14 The Boole/Stone algebra of sets

Size: px
Start display at page:

Download "14 The Boole/Stone algebra of sets"

Transcription

1 14 The Ble/Stne algebra f sets Lattces and Blean algebras. Gven a set A, the subsets f A admt the fllwng smple and famlar peratns n them: (ntersectn), (unn) and - (cmplementatn). If X, Y A, then X Y, X Y are als subsets f A. Wth A fxed (and suppressed n the ntatn), we wrte -X = A - X fr any X A ; f curse, -X A agan. Intersectn and unn are bnary peratns n (A), - s a unary peratn n (A) : : (A) (A) (A), : (A) (A) (A), - : (A) (A). Of curse, ntersectn and unn are defned fr any number f arguments; usng the bnary versns repeatedly, we can reprduce fnte ntersectns and unn, except the empty ntersectn and the empty unn. Fr the empty ntersectn, we take the set A tself; fr the empty unn, the empty set. What s the justfcatn? Fr any famly (A) f subsets f A, we have = {x A : fr all X, x X} and = {x A : fr sme X, x X}. Nte that the expressn fr clause " A " ; the expressn fr p. 3. s the same as that n Sectn 3, page 35 except fr the has a smlar dfference t the earler expressn n 146

2 Fr the unn, there s n actual dfference n meanng; the ld and the new expressns gve the same set. Fr the ntersectn, the same s true except fr the empty famly ; the ld expressn gves V, a nn-set; the new expressn gves A tself. Of curse, the unn f the empty famly, accrdng t the general frmula, s the empty set. It ges wthut sayng that X Y = {X, Y}, X Y = {X, Y}. The cmpste bject ( (A);,, -, A, ) (1) s an example f what we call an algebra: a set (n ths case (A) ), called the underlyng set f the algebra, wth certan partcular peratns n t (n ths case, the bnary peratns,, the unary peratn -, and the -ary peratns A, : -ary peratns are dstngushed elements f the underlyng set). Any bject f the frm (B ;,,, 1, ) wth B a set,, bth B B B, :B B, and 1, B, s an algebra smlar t (1). Speakng n very general terms, we wll seek, and at least partly fnd, prpertes f algebras f the frm (1) that dstngush them amng all the algebras smlar t them; the result wll be the ntn f Blean algebra. Fr future reference, let's say that when we dente an algebra by a sngle letter, say B, dentes the underlyng set f B. Ths, f curse, cnflcts wth the ntatn fr "cardnalty"; t s advsable t use #A fr the cardnalty f the set A when the underlyng set f an algebra s als t be used. B Let us frst lk at the basc peratns frm anther pnt f vew, namely the cntext f the pset ( (A), ). We have, fr any (A), that s the largest subset Y f A fr whch Y X fr all X : X fr all X, and f Y X fr all X, then Y ; and smlarly, 147

3 s the least subset Y f A fr whch X Y fr all X : X fr all X, and f X Y fr all X, then Y. (verfy ths statement). In general, n any pset (B, ), and fr any famly B f elements f B, a lwer bund f s any y B such that y x fr all x ; the greatest lwer bund (g.l.b), r nfmum (nf) f (f t exsts!) s the maxmum element f the set L f all lwer bunds f : y L such that y y fr all y L. (Nte that the requrement s mre than t say that y be a maxmal element f L!). The g.l.b. f s dented by ; des nt necessarly exst (n an arbtrary pset (B, ) ), but f t des, t s unquely determned by the defntn. The ntns f upper bund, least upper bund (l.u.b., supremum, sup), wth the ntatn, are defned smlarly ("dually"). [In the cntext f rdnals and well-rderngs, we have already used lub's extensvely.] Nw, ntce that what we sad abve abut ntersectns and unns amunts t ths that n the pset ( (A), ), =., exst fr all (A), and n fact =, It s wrth remarkng that the defntns f nf (sup) can be put n the fllwng frm: y y x fr all x ; y x y fr all x ; y ranges ver all the elements f the pset. Nte als that s the maxmum element f the pset (f such exsts); s the mnmum element (f exsts). We wrte 1 fr the maxmum element, fr the mnmum element (f they exst). A pset (B, ) s called a lattce f, exst fr all fnte sets B. Thus, n a lattce (B, ), there always are a maxmum element 1, a mnmum element ; mrever, fr any x, y B, x y = def {x, y}, x y = {x, y} always exst. The def 148

4 pset ( (A), ) s a lattce; n fact, t s what s called a cmplete lattce, meanng that, exst fr all B = (A). Nte the fllwng laws that always hld n any lattce: x y = y x, x y = y x (cmmutatve laws) (x y) z = x (y z), (x y) z = x (y z) (asscatve laws) x x = x, x x = x (demptent laws) x (x y) = x, x (x y) = x (absrptn laws) x 1 = x, x 1 = 1, x =, x = x. Exercses. () Verfy that the abve hld n any lattce. () Assume an algebra (B,,, 1, ) satsfyng the abve laws. Shw that there s a unque partal rderng n B that makes (B, ) a lattce n such a way that the gven,, 1, becme the lattce peratns. () Suppse that n a pset, exsts fr all sets f elements f the pset. Shw that then als always exsts. Shw that f, n ths assertn, we restrct t be a fnte set n bth ccurrences, then the resultng statement s nt always true any mre. Exercses () and () say that the cncept f lattce can be gven a purely "peratnal" ("algebrac") frmulatn. The set-theretc cmplement -X = A - X als can be gven a "lattce" descrptn. The set Y = -X s dstngushed amng all the subsets f A by the fllwng tw prpertes: Y X = A and Y X =, (verfy!). In a lattce, y s a cmplement f x f y x = 1 and y x =. In a general lattce, the cmplement f an element may nt exst, and t s als pssble that there are tw dfferent cmplements f the same element. 149

