) REFERENCES Buss, Smuel R., Christos Pimitriou n John Tsitsiklis (1991). On the reitility of oule utomt: n llegory out hos. Comlex Systems 5, Co, Xi-Ren (1989). The reitility of isrete event systems. IEEE Trns. Automti Control 34(11), Fel, H.K. n L.E. Hollowy (1999). Using SPC n temlte monitoring metho for fult etetion n reition in isrete event mnufturing systems. In: Proeeings of the 1999 IEEE Interntionl Symosium on Intelligent Control/Intelligent Systems n Semiotis Gen, Shik (2006). On ignosis n reitility of rtilly-oserve isreteevent systems. Ph.D. Thesis. University of Mihign, Eletril Engineering: Systems. Lfortune, S. (n..). Umes-li softwre lirry. htt:// tooloxes.html. Smth, M., R. Sengut, S. Lfortune, K. Sinnmohieen n D. Teneketzis (1996). Filure ignosis using isrete event moels. IEEE Trns. Control Systems Tehnology 4(2), Shenging, Jing n Rtnesh Kumr (2004). Filure ignosis of isrete-event systems with liner-time temorl logi seifitions. IEEE Trns. Automti Control 49(6),
CS 491G Combinatorial Optimization Lecture Notes
CS 491G Comintoril Optimiztion Leture Notes Dvi Owen July 30, August 1 1 Mthings Figure 1: two possile mthings in simple grph. Definition 1 Given grph G = V, E, mthing is olletion of eges M suh tht e i,
More informationCompression of Palindromes and Regularity.
Compression of Plinromes n Regulrity. Kyoko Shikishim-Tsuji Center for Lierl Arts Eution n Reserh Tenri University 1 Introution In [1], property of likstrem t t view of tse is isusse n it is shown tht
More informationSolutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite!
Solutions for HW9 Exerise 28. () Drw C 6, W 6 K 6, n K 5,3. C 6 : W 6 : K 6 : K 5,3 : () Whih of the following re iprtite? Justify your nswer. Biprtite: put the re verties in V 1 n the lk in V 2. Biprtite:
More information2.4 Theoretical Foundations
2 Progrmming Lnguge Syntx 2.4 Theoretil Fountions As note in the min text, snners n prsers re se on the finite utomt n pushown utomt tht form the ottom two levels of the Chomsky lnguge hierrhy. At eh level
More informationCS 573 Automata Theory and Formal Languages
Non-determinism Automt Theory nd Forml Lnguges Professor Leslie Lnder Leture # 3 Septemer 6, 2 To hieve our gol, we need the onept of Non-deterministi Finite Automton with -moves (NFA) An NFA is tuple
More informationCounting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs
Isomorphism of Grphs Definition The simple grphs G 1 = (V 1, E 1 ) n G = (V, E ) re isomorphi if there is ijetion (n oneto-one n onto funtion) f from V 1 to V with the property tht n re jent in G 1 if
More informationMid-Term Examination - Spring 2014 Mathematical Programming with Applications to Economics Total Score: 45; Time: 3 hours
Mi-Term Exmintion - Spring 0 Mthemtil Progrmming with Applitions to Eonomis Totl Sore: 5; Time: hours. Let G = (N, E) e irete grph. Define the inegree of vertex i N s the numer of eges tht re oming into
More informationTechnische Universität München Winter term 2009/10 I7 Prof. J. Esparza / J. Křetínský / M. Luttenberger 11. Februar Solution
Tehnishe Universität Münhen Winter term 29/ I7 Prof. J. Esprz / J. Křetínský / M. Luttenerger. Ferur 2 Solution Automt nd Forml Lnguges Homework 2 Due 5..29. Exerise 2. Let A e the following finite utomton:
More information22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of:
22: Union Fin CS 473u - Algorithms - Spring 2005 April 14, 2005 1 Union-Fin We wnt to mintin olletion of sets, uner the opertions of: 1. MkeSet(x) - rete set tht ontins the single element x. 2. Fin(x)
More informationNON-DETERMINISTIC FSA
Tw o types of non-determinism: NON-DETERMINISTIC FS () Multiple strt-sttes; strt-sttes S Q. The lnguge L(M) ={x:x tkes M from some strt-stte to some finl-stte nd ll of x is proessed}. The string x = is