5 A partcular prperty f ( (A), ) as a lattce s that t s dstrbutve. A lattce (B, ) s dstrbutve f (x y) z = (x z) (y z) fr all x, y, z B. Indeed, the dstrbutve law s famlar fr ( (A), ) (see Assgnment 1). Exercses. (v) Shw that n a dstrbutve lattce, the dual f the dstrbutve law, that s (x y) z = (x z) (y z) hlds t. (v) Shw that n a dstrbutve lattce, every element has at mst ne cmplement. (v) Shw that any lnear rderng wth a mnmal and a maxmal element s a dstrbutve lattce. A Blean algebra s a dstrbutve lattce n whch every element has a cmplement. Of curse, ( (A), ) s a Blean algebra. One partcular Blean algebra, ( (1), ), plays a central rle n ur thery. Ths ne has tw elements: and 1 (rght?) ; nte that (1) = 2. The bnary Blean peratns are tabulated as fllws: In addtn, we have (1) =, () = 1. We call ths algebra the tw-element Blean algebra, and dente t by 2. Let us pnt ut that 2 s als cnsdered t be the algebra f truth values t=true and 15

6 f=false ; t s dentfed wth 1, f wth. Under ths dentfcatn, the abve peratns, and becme the lgcal peratns f cnjunctn ("and"), dsjunctn ("r"), and negatn ("nt"). Wth any pset B = ( B, ), we have ts ppste, B. The underlyng set f B s the same, B, as f B ; the rderng n B s the ppste f that n B : x y y x. B def It s clear that B s defned s a pset t. Mrever, t s als clear that the nf f a set n the sense f B s the same as the sup f n the sense f B, and vce versa. Thus, f B s a lattce, s s B then B. Mrever, as exercse (v) abve shws, f B s a dstrbutve lattce, s dstrbutve t. Als, the defntn f cmplement shws that the ntns f cmplement n B and B are the same. Brefly put, the ntn f "lattce", "dstrbutve lattce", and "Blean algebra" are each self-dual cncepts: f a pset falls n any f these categres, s des ts ppste Sme algebrac deas. Nte that the ntn f Blean algebra s defned n terms f the peratns,,, 1 and by denttes : the laws descrbng lattces, the dstrbutve law, and the laws defnng the cmplement. In general, an dentty, fr any knd f algebra, s an equalty f tw terms bult up f the basc peratns f the algebra, requred t hld fr all values f the varables nvlved. In the defntn f Blean algebra, we have fund sme partcular denttes that hld n the set-algebra ( (A),,,, 1, ) ; have we fund them all? As t s, ths questn s nt very ntellgent snce, e.g., 1 x = x s an dentty nt lsted abve that bvusly hlds n the set-algebra, and n fact, n all lattces, as a cnsequence f tw f the axms (why?). Hwever, we may ask: (*) s t the case that all denttes that hld n the set-algebras are cnsequences f the Blean axms, that s, are true n all Blean algebras? 151

7 Put ths way, the questn amunts t askng whether we have fund, n the Blean axms, a suffcent bass t deduce all denttes frmulated n terms,, -, 1, that are true fr sets; f the answer s "n", then there s anther, stll undscvered, essentally new dentty cncernng these set-peratns. We wll gve an affrmatve answer t the questn just asked, by deducng t frm a mre abstract therem t be stated sn. Example. The s-called De-Mrgan law: (x y) = ( x) ( y) hlds n set-algebras; n fact, t hlds, n all Blean algebras (exercse (v)). A hmmrphsm f lattces L and M, n ntatn f:l M, s a mappng f: L M between the underlyng sets that preserves the lattce peratns: f(x y) = f(x) f(y), f(x y) = f(x) f(y), f(1) = 1, f() =. These equaltes are requred t hld fr all x, y L ; f curse, n the left sdes,,, 1, refer t the lattce peratns f L, n the rght t thse f M. An embeddng f lattces s a 1-1 hmmrphsm; an smrphsm s a bjectve hmmrphsm. Exercses. (v) A lattce hmmrphsm f between Blean algebras s a Blean hmmrphsm n the sense that t als preserves cmplements: f( x) = f(x). (x) Fnd a Blean embeddng f ( (2), ) nt ( (3), ). 152

8 x y (x) Any lattce hmmrphsm preserves the partal rderng relatn: fx fy. If L, M are lattces, and f s a pset smrphsm f:( L, ) ( M, ) (.e., f s a bjectn f: L M, and x y fx fy (x, y L ) ), then f s a lattce smrphsm as well. Hwever, a pset-hmmrphsm between lattces (map preservng the rder) s nt necessarly a lattce hmmrphsm. There are the fllwng pnts t be made abut hmmrphsms and embeddngs: (1) gven a (Blean) hmmrphsm f:b C, and a Blean term t(x) bult up f varables and the symbls fr the Blean peratns, then fr any values b frm B fr the varables x we have f(t B (b)) = t C (fb) ; that s, f we frst evaluate t at b n B, then apply f, we btan the same value as when we frst apply f t each f the values n b, and then evaluate t n C at thse arguments; and (2) f an dentty s(x) = t(x) hlds n C (fr all values n C ), and f:b C s an embeddng, then the same dentty als hlds n B. (1) s a cnsequence f the defntn f "hmmrphsm"; nte that the "hmmrphsm" s defned n such a way that the assertn hld n case t s a smple term (has just ne peratn mentned n t); the general statement s prved by "nductn". (2) s a cnsequence f (1) as fllws. Suppse s(x) = t(x) hlds n C, and f:b C s an embeddng. T shw that the same dentty hlds n B, let b be arbtrary elements t evaluate the varables x. Then f(s B (b)) = s C (fb) 153

9 and f(t B (b)) = t C (fb). Snce we have s C (fb) = t C (fb) by the assumptn that the dentty hlds n C, we get B B B B that f(s (b)) = f(t (b)). Snce f s 1-1, t fllws that s (b) = t (b) as desred. Put brefly, (2) says that any dentty that hlds n an algebra hlds n any ther that can be embedded nt the gven ne. Exercse. (x) Suppse the lattce L can be embedded nt a dstrbutve lattce. Then L tself s dstrbutve. Gven a famly L I f psets, ther Cartesan prduct, L, s the pset L whse I underlyng set s L = L, and fr whch I f g f() g() fr all I. Here, f and g are arbtrary elements f L I (remember that the latter s the set f certan functns wth dman I ); n the left sde, s the rderng f L I t be defned; n the rght, refers t the rderng gven n (each) L. Exercse. (x) Verfy that L s ndeed a pset; f each L s a lattce, then s s I L ; f each L s a dstrbutve lattce, r a Blean algebra, then s s L. In fact, I I the lattce (Blean) peratns n L are defned pntwse: e.g., I (f g)() = f() g(). 154