More informationAssignment 1 Automata, Languages, and Computability. 1 Finite State Automata and Regular Languages
Deprtment of Computer Science, Austrlin Ntionl University COMP2600 Forml Methods for Softwre Engineering Semester 2, 206 Assignment Automt, Lnguges, nd Computility Smple Solutions Finite Stte Automt nd
More informationCS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6
CS311 Computtionl Strutures Regulr Lnguges nd Regulr Grmmrs Leture 6 1 Wht we know so fr: RLs re losed under produt, union nd * Every RL n e written s RE, nd every RE represents RL Every RL n e reognized
More informationA Disambiguation Algorithm for Finite Automata and Functional Transducers
A Dismigution Algorithm for Finite Automt n Funtionl Trnsuers Mehryr Mohri Cournt Institute of Mthemtil Sienes n Google Reserh 51 Merer Street, New York, NY 1001, USA Astrt. We present new ismigution lgorithm
More informationSection 2.3. Matrix Inverses
Mtri lger Mtri nverses Setion.. Mtri nverses hree si opertions on mtries, ition, multiplition, n sutrtion, re nlogues for mtries of the sme opertions for numers. n this setion we introue the mtri nlogue
More informationGraph Theory. Simple Graph G = (V, E). V={a,b,c,d,e,f,g,h,k} E={(a,b),(a,g),( a,h),(a,k),(b,c),(b,k),...,(h,k)}
Grph Theory Simple Grph G = (V, E). V ={verties}, E={eges}. h k g f e V={,,,,e,f,g,h,k} E={(,),(,g),(,h),(,k),(,),(,k),...,(h,k)} E =16. 1 Grph or Multi-Grph We llow loops n multiple eges. G = (V, E.ψ)
More informationIntroduction to Graphical Models
Introution to Grhil Moels Kenji Fukumizu The Institute of Sttistil Mthemtis Comuttionl Methoology in Sttistil Inferene II Introution n Review 2 Grhil Moels Rough Sketh Grhil moels Grh: G V E V: the set
More informationSolutions to Problem Set #1
CSE 233 Spring, 2016 Solutions to Prolem Set #1 1. The movie tse onsists of the following two reltions movie: title, iretor, tor sheule: theter, title The first reltion provies titles, iretors, n tors
More information1. For each of the following theorems, give a two or three sentence sketch of how the proof goes or why it is not true.
York University CSE 2 Unit 3. DFA Clsses Converting etween DFA, NFA, Regulr Expressions, nd Extended Regulr Expressions Instructor: Jeff Edmonds Don t chet y looking t these nswers premturely.. For ech
More informationGNFA GNFA GNFA GNFA GNFA
DFA RE NFA DFA -NFA REX GNFA Definition GNFA A generlize noneterministic finite utomton (GNFA) is grph whose eges re lele y regulr expressions, with unique strt stte with in-egree, n unique finl stte with
More informationCIT 596 Theory of Computation 1. Graphs and Digraphs
CIT 596 Theory of Computtion 1 A grph G = (V (G), E(G)) onsists of two finite sets: V (G), the vertex set of the grph, often enote y just V, whih is nonempty set of elements lle verties, n E(G), the ege
More informationChapter 4 Regular Grammar and Regular Sets. (Solutions / Hints)
C K Ngpl Forml Lnguges nd utomt Theory Chpter 4 Regulr Grmmr nd Regulr ets (olutions / Hints) ol. (),,,,,,,,,,,,,,,,,,,,,,,,,, (),, (c) c c, c c, c, c, c c, c, c, c, c, c, c, c c,c, c, c, c, c, c, c, c,
More informationLecture 6: Coding theory
Leture 6: Coing theory Biology 429 Crl Bergstrom Ferury 4, 2008 Soures: This leture loosely follows Cover n Thoms Chpter 5 n Yeung Chpter 3. As usul, some of the text n equtions re tken iretly from those
More informationImplication Graphs and Logic Testing
Implition Grphs n Logi Testing Vishwni D. Agrwl Jmes J. Dnher Professor Dept. of ECE, Auurn University Auurn, AL 36849 vgrwl@eng.uurn.eu www.eng.uurn.eu/~vgrwl Joint reserh with: K. K. Dve, ATI Reserh,
More informationMinimal DFA. minimal DFA for L starting from any other