10 (x) The prjectn mappng π : L L j j I f f(j) ne fr each j I, s a lattce hmmrphsm. (xv) Turnng t Cartesan prducts f sets, let us nte the fllwng "mappng prperty" f Cartesan prducts: fr any sets A fr I, and any further set B : the maps f:b A are n a ne-t-ne crrespndence wth famles f the I frm f :B A I. Indeed, the crrespndence, n ne drectn, asscates wth f the famly where f = π f (wth π defned as n (x) ). (xv) Nw, f the A and B are lattces (say), then the crrespndence f () gves a ne-t-ne crrespndence between hmmrphsms f:b A I and famles f hmmrphsms f the frm f :B A I. Put n anther way, t gve a hmmrphsm f:b A I s the same as t gve a famly f hmmrphsms f :B A I. When n the prduct A all the algebras A are the same, say A, we wrte A I I fr the prduct A ; A I s a pwer (the I th pwer) f A. Nte that the underlyng set f the I algebra A I, A I, s the same as I A, where n the latter the ntatn f Sectn 3, p.36 s used. The reasn why we talk abut prducts f algebras s because the pwer-set algebras ( (A), ) are all, essentally, pwers f 2, the tw-element algebra, and ths turns ut t be a useful way f lkng at pwer-set algebras. Recall the bjectn 155

11 (A) A 2 X char X. (1) A Nw, (A) and 2 are the respectve underlyng sets f the algebras ( (A), ) and A 2. We have that the mappng n (1) s an smrphsm ( (A), ) A 2. Exercse (xv): verfy ths mprtant fact. Cmbnng the last fact wth what we learned abve abut mappngs nt a prduct-algebra, we btan fr any lattce L, and any set A, the lattce hmmrphsms f:l ( (A), ) are n a ne-t-ne crrespndence wth famles f hmmrphsms f the frm f :L a 2 a A. Mrever, n ths crrespndence, f s an embeddng (1-1) f and nly f, fr every par (x, y) f dstnct elements x y f L, there s a A such that f a (x) f a (y). Exercse (xv). Verfy the last tw dsplayed assertns. Stne representatn therem fr dstrbutve lattces (and Blean algebras). Any dstrbutve lattce (hence, any Blean algebra) has an embeddng nt a pwer-set algebra. Equvalently, f L a dstrbutve lattce, and x y are arbtrary elements f L, then there s a 2-valued hmmrphsm f:l 2 such that f(x) f(y). The prf f the Stne representatn therem s the subject f the next subsectn. 156

12 Exercse (xv). Verfy that the tw versn f the therem are ndeed equvalent. Nte that the dstrbutvty cndtn n the lattce s necessary. Nte that the questn asked under (*) (at the begnnng f the present subsectn 14.2) has, as a cnsequence f the Stne representatn therem, an affrmatve answer Prme flters and ultraflters We nw set ut t prve the Stne representatn therem. Frst, we nvestgate the ntn f a 2-valued lattce hmmrphsm f:l 2. Any such f s gven by the set F = {x L : f(x)=1} ; namely, f s then the characterstc functn f X, f = char F : L 2. The questn s what prpertes F must have n rder fr char F t be a lattce hmmrphsm. We ntrduce sme standard termnlgy. Let L be a lattce. F L s a flter n L f () F 1 L F, () F F s clsed upward: x F, x y y F (x, y L ) [as a cnsequence, n () F, t wuld have been enugh t requre that F be nn-empty], and () F f x and y bth belng t F, then s des x y (x, y L ). Exercse (xx). Verfy that F L s a flter ff char F s an rder-preservng map L 2, and t als preserves and 1 [fr ths, we say that f s a meet-semlattce hmmrphsm]. A flter F n L s prme f (v) F [equvalently, F L PF L ; we say that F s a prper flter] and (v) whenever x y F, then ether x F, r y F (x, y L PF ). Exercses. (xx) The prme flters n a lattce L are n a ne-t-ne crrespndence wth the hmmrphsms L 2. (xx) Let F be a flter n the Blean algebra B. Then F s a prme flter n B ff fr any x B, exactly ne f x, x belngs t F. 157

13 In the case f a Blean algebra, we may say "ultraflter" t mean "prme flter". In vew f the refrmulatn f the ntn f 2-valued hmmrphsm as prme flter, and n vew f secnd frm f the Stne representatn therem (at the end f the secnd sectn), we nw see that the Stne representatn therem s equvalent t the fllwng statement: Fr any dstrbutve lattce L, and any par f dstnct elements x y f L, there s a prme flter P f L fr whch ne f x, y belngs t P, and the ther f x, y des nt belng t P. We are gng t shw a strnger statement, whch s als mre specfc cncernng whch f the tw gven elements can be made t belng, and whch nt t belng, t the prme flter. The strnger versn can then be used t btan ther nterestng cnsequences. The man feature f the strnger versn s a certan symmetry wth respect t "dualzng", that s, takng the ppste f the lattce n questn. Cnsder a lattce L. An deal f L s, by defntn, the same thng as a flter n L. Unravelng ths, we btan that an deal s a subset I f L such that () I, () I I L I s clsed dwnward: x I, y x y I (x, y L ), and () f bth x and y I belng t I, then s des x y (x, y L ). A prme deal f L s a prme flter f L, that s, an deal I fr whch (v) PI 1 L I, and (v) PI whenever x y I, then ether x I r y I. Prme Flter Exstence Therem (PFET). Gven any flter F and any deal I n the dstrbutve lattce L such that F and I are dsjnt: F I =, there s at least ne prme flter P n L whch cntans F as a subset and whch s dsjnt frm I : F P, I P =. Befre we turn t the prf f the PFET, let us see hw the latest frmulatn f the Stne representatn therem fllws frm t. Suppse x, y L, and x y. Then ether x y, r y x (r bth). Say, we have x y. Nw, cnsder the sets F = x = {u L : u x}, and I = y = {v L : v y}. We mmedately see def def 158

14 that x s a flter, and y s an deal (exercse). Als, they are dsjnt: f we had u x y, then x u and u y, and thus x y wuld be the case. The PFET gves a prme flter P wth x P and y P =. Then, snce x x and y y, we have that x P and y P as desred. The prf f the PFET s an applcatn f Zrn's lemma. T emphasze the character f ths prf, we slate a part f t as a separate statement. Crtern fr a prme flter. Let F be a flter, I an deal n the dstrbutve lattce L. Then any flter n L whch s maxmal amng thse flters that cntan F and dsjnt frm I s prme. Prf f the PFET frm the Crtern. Assumng the truth f the Crtern, we prceed as expected. Cnsder the set f all flters n L that cntan F as a subset and are dsjnt frm I, partally rdered by nclusn,. We apply Zrn's lemma t the pset (, ). We clam that f s any nn-empty chan n, then. Indeed, t s clear that cndtn () fr flters hlds, because s nn-empty; () s als clear. T see (), f F F F x, y, then there are F, F wth x F, y F ; snce s a chan, ether F F, r F F ; we cnclude that bth x and y belng ether t F r t F, hence, s des x y (snce F, F are flters!); but F, F are bth subsets f, thus x y belngs t as was t be shwn. As t I, f a I belnged t, then t wuld belng t an F, cntradctng F and the defntn f. The clam s verfed. The cndtn f Zrn's lemma, namely that each chan have an upper bund s almst verfed: fr each nn-empty chan, take F as an upper bund. s such an upper bund. Fr the empty chan, By Zrn's lemma, there s a maxmal element P f (, ). By the Crtern, any such maxmal element, that s, any flter maxmal amng thse flters that cntan F frm I s prme. Ths cmpletes the prf. and dsjnt Prf f the Crtern. Let P be any flter maxmal amng thse flters that cntan F and dsjnt frm I. We verfy the cndtns (v) and (v) fr P. Snce I s an PF PF 159

15 deal, I. Snce I P =, t fllws that P ; ths s (v). L L PF T see (v), assume x PF y P, and assume, cntrary t what we want, that x P and y P. We nw cnstruct a flter P[x] cntanng P {x} as a subset; we put P[x] = {u L : u s x fr sme s P}. Indeed, P[x] s a flter: cndtns () F and () F are clear; and f u, v bth belng t P[x], then there are s, t P wth u s x and v t x ; t fllws that, fr r = s t, we have u r x and v r x, and hence, u v r x (why?); ths shws that u v P[x]. Snce x P, we have P P[x]. By the maxmalty f P amng thse flters that cntan F and are dsjnt frm I, and snce clearly F P[x] (because F P ), t must be that P[x] s nt dsjnt frm I ; there s a I P[x]. The defntn f P[x] gves that there s s P such that s x a. Dng the same wth y as wth x, we get b I and t P such that t y b. Let c = a b and r = s t. Then, f curse, r x c and r y c, (why?); als, c I and r P, snce I s an deal and P s a flter. Nw [and ths s the ne pnt where we use that L s dstrbutve!], 16

16 r (x y) = (r x) (r y) c dstrbutve law means "sup" Snce we assumed that x y P, and P s a flter, t fllws that c P, n cntradctn t the fact that P I =. Ths cntradctn shws that, ndeed, x y P mples that ether x P, y P, shwng that P s a prme flter. Ths cmpletes the prf f the PFET. Exercse. (xx) A prncpal flter s ne f the frm x (fr the latter ntatn, see abve). Shw that the prncpal ultraflters f (P(A), ) are n a ne-t-ne crrespndence wth the elements f the set A. (xx) The set I rat = {q : q 1 and q s ratnal}, wth the standard rderng f the ratnal (real) numbers s a dstrbutve lattce. Gve a descrptn n famlar terms f the nn-prncpal flters f (I, ). rat (xxv) What can we say abut prme flters f a ttal rderng wth and 1 as a dstrbutve lattce? (xxv) If U and V are prme flters (ultraflters) n a Blean algebra, then U V mples U = V. * (xxv) Cnversely, f n a dstrbutve lattce L, we have that P Q mples that P = Q whenever P, Q are prme flters, then L s a Blean algebra. (xxv) Apply the PFET t shw the fllwng. Let A be any nn-empty set, and assume that s a famly f subsets f A wth the prperty that the ntersectn f any fntely many sets n s nn-empty. Shw that there s an ultraflter f ( (A), ) whch cntans. (xxv) The set A s fnte f and nly f all ultraflters f ( (A), ) are prncpal. 161

CONVEX COMBINATIONS OF ANALYTIC FUNCTIONS

CONVEX COMBINATIONS OF ANALYTIC FUNCTIONS rnat. J. Math. & Math. S. Vl. 6 N. (983) 33534 335 ON THE RADUS OF UNVALENCE OF CONVEX COMBNATONS OF ANALYTC FUNCTONS KHALDA. NOOR, FATMA M. ALOBOUD and NAEELA ALDHAN Mathematcs Department Scence Cllege

More information

A New Method for Solving Integer Linear. Programming Problems with Fuzzy Variables

A New Method for Solving Integer Linear. Programming Problems with Fuzzy Variables Appled Mathematcal Scences, Vl. 4, 00, n. 0, 997-004 A New Methd fr Slvng Integer Lnear Prgrammng Prblems wth Fuzzy Varables P. Pandan and M. Jayalakshm Department f Mathematcs, Schl f Advanced Scences,

More information

Week 2. This week, we covered operations on sets and cardinality.