Miniml DFA Among the mny DFAs ccepting the sme regulr lnguge L, there is exctly one (up to renming of sttes) which hs the smllest possile numer of sttes. Moreover, it is possile to otin tht miniml DFA
More informationLecture 8: Abstract Algebra
Mth 94 Professor: Pri Brtlett Leture 8: Astrt Alger Week 8 UCSB 2015 This is the eighth week of the Mthemtis Sujet Test GRE prep ourse; here, we run very rough-n-tumle review of strt lger! As lwys, this
More informationSubsequence Automata with Default Transitions
Susequene Automt with Defult Trnsitions Philip Bille, Inge Li Gørtz, n Freerik Rye Skjoljensen Tehnil University of Denmrk {phi,inge,fskj}@tu.k Astrt. Let S e string of length n with hrters from n lphet
More informationCS 2204 DIGITAL LOGIC & STATE MACHINE DESIGN SPRING 2014
S 224 DIGITAL LOGI & STATE MAHINE DESIGN SPRING 214 DUE : Mrh 27, 214 HOMEWORK III READ : Relte portions of hpters VII n VIII ASSIGNMENT : There re three questions. Solve ll homework n exm prolems s shown
More information= state, a = reading and q j
4 Finite Automt CHAPTER 2 Finite Automt (FA) (i) Derterministi Finite Automt (DFA) A DFA, M Q, q,, F, Where, Q = set of sttes (finite) q Q = the strt/initil stte = input lphet (finite) (use only those
More informationCoalgebra, Lecture 15: Equations for Deterministic Automata
Colger, Lecture 15: Equtions for Deterministic Automt Julin Slmnc (nd Jurrin Rot) Decemer 19, 2016 In this lecture, we will study the concept of equtions for deterministic utomt. The notes re self contined
More informationTheory of Computation Regular Languages. (NTU EE) Regular Languages Fall / 38
Theory of Computtion Regulr Lnguges (NTU EE) Regulr Lnguges Fll 2017 1 / 38 Schemtic of Finite Automt control 0 0 1 0 1 1 1 0 Figure: Schemtic of Finite Automt A finite utomton hs finite set of control
More informationGrammar. Languages. Content 5/10/16. Automata and Languages. Regular Languages. Regular Languages
5//6 Grmmr Automt nd Lnguges Regulr Grmmr Context-free Grmmr Context-sensitive Grmmr Prof. Mohmed Hmd Softwre Engineering L. The University of Aizu Jpn Regulr Lnguges Context Free Lnguges Context Sensitive
More informationCMPSCI 250: Introduction to Computation. Lecture #31: What DFA s Can and Can t Do David Mix Barrington 9 April 2014
CMPSCI 250: Introduction to Computtion Lecture #31: Wht DFA s Cn nd Cn t Do Dvid Mix Brrington 9 April 2014 Wht DFA s Cn nd Cn t Do Deterministic Finite Automt Forml Definition of DFA s Exmples of DFA
More informationFormal Languages and Automata
Moile Computing nd Softwre Engineering p. 1/5 Forml Lnguges nd Automt Chpter 2 Finite Automt Chun-Ming Liu cmliu@csie.ntut.edu.tw Deprtment of Computer Science nd Informtion Engineering Ntionl Tipei University
More informationNondeterminism and Nodeterministic Automata
Nondeterminism nd Nodeterministic Automt 61 Nondeterminism nd Nondeterministic Automt The computtionl mchine models tht we lerned in the clss re deterministic in the sense tht the next move is uniquely
More informationFinite state automata
Finite stte utomt Lecture 2 Model-Checking Finite-Stte Systems (untimed systems) Finite grhs with lels on edges/nodes set of nodes (sttes) set of edges (trnsitions) set of lels (lhet) Finite Automt, CTL,
More informationLecture 08: Feb. 08, 2019
4CS4-6:Theory of Computtion(Closure on Reg. Lngs., regex to NDFA, DFA to regex) Prof. K.R. Chowdhry Lecture 08: Fe. 08, 2019 : Professor of CS Disclimer: These notes hve not een sujected to the usul scrutiny
More informationMore on automata. Michael George. March 24 April 7, 2014
More on utomt Michel George Mrch 24 April 7, 2014 1 Automt constructions Now tht we hve forml model of mchine, it is useful to mke some generl constructions. 1.1 DFA Union / Product construction Suppose
More informationChapter 4 State-Space Planning