Week 2. This week, we covered operations on sets and cardinality. Week 2 Ths week, we covered operatons on sets and cardnalty. Defnton 0.1 (Correspondence). A correspondence between two sets A and B s a set S contaned n A B = {(a, b) a A, b B}. A correspondence from

More information

A Note on Equivalences in Measuring Returns to Scale

A Note on Equivalences in Measuring Returns to Scale Internatnal Jurnal f Busness and Ecnmcs, 2013, Vl. 12, N. 1, 85-89 A Nte n Equvalences n Measurng Returns t Scale Valentn Zelenuk Schl f Ecnmcs and Centre fr Effcenc and Prductvt Analss, The Unverst f

More information

FINITE BOOLEAN ALGEBRA. 1. Deconstructing Boolean algebras with atoms. Let B = <B,,,,,0,1> be a Boolean algebra and c B.

FINITE BOOLEAN ALGEBRA. 1. Deconstructing Boolean algebras with atoms. Let B = <B,,,,,0,1> be a Boolean algebra and c B. FINITE BOOLEAN ALGEBRA 1. Decnstructing Blean algebras with atms. Let B = be a Blean algebra and c B. The ideal generated by c, (c], is: (c] = {b B: b c} The filter generated by c, [c), is:

More information

a b a In case b 0, a being divisible by b is the same as to say that

a b a In case b 0, a being divisible by b is the same as to say that Secton 6.2 Dvsblty among the ntegers An nteger a ε s dvsble by b ε f there s an nteger c ε such that a = bc. Note that s dvsble by any nteger b, snce = b. On the other hand, a s dvsble by only f a = :

More information

Affine transformations and convexity

Affine transformations and convexity Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/

More information

Wp/Lmin. Wn/Lmin 2.5V

Wp/Lmin. Wn/Lmin 2.5V UNIVERITY OF CALIFORNIA Cllege f Engneerng Department f Electrcal Engneerng and Cmputer cences Andre Vladmrescu Hmewrk #7 EEC Due Frday, Aprl 8 th, pm @ 0 Cry Prblem #.5V Wp/Lmn 0.0V Wp/Lmn n ut Wn/Lmn.5V

More information

Shell Stiffness for Diffe ent Modes

Shell Stiffness for Diffe ent Modes Engneerng Mem N 28 February 0 979 SUGGESTONS FOR THE DEFORMABLE SUBREFLECTOR Sebastan vn Herner Observatns wth the present expermental versn (Engneerng Dv nternal Reprt 09 July 978) have shwn that a defrmable

More information

SIMULATION OF THREE PHASE THREE LEG TRANSFORMER BEHAVIOR UNDER DIFFERENT VOLTAGE SAG TYPES

SIMULATION OF THREE PHASE THREE LEG TRANSFORMER BEHAVIOR UNDER DIFFERENT VOLTAGE SAG TYPES SIMULATION OF THREE PHASE THREE LEG TRANSFORMER BEHAVIOR UNDER DIFFERENT VOLTAGE SAG TYPES Mhammadreza Dlatan Alreza Jallan Department f Electrcal Engneerng, Iran Unversty f scence & Technlgy (IUST) e-mal:

More information

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

COMPLEX NUMBERS AND QUADRATIC EQUATIONS COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not

More information

element k Using FEM to Solve Truss Problems

element k Using FEM to Solve Truss Problems sng EM t Slve Truss Prblems A truss s an engneerng structure cmpsed straght members, a certan materal, that are tpcall pn-ned at ther ends. Such members are als called tw-rce members snce the can nl transmt

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

Reproducing kernel Hilbert spaces. Nuno Vasconcelos ECE Department, UCSD

Reproducing kernel Hilbert spaces. Nuno Vasconcelos ECE Department, UCSD Reprucng ernel Hlbert spaces Nun Vascncels ECE Department UCSD Classfcatn a classfcatn prblem has tw tpes f varables X -vectr f bservatns features n the wrl Y - state class f the wrl Perceptrn: classfer

More information

Section 3: Detailed Solutions of Word Problems Unit 1: Solving Word Problems by Modeling with Formulas

Section 3: Detailed Solutions of Word Problems Unit 1: Solving Word Problems by Modeling with Formulas Sectn : Detaled Slutns f Wrd Prblems Unt : Slvng Wrd Prblems by Mdelng wth Frmulas Example : The factry nvce fr a mnvan shws that the dealer pad $,5 fr the vehcle. If the stcker prce f the van s $5,, hw

More information

Homology groups of disks with holes

Homology groups of disks with holes Hmlgy grups f disks with hles THEOREM. Let p 1,, p k } be a sequence f distinct pints in the interir unit disk D n where n 2, and suppse that fr all j the sets E j Int D n are clsed, pairwise disjint subdisks.

More information

An Introduction to Morita Theory

An Introduction to Morita Theory An Introducton to Morta Theory Matt Booth October 2015 Nov. 2017: made a few revsons. Thanks to Nng Shan for catchng a typo. My man reference for these notes was Chapter II of Bass s book Algebrac K-Theory

More information

Chapter Summary. Mathematical Induction Strong Induction Recursive Definitions Structural Induction Recursive Algorithms

Chapter Summary. Mathematical Induction Strong Induction Recursive Definitions Structural Induction Recursive Algorithms Chapter 5 1 Chapter Summary Mathematical Inductin Strng Inductin Recursive Definitins Structural Inductin Recursive Algrithms Sectin 5.1 3 Sectin Summary Mathematical Inductin Examples f Prf by Mathematical

More information

Design of Analog Integrated Circuits

Design of Analog Integrated Circuits Desgn f Analg Integrated Crcuts I. Amplfers Desgn f Analg Integrated Crcuts Fall 2012, Dr. Guxng Wang 1 Oerew Basc MOS amplfer structures Cmmn-Surce Amplfer Surce Fllwer Cmmn-Gate Amplfer Desgn f Analg

More information

Linear Plus Linear Fractional Capacitated Transportation Problem with Restricted Flow

Linear Plus Linear Fractional Capacitated Transportation Problem with Restricted Flow Amercan urnal f Operatns Research,,, 58-588 Publshed Onlne Nvember (http://www.scrp.rg/urnal/ar) http://dx.d.rg/.46/ar..655 Lnear Plus Lnear Fractnal Capactated Transprtatn Prblem wth Restrcted Flw Kavta

More information

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens THE CHINESE REMAINDER THEOREM KEITH CONRAD We should thank the Chnese for ther wonderful remander theorem. Glenn Stevens 1. Introducton The Chnese remander theorem says we can unquely solve any par of

More information

REAL ANALYSIS I HOMEWORK 1

REAL ANALYSIS I HOMEWORK 1 REAL ANALYSIS I HOMEWORK CİHAN BAHRAN The questons are from Tao s text. Exercse 0.0.. If (x α ) α A s a collecton of numbers x α [0, + ] such that x α

More information

12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA. 4. Tensor product

12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA. 4. Tensor product 12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA Here s an outlne of what I dd: (1) categorcal defnton (2) constructon (3) lst of basc propertes (4) dstrbutve property (5) rght exactness (6) localzaton

More information

DIFFERENTIAL FORMS BRIAN OSSERMAN

DIFFERENTIAL FORMS BRIAN OSSERMAN DIFFERENTIAL FORMS BRIAN OSSERMAN Dfferentals are an mportant topc n algebrac geometry, allowng the use of some classcal geometrc arguments n the context of varetes over any feld. We wll use them to defne

More information

FINITELY-GENERATED MODULES OVER A PRINCIPAL IDEAL DOMAIN

FINITELY-GENERATED MODULES OVER A PRINCIPAL IDEAL DOMAIN FINITELY-GENERTED MODULES OVER PRINCIPL IDEL DOMIN EMMNUEL KOWLSKI Throughout ths note, s a prncpal deal doman. We recall the classfcaton theorem: Theorem 1. Let M be a fntely-generated -module. (1) There

More information

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space.

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space. Lnear, affne, and convex sets and hulls In the sequel, unless otherwse specfed, X wll denote a real vector space. Lnes and segments. Gven two ponts x, y X, we defne xy = {x + t(y x) : t R} = {(1 t)x +

More information

Appendix B. Criterion of Riemann-Stieltjes Integrability

Appendix B. Criterion of Riemann-Stieltjes Integrability Appendx B. Crteron of Remann-Steltes Integrablty Ths note s complementary to [R, Ch. 6] and [T, Sec. 3.5]. The man result of ths note s Theorem B.3, whch provdes the necessary and suffcent condtons for

More information

READING STATECHART DIAGRAMS

READING STATECHART DIAGRAMS READING STATECHART DIAGRAMS Figure 4.48 A Statechart diagram with events The diagram in Figure 4.48 shws all states that the bject plane can be in during the curse f its life. Furthermre, it shws the pssible

More information

Math 217 Fall 2013 Homework 2 Solutions

Math 217 Fall 2013 Homework 2 Solutions Math 17 Fall 013 Homework Solutons Due Thursday Sept. 6, 013 5pm Ths homework conssts of 6 problems of 5 ponts each. The total s 30. You need to fully justfy your answer prove that your functon ndeed has

More information

Spectral Graph Theory and its Applications September 16, Lecture 5

Spectral Graph Theory and its Applications September 16, Lecture 5 Spectral Graph Theory and ts Applcatons September 16, 2004 Lecturer: Danel A. Spelman Lecture 5 5.1 Introducton In ths lecture, we wll prove the followng theorem: Theorem 5.1.1. Let G be a planar graph

More information

20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The first idea is connectedness.

20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The first idea is connectedness. 20. Mon, Oct. 13 What we have done so far corresponds roughly to Chapters 2 & 3 of Lee. Now we turn to Chapter 4. The frst dea s connectedness. Essentally, we want to say that a space cannot be decomposed

More information

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg prnceton unv. F 17 cos 521: Advanced Algorthm Desgn Lecture 7: LP Dualty Lecturer: Matt Wenberg Scrbe: LP Dualty s an extremely useful tool for analyzng structural propertes of lnear programs. Whle there

More information

Polynomials. 1 More properties of polynomials

Polynomials. 1 More properties of polynomials Polynomals 1 More propertes of polynomals Recall that, for R a commutatve rng wth unty (as wth all rngs n ths course unless otherwse noted), we defne R[x] to be the set of expressons n =0 a x, where a

More information

Approach: (Equilibrium) TD analysis, i.e., conservation eqns., state equations Issues: how to deal with

Approach: (Equilibrium) TD analysis, i.e., conservation eqns., state equations Issues: how to deal with Schl f Aerspace Chemcal D: Mtvatn Prevus D Analyss cnsdered systems where cmpstn f flud was frzen fxed chemcal cmpstn Chemcally eactng Flw but there are numerus stuatns n prpulsn systems where chemcal

More information

Exercise Solutions to Real Analysis

Exercise Solutions to Real Analysis xercse Solutons to Real Analyss Note: References refer to H. L. Royden, Real Analyss xersze 1. Gven any set A any ɛ > 0, there s an open set O such that A O m O m A + ɛ. Soluton 1. If m A =, then there

More information

Feedback Principle :-

Feedback Principle :- Feedback Prncple : Feedback amplfer s that n whch a part f the utput f the basc amplfer s returned back t the nput termnal and mxed up wth the nternal nput sgnal. The sub netwrks f feedback amplfer are:

More information

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP C O L L O Q U I U M M A T H E M A T I C U M VOL. 80 1999 NO. 1 FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP BY FLORIAN K A I N R A T H (GRAZ) Abstract. Let H be a Krull monod wth nfnte class

More information

Conduction Heat Transfer

Conduction Heat Transfer Cnductn Heat Transfer Practce prblems A steel ppe f cnductvty 5 W/m-K has nsde and utsde surface temperature f C and 6 C respectvely Fnd the heat flw rate per unt ppe length and flux per unt nsde and per

More information

Chapter 3, Solution 1C.