Leture slides for Automted Plnning: Theory nd Prtie Chpter 4 Stte-Spe Plnning Dn S. Nu CMSC 722, AI Plnning University of Mrylnd, Spring 2008 1 Motivtion Nerly ll plnning proedures re serh proedures Different
More informationCHAPTER 1 Regular Languages. Contents
Finite Automt (FA or DFA) CHAPTE 1 egulr Lnguges Contents definitions, exmples, designing, regulr opertions Non-deterministic Finite Automt (NFA) definitions, euivlence of NFAs nd DFAs, closure under regulr
More informationTheory of Computation Regular Languages
Theory of Computtion Regulr Lnguges Bow-Yw Wng Acdemi Sinic Spring 2012 Bow-Yw Wng (Acdemi Sinic) Regulr Lnguges Spring 2012 1 / 38 Schemtic of Finite Automt control 0 0 1 0 1 1 1 0 Figure: Schemtic of
More information18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106
8. Problem Set Due Wenesy, Ot., t : p.m. in - Problem Mony / Consier the eight vetors 5, 5, 5,..., () List ll of the one-element, linerly epenent sets forme from these. (b) Wht re the two-element, linerly
More informationLecture 2: Cayley Graphs
Mth 137B Professor: Pri Brtlett Leture 2: Cyley Grphs Week 3 UCSB 2014 (Relevnt soure mteril: Setion VIII.1 of Bollos s Moern Grph Theory; 3.7 of Gosil n Royle s Algeri Grph Theory; vrious ppers I ve re
More informationI. Theory of Automata II. Theory of Formal Languages III. Theory of Turing Machines
CI 3104 /Winter 2011: Introduction to Forml Lnguges Chter 13: Grmmticl Formt Chter 13: Grmmticl Formt I. Theory of Automt II. Theory of Forml Lnguges III. Theory of Turing Mchines Dr. Neji Zgui CI3104-W11
More informationModel Reduction of Finite State Machines by Contraction
Model Reduction of Finite Stte Mchines y Contrction Alessndro Giu Dip. di Ingegneri Elettric ed Elettronic, Università di Cgliri, Pizz d Armi, 09123 Cgliri, Itly Phone: +39-070-675-5892 Fx: +39-070-675-5900
More informationNondeterministic Finite Automata
Nondeterministi Finite utomt The Power of Guessing Tuesdy, Otoer 4, 2 Reding: Sipser.2 (first prt); Stoughton 3.3 3.5 S235 Lnguges nd utomt eprtment of omputer Siene Wellesley ollege Finite utomton (F)
More information1 Nondeterministic Finite Automata
1 Nondeterministic Finite Automt Suppose in life, whenever you hd choice, you could try oth possiilities nd live your life. At the end, you would go ck nd choose the one tht worked out the est. Then you
More informationState Minimization for DFAs
Stte Minimiztion for DFAs Red K & S 2.7 Do Homework 10. Consider: Stte Minimiztion 4 5 Is this miniml mchine? Step (1): Get rid of unrechle sttes. Stte Minimiztion 6, Stte is unrechle. Step (2): Get rid
More informationChapter Five: Nondeterministic Finite Automata. Formal Language, chapter 5, slide 1
Chpter Five: Nondeterministic Finite Automt Forml Lnguge, chpter 5, slide 1 1 A DFA hs exctly one trnsition from every stte on every symol in the lphet. By relxing this requirement we get relted ut more
More informationData Structures LECTURE 10. Huffman coding. Example. Coding: problem definition
Dt Strutures, Spring 24 L. Joskowiz Dt Strutures LEURE Humn oing Motivtion Uniquel eipherle oes Prei oes Humn oe onstrution Etensions n pplitions hpter 6.3 pp 385 392 in tetook Motivtion Suppose we wnt
More informationfor all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx
Applitions of Integrtion Are of Region Between Two Curves Ojetive: Fin the re of region etween two urves using integrtion. Fin the re of region etween interseting urves using integrtion. Desrie integrtion
More informationQuadratic reciprocity
Qudrtic recirocity Frncisc Bozgn Los Angeles Mth Circle Octoer 8, 01 1 Qudrtic Recirocity nd Legendre Symol In the eginning of this lecture, we recll some sic knowledge out modulr rithmetic: Definition
More informationRegular expressions, Finite Automata, transition graphs are all the same!!
CSI 3104 /Winter 2011: Introduction to Forml Lnguges Chpter 7: Kleene s Theorem Chpter 7: Kleene s Theorem Regulr expressions, Finite Automt, trnsition grphs re ll the sme!! Dr. Neji Zgui CSI3104-W11 1
More informationNecessary and sucient conditions for some two. Abstract. Further we show that the necessary conditions for the existence of an OD(44 s 1 s 2 )
Neessry n suient onitions for some two vrile orthogonl esigns in orer 44 C. Koukouvinos, M. Mitrouli y, n Jennifer Seerry z Deite to Professor Anne Penfol Street Astrt We give new lgorithm whih llows us
More informationSurds and Indices. Surds and Indices. Curriculum Ready ACMNA: 233,
Surs n Inies Surs n Inies Curriulum Rey ACMNA:, 6 www.mthletis.om Surs SURDS & & Inies INDICES Inies n surs re very losely relte. A numer uner (squre root sign) is lle sur if the squre root n t e simplifie.
More informationOn a Class of Planar Graphs with Straight-Line Grid Drawings on Linear Area
Journl of Grph Algorithms n Applitions http://jg.info/ vol. 13, no. 2, pp. 153 177 (2009) On Clss of Plnr Grphs with Stright-Line Gri Drwings on Liner Are M. Rezul Krim 1,2 M. Siur Rhmn 1 1 Deprtment of
More informationIs the system correct? Introduction to Formal Verification. Measuring SW Complexity. Design Complexity. Aniello Murano. Source Lines of Code (SLOC)
Introduction to Forml Verifiction Is the system correct? Aniello Murno Università degli studi di Noli Federico II Dirtimento di Scienze Fisiche Sezione di Informtic 22 Mggio, 2006 1 2 Design Comlexity
More informationMyhill-Nerode Theorem
Overview Myhill-Nerode Theorem Correspondence etween DA s nd MN reltions Cnonicl DA for L Computing cnonicl DFA Myhill-Nerode Theorem Deepk D Souz Deprtment of Computer Science nd Automtion Indin Institute
More informationF / x everywhere in some domain containing R. Then, + ). (10.4.1)
0.4 Green's theorem in the plne Double integrls over plne region my be trnsforme into line integrls over the bounry of the region n onversely. This is of prtil interest beuse it my simplify the evlution
More information5. (±±) Λ = fw j w is string of even lengthg [ 00 = f11,00g 7. (11 [ 00)± Λ = fw j w egins with either 11 or 00g 8. (0 [ ffl)1 Λ = 01 Λ [ 1 Λ 9.
Regulr Expressions, Pumping Lemm, Right Liner Grmmrs Ling 106 Mrch 25, 2002 1 Regulr Expressions A regulr expression descries or genertes lnguge: it is kind of shorthnd for listing the memers of lnguge.
More informationLogic, Set Theory and Computability [M. Coppenbarger]
14 Orer (Hnout) Definition 7-11: A reltion is qusi-orering (or preorer) if it is reflexive n trnsitive. A quisi-orering tht is symmetri is n equivlene reltion. A qusi-orering tht is nti-symmetri is n orer
More informationLecture 09: Myhill-Nerode Theorem
CS 373: Theory of Computtion Mdhusudn Prthsrthy Lecture 09: Myhill-Nerode Theorem 16 Ferury 2010 In this lecture, we will see tht every lnguge hs unique miniml DFA We will see this fct from two perspectives
More informationNondeterministic Automata vs Deterministic Automata
Nondeterministi Automt vs Deterministi Automt We lerned tht NFA is onvenient model for showing the reltionships mong regulr grmmrs, FA, nd regulr expressions, nd designing them. However, we know tht n
More informationHomework 3 Solutions
CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.