Chapter 3, Solution 1C. COSMOS: Cmplete Onlne Slutns Manual Organzatn System Chapter 3, Slutn C. (a If the lateral surfaces f the rd are nsulated, the heat transfer surface area f the cylndrcal rd s the bttm r the tp surface

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

Chem 204A, Fall 2004, Mid-term (II)

Chem 204A, Fall 2004, Mid-term (II) Frst tw letters f yur last name Last ame Frst ame McGll ID Chem 204A, Fall 2004, Md-term (II) Read these nstructns carefully befre yu start tal me: 2 hurs 50 mnutes (6:05 PM 8:55 PM) 1. hs exam has ttal

More information

Chapter 7. Systems 7.1 INTRODUCTION 7.2 MATHEMATICAL MODELING OF LIQUID LEVEL SYSTEMS. Steady State Flow. A. Bazoune

Chapter 7. Systems 7.1 INTRODUCTION 7.2 MATHEMATICAL MODELING OF LIQUID LEVEL SYSTEMS. Steady State Flow. A. Bazoune Chapter 7 Flud Systems and Thermal Systems 7.1 INTODUCTION A. Bazune A flud system uses ne r mre fluds t acheve ts purpse. Dampers and shck absrbers are eamples f flud systems because they depend n the

More information

Physic 231 Lecture 33

Physic 231 Lecture 33 Physc 231 Lecture 33 Man pnts f tday s lecture: eat and heat capacty: Q cm Phase transtns and latent heat: Q Lm ( ) eat flw Q k 2 1 t L Examples f heat cnductvty, R values fr nsulatrs Cnvectn R L / k Radatn

More information

A new Type of Fuzzy Functions in Fuzzy Topological Spaces

A new Type of Fuzzy Functions in Fuzzy Topological Spaces IOSR Jurnal f Mathematics (IOSR-JM e-issn: 78-578, p-issn: 39-765X Vlume, Issue 5 Ver I (Sep - Oct06, PP 8-4 wwwisrjurnalsrg A new Type f Fuzzy Functins in Fuzzy Tplgical Spaces Assist Prf Dr Munir Abdul

More information

Introduction to Electronic circuits.

Introduction to Electronic circuits. Intrductn t Electrnc crcuts. Passve and Actve crcut elements. Capactrs, esstrs and Inductrs n AC crcuts. Vltage and current dvders. Vltage and current surces. Amplfers, and ther transfer characterstc.

More information

NOTE ON APPELL POLYNOMIALS

NOTE ON APPELL POLYNOMIALS NOTE ON APPELL POLYNOMIALS I. M. SHEFFER An interesting characterizatin f Appell plynmials by means f a Stieltjes integral has recently been given by Thrne. 1 We prpse t give a secnd such representatin,

More information

2 More examples with details

2 More examples with details Physcs 129b Lecture 3 Caltech, 01/15/19 2 More examples wth detals 2.3 The permutaton group n = 4 S 4 contans 4! = 24 elements. One s the dentty e. Sx of them are exchange of two objects (, j) ( to j and

More information

Concircular π-vector Fields and Special Finsler Spaces *

Concircular π-vector Fields and Special Finsler Spaces * Adances n Pure Matematcs 03 3 8-9 ttp://dx.d.rg/0.436/apm.03.3040 Publsed Onlne Marc 03 (ttp://www.scrp.rg/urnal/apm) Cncrcular π-vectr Felds and Specal Fnsler Spaces * Nabl L. Yussef Amr Sleman 3 Department

More information

55:041 Electronic Circuits

55:041 Electronic Circuits 55:04 Electrnc Crcuts Feedback & Stablty Sectns f Chapter 2. Kruger Feedback & Stablty Cnfguratn f Feedback mplfer S S S S fb Negate feedback S S S fb S S S S S β s the feedback transfer functn Implct

More information

5 The Rational Canonical Form

5 The Rational Canonical Form 5 The Ratonal Canoncal Form Here p s a monc rreducble factor of the mnmum polynomal m T and s not necessarly of degree one Let F p denote the feld constructed earler n the course, consstng of all matrces

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

MAXIMIN CLUSTERS FOR NEAR-REPLICATE REGRESSION LACK OF FIT TESTS. BY FORREST R. MILLER, JAMES W. NEILL AND BRIAN W. SHERFEY Kansas State University

MAXIMIN CLUSTERS FOR NEAR-REPLICATE REGRESSION LACK OF FIT TESTS. BY FORREST R. MILLER, JAMES W. NEILL AND BRIAN W. SHERFEY Kansas State University The Annals f Statstcs 1998, Vl. 6, N. 4, 14111433 MAXIMIN CLUSTERS FOR NEAR-REPLICATE REGRESSION LACK OF FIT TESTS BY FORREST R. MILLER, JAMES W. NEILL AND BRIAN W. SHERFEY Kansas State Unversty T assess

More information

Conservation of Energy

Conservation of Energy Cnservatn f Energy Equpment DataStud, ruler 2 meters lng, 6 n ruler, heavy duty bench clamp at crner f lab bench, 90 cm rd clamped vertcally t bench clamp, 2 duble clamps, 40 cm rd clamped hrzntally t

More information

Lecture 7: Gluing prevarieties; products

Lecture 7: Gluing prevarieties; products Lecture 7: Glung prevaretes; products 1 The category of algebrac prevaretes Proposton 1. Let (f,ϕ) : (X,O X ) (Y,O Y ) be a morphsm of algebrac prevaretes. If U X and V Y are affne open subvaretes wth

More information

A proposition is a statement that can be either true (T) or false (F), (but not both).

A proposition is a statement that can be either true (T) or false (F), (but not both). 400 lecture nte #1 [Ch 2, 3] Lgic and Prfs 1.1 Prpsitins (Prpsitinal Lgic) A prpsitin is a statement that can be either true (T) r false (F), (but nt bth). "The earth is flat." -- F "March has 31 days."