More informationMaximum size of a minimum watching system and the graphs achieving the bound
Mximum size of minimum wthing system n the grphs hieving the oun Tille mximum un système e ontrôle minimum et les grphes tteignnt l orne Dvi Auger Irène Chron Olivier Hury Antoine Lostein 00D0 Mrs 00 Déprtement
More informationA Lower Bound for the Length of a Partial Transversal in a Latin Square, Revised Version
A Lower Bound for the Length of Prtil Trnsversl in Ltin Squre, Revised Version Pooy Htmi nd Peter W. Shor Deprtment of Mthemtil Sienes, Shrif University of Tehnology, P.O.Bo 11365-9415, Tehrn, Irn Deprtment
More informationTotal score: /100 points
Points misse: Stuent's Nme: Totl sore: /100 points Est Tennessee Stte University Deprtment of Computer n Informtion Sienes CSCI 2710 (Trnoff) Disrete Strutures TEST 2 for Fll Semester, 2004 Re this efore
More informationParticle Physics. Michaelmas Term 2011 Prof Mark Thomson. Handout 3 : Interaction by Particle Exchange and QED. Recap
Prtile Physis Mihelms Term 2011 Prof Mrk Thomson g X g X g g Hnout 3 : Intertion y Prtile Exhnge n QED Prof. M.A. Thomson Mihelms 2011 101 Rep Working towrs proper lultion of ey n sttering proesses lnitilly
More informationNon-deterministic Finite Automata
Non-deterministic Finite Automt Eliminting non-determinism Rdoud University Nijmegen Non-deterministic Finite Automt H. Geuvers nd T. vn Lrhoven Institute for Computing nd Informtion Sciences Intelligent
More informationI 3 2 = I I 4 = 2A
ECE 210 Eletril Ciruit Anlysis University of llinois t Chigo 2.13 We re ske to use KCL to fin urrents 1 4. The key point in pplying KCL in this prolem is to strt with noe where only one of the urrents
More informationUnfoldings of Networks of Timed Automata
Unfolings of Networks of Time Automt Frnk Cssez Thoms Chtin Clue Jr Ptrii Bouyer Serge H Pierre-Alin Reynier Rennes, Deemer 3, 2008 Unfolings [MMilln 93] First efine for Petri nets Then extene to other
More information(9) P (x)u + Q(x)u + R(x)u =0
STURM-LIOUVILLE THEORY 7 2. Second order liner ordinry differentil equtions 2.1. Recll some sic results. A second order liner ordinry differentil eqution (ODE) hs the form (9) P (x)u + Q(x)u + R(x)u =0
More informationHarvard University Computer Science 121 Midterm October 23, 2012
Hrvrd University Computer Science 121 Midterm Octoer 23, 2012 This is closed-ook exmintion. You my use ny result from lecture, Sipser, prolem sets, or section, s long s you quote it clerly. The lphet is
More informationOn the Spectra of Bipartite Directed Subgraphs of K 4
On the Spetr of Biprtite Direte Sugrphs of K 4 R. C. Bunge, 1 S. I. El-Znti, 1, H. J. Fry, 1 K. S. Kruss, 2 D. P. Roerts, 3 C. A. Sullivn, 4 A. A. Unsiker, 5 N. E. Witt 6 1 Illinois Stte University, Norml,
More informationDiscrete Structures Lecture 11
Introdution Good morning. In this setion we study funtions. A funtion is mpping from one set to nother set or, perhps, from one set to itself. We study the properties of funtions. A mpping my not e funtion.
More informationHARMONIC BALANCE SOLUTION OF COUPLED NONLINEAR NON-CONSERVATIVE DIFFERENTIAL EQUATION
GNIT J. nglesh Mth. So. ISSN - HRMONIC LNCE SOLUTION OF COUPLED NONLINER NON-CONSERVTIVE DIFFERENTIL EQUTION M. Sifur Rhmn*, M. Mjeur Rhmn M. Sjeur Rhmn n M. Shmsul lm Dertment of Mthemtis Rjshhi University
More informationDuke Math Meet
Duke Mth Meet 01-14 Power Round Qudrtic Residues nd Prime Numers For integers nd, we write to indicte tht evenly divides, nd to indicte tht does not divide For exmle, 4 nd 4 Let e rime numer An integer
More informationConvert the NFA into DFA
Convert the NF into F For ech NF we cn find F ccepting the sme lnguge. The numer of sttes of the F could e exponentil in the numer of sttes of the NF, ut in prctice this worst cse occurs rrely. lgorithm:
More informationCentrum voor Wiskunde en Informatica REPORTRAPPORT. Supervisory control for nondeterministic systems
Centrum voor Wiskunde en Informtic REPORTRAPPORT Supervisory control for nondeterministic systems A. Overkmp Deprtment of Opertions Reserch, Sttistics, nd System Theory BS-R9411 1994 Supervisory Control
More informationHow many proofs of the Nebitt s Inequality?
How mny roofs of the Neitt s Inequlity? Co Minh Qung. Introdution On Mrh, 90, Nesitt roosed the following rolem () The ove inequlity is fmous rolem. There re mny eole interested in nd solved (). In this
More informationC. C^mpenu, K. Slom, S. Yu upper boun of mn. So our result is tight only for incomplete DF's. For restricte vlues of m n n we present exmples of DF's
Journl of utomt, Lnguges n Combintorics u (v) w, x{y c OttovonGuerickeUniversitt Mgeburg Tight lower boun for the stte complexity of shue of regulr lnguges Cezr C^mpenu, Ki Slom Computing n Informtion
More informationCSCI 340: Computational Models. Kleene s Theorem. Department of Computer Science
CSCI 340: Computtionl Models Kleene s Theorem Chpter 7 Deprtment of Computer Science Unifiction In 1954, Kleene presented (nd proved) theorem which (in our version) sttes tht if lnguge cn e defined y ny
More informationNow we must transform the original model so we can use the new parameters. = S max. Recruits
MODEL FOR VARIABLE RECRUITMENT (ontinue) Alterntive Prmeteriztions of the pwner-reruit Moels We n write ny moel in numerous ifferent ut equivlent forms. Uner ertin irumstnes it is onvenient to work with
More informationWatson-Crick local languages and Watson-Crick two dimensional local languages
Interntionl Journl of Mthemtics nd Soft Comuting Vol.5 No.. (5) 65-7. ISSN Print : 49 338 ISSN Online: 39 55 Wtson-Crick locl lnguges nd Wtson-Crick two dimensionl locl lnguges Mry Jemim Smuel nd V.R.
More informationCS 301. Lecture 04 Regular Expressions. Stephen Checkoway. January 29, 2018
CS 301 Lecture 04 Regulr Expressions Stephen Checkowy Jnury 29, 2018 1 / 35 Review from lst time NFA N = (Q, Σ, δ, q 0, F ) where δ Q Σ P (Q) mps stte nd n lphet symol (or ) to set of sttes We run n NFA
More informationFinite Automata Theory and Formal Languages TMV027/DIT321 LP4 2018
Finite Automt Theory nd Forml Lnguges TMV027/DIT321 LP4 2018 Lecture 10 An Bove April 23rd 2018 Recp: Regulr Lnguges We cn convert between FA nd RE; Hence both FA nd RE ccept/generte regulr lnguges; More
More informationCS261: A Second Course in Algorithms Lecture #5: Minimum-Cost Bipartite Matching
CS261: A Seon Course in Algorithms Leture #5: Minimum-Cost Biprtite Mthing Tim Roughgren Jnury 19, 2016 1 Preliminries Figure 1: Exmple of iprtite grph. The eges {, } n {, } onstitute mthing. Lst leture
More informationComputing on rings by oblivious robots: a unified approach for different tasks
Computing on rings y olivious roots: unifie pproh for ifferent tsks Ginlorenzo D Angelo, Griele Di Stefno, Alfreo Nvrr, Niols Nisse, Krol Suhn To ite this version: Ginlorenzo D Angelo, Griele Di Stefno,
More informationFinite Automata-cont d
Automt Theory nd Forml Lnguges Professor Leslie Lnder Lecture # 6 Finite Automt-cont d The Pumping Lemm WEB SITE: http://ingwe.inghmton.edu/ ~lnder/cs573.html Septemer 18, 2000 Exmple 1 Consider L = {ww
More information#A42 INTEGERS 11 (2011) ON THE CONDITIONED BINOMIAL COEFFICIENTS
#A42 INTEGERS 11 (2011 ON THE CONDITIONED BINOMIAL COEFFICIENTS Liqun To Shool of Mthemtil Sienes, Luoyng Norml University, Luoyng, Chin lqto@lynuedun Reeived: 12/24/10, Revised: 5/11/11, Aepted: 5/16/11,
More informationarxiv: v2 [math.co] 31 Oct 2016
On exlue minors of onnetivity 2 for the lss of frme mtrois rxiv:1502.06896v2 [mth.co] 31 Ot 2016 Mtt DeVos Dryl Funk Irene Pivotto Astrt We investigte the set of exlue minors of onnetivity 2 for the lss
More informationNon-deterministic Finite Automata
Non-deterministic Finite Automt From Regulr Expressions to NFA- Eliminting non-determinism Rdoud University Nijmegen Non-deterministic Finite Automt H. Geuvers nd J. Rot Institute for Computing nd Informtion
More informationTypes of Finite Automata. CMSC 330: Organization of Programming Languages. Comparing DFAs and NFAs. Comparing DFAs and NFAs (cont.) Finite Automata 2
CMSC 330: Orgniztion of Progrmming Lnguges Finite Automt 2 Types of Finite Automt Deterministic Finite Automt () Exctly one sequence of steps for ech string All exmples so fr Nondeterministic Finite Automt
More informationA Primer on Continuous-time Economic Dynamics
Eonomis 205A Fll 2008 K Kletzer A Primer on Continuous-time Eonomi Dnmis A Liner Differentil Eqution Sstems (i) Simplest se We egin with the simple liner first-orer ifferentil eqution The generl solution
More informationSpeech Recognition Lecture 2: Finite Automata and Finite-State Transducers
Speech Recognition Lecture 2: Finite Automt nd Finite-Stte Trnsducers Eugene Weinstein Google, NYU Cournt Institute eugenew@cs.nyu.edu Slide Credit: Mehryr Mohri Preliminries Finite lphet, empty string.
More informationSymmetrical Components 1
Symmetril Components. Introdution These notes should e red together with Setion. of your text. When performing stedy-stte nlysis of high voltge trnsmission systems, we mke use of the per-phse equivlent
More informationDiscrete Structures, Test 2 Monday, March 28, 2016 SOLUTIONS, VERSION α
Disrete Strutures, Test 2 Mondy, Mrh 28, 2016 SOLUTIONS, VERSION α α 1. (18 pts) Short nswer. Put your nswer in the ox. No prtil redit. () Consider the reltion R on {,,, d with mtrix digrph of R.. Drw
More informationQUADRATIC RESIDUES MATH 372. FALL INSTRUCTOR: PROFESSOR AITKEN
QUADRATIC RESIDUES MATH 37 FALL 005 INSTRUCTOR: PROFESSOR AITKEN When is n integer sure modulo? When does udrtic eution hve roots modulo? These re the uestions tht will concern us in this hndout 1 The
More informationThe DOACROSS statement
The DOACROSS sttement Is prllel loop similr to DOALL, ut it llows prouer-onsumer type of synhroniztion. Synhroniztion is llowe from lower to higher itertions sine it is ssume tht lower itertions re selete
More informationRegular languages refresher
Regulr lnguges refresher 1 Regulr lnguges refresher Forml lnguges Alphet = finite set of letters Word = sequene of letter Lnguge = set of words Regulr lnguges defined equivlently y Regulr expressions Finite-stte
More informationThe University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER MACHINES AND THEIR LANGUAGES ANSWERS
The University of ottinghm SCHOOL OF COMPUTR SCIC A LVL 2 MODUL, SPRIG SMSTR 2015 2016 MACHIS AD THIR LAGUAGS ASWRS Time llowed TWO hours Cndidtes my omplete the front over of their nswer ook nd sign their
More information