More information

V. Electrostatics Lecture 27a: Diffuse charge at electrodes

V. Electrostatics Lecture 27a: Diffuse charge at electrodes V. Electrstatcs Lecture 27a: Dffuse charge at electrdes Ntes by MIT tudent We have talked abut the electrc duble structures and crrespndng mdels descrbng the n and ptental dstrbutn n the duble layer. Nw

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

Distribution det x s on p-adic matrices

Distribution det x s on p-adic matrices January 30, 207 Dstruton det x s on p-adc matrces aul arrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ Let e a p-adc feld wth ntegers o, local parameter, and resdue feld cardnalty q. Let A

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

The Second Eigenvalue of Planar Graphs

The Second Eigenvalue of Planar Graphs Spectral Graph Theory Lecture 20 The Second Egenvalue of Planar Graphs Danel A. Spelman November 11, 2015 Dsclamer These notes are not necessarly an accurate representaton of what happened n class. The

More information

Transient Conduction: Spatial Effects and the Role of Analytical Solutions

Transient Conduction: Spatial Effects and the Role of Analytical Solutions Transent Cnductn: Spatal Effects and the Rle f Analytcal Slutns Slutn t the Heat Equatn fr a Plane Wall wth Symmetrcal Cnvectn Cndtns If the lumped capactance apprxmatn can nt be made, cnsderatn must be

More information

First day August 1, Problems and Solutions

First day August 1, Problems and Solutions FOURTH INTERNATIONAL COMPETITION FOR UNIVERSITY STUDENTS IN MATHEMATICS July 30 August 4, 997, Plovdv, BULGARIA Frst day August, 997 Problems and Solutons Problem. Let {ε n } n= be a sequence of postve

More information

Spring 2002 Lecture #17

Spring 2002 Lecture #17 1443-51 Sprng 22 Lecture #17 r. Jaehn Yu 1. Cndtns fr Equlbrum 2. Center f Gravty 3. Elastc Prpertes f Slds Yung s dulus Shear dulus ulk dulus Tday s Hmewrk Assgnment s the Hmewrk #8!!! 2 nd term eam n

More information

ENGI 4421 Probability & Statistics

ENGI 4421 Probability & Statistics Lecture Ntes fr ENGI 441 Prbablty & Statstcs by Dr. G.H. Gerge Asscate Prfessr, Faculty f Engneerng and Appled Scence Seventh Edtn, reprnted 018 Sprng http://www.engr.mun.ca/~ggerge/441/ Table f Cntents

More information

Problem Set 5 Solutions - McQuarrie Problems 3.20 MIT Dr. Anton Van Der Ven

Problem Set 5 Solutions - McQuarrie Problems 3.20 MIT Dr. Anton Van Der Ven Prblem Set 5 Slutns - McQuarre Prblems 3.0 MIT Dr. Antn Van Der Ven Fall Fall 003 001 Prblem 3-4 We have t derve the thermdynamc prpertes f an deal mnatmc gas frm the fllwng: = e q 3 m = e and q = V s

More information

On cyclic of Steiner system (v); V=2,3,5,7,11,13

On cyclic of Steiner system (v); V=2,3,5,7,11,13 On cyclc of Stener system (v); V=,3,5,7,,3 Prof. Dr. Adl M. Ahmed Rana A. Ibraham Abstract: A stener system can be defned by the trple S(t,k,v), where every block B, (=,,,b) contans exactly K-elementes

More information

Exercises H /OOA> f Wo AJoTHS l^»-l S. m^ttrt /A/ ?C,0&L6M5 INFERENCE FOR DISTRIBUTIONS OF CATEGORICAL DATA. tts^e&n tai-ns 5 2%-cas-hews^, 27%

Exercises H /OOA> f Wo AJoTHS l^»-l S. m^ttrt /A/ ?C,0&L6M5 INFERENCE FOR DISTRIBUTIONS OF CATEGORICAL DATA. tts^e&n tai-ns 5 2%-cas-hews^, 27% /A/ mttrt?c,&l6m5 INFERENCE FOR DISTRIBUTIONS OF CATEGORICAL DATA Exercses, nuts! A cmpany clams that each batch f ttse&n ta-ns 5 2%-cas-hews, 27% almnds, 13% macadama nuts, and 8% brazl nuts. T test ths

More information

Math 594. Solutions 1

Math 594. Solutions 1 Math 594. Solutons 1 1. Let V and W be fnte-dmensonal vector spaces over a feld F. Let G = GL(V ) and H = GL(W ) be the assocated general lnear groups. Let X denote the vector space Hom F (V, W ) of lnear

More information

Graph Reconstruction by Permutations

Graph Reconstruction by Permutations Graph Reconstructon by Permutatons Perre Ille and Wllam Kocay* Insttut de Mathémathques de Lumny CNRS UMR 6206 163 avenue de Lumny, Case 907 13288 Marselle Cedex 9, France e-mal: lle@ml.unv-mrs.fr Computer

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

ME2142/ME2142E Feedback Control Systems. Modelling of Physical Systems The Transfer Function

ME2142/ME2142E Feedback Control Systems. Modelling of Physical Systems The Transfer Function Mdellng Physcal Systems The Transer Functn Derental Equatns U Plant Y In the plant shwn, the nput u aects the respnse the utput y. In general, the dynamcs ths respnse can be descrbed by a derental equatn

More information

Introduction to Spacetime Geometry

Introduction to Spacetime Geometry Intrductin t Spacetime Gemetry Let s start with a review f a basic feature f Euclidean gemetry, the Pythagrean therem. In a twdimensinal crdinate system we can relate the length f a line segment t the

More information

CONSTRUCTING STATECHART DIAGRAMS

CONSTRUCTING STATECHART DIAGRAMS CONSTRUCTING STATECHART DIAGRAMS The fllwing checklist shws the necessary steps fr cnstructing the statechart diagrams f a class. Subsequently, we will explain the individual steps further. Checklist 4.6

More information

Exploiting vector space properties for the global optimization of process networks

Exploiting vector space properties for the global optimization of process networks Exptng vectr space prpertes fr the gbal ptmzatn f prcess netwrks Juan ab Ruz Ignac Grssmann Enterprse Wde Optmzatn Meetng March 00 Mtvatn - The ptmzatn f prcess netwrks s ne f the mst frequent prblems

More information

Subset Topological Spaces and Kakutani s Theorem

Subset Topological Spaces and Kakutani s Theorem MOD Natural Neutrosophc Subset Topologcal Spaces and Kakutan s Theorem W. B. Vasantha Kandasamy lanthenral K Florentn Smarandache 1 Copyrght 1 by EuropaNova ASBL and the Authors Ths book can be ordered

More information

Fixed points of IA-endomorphisms of a free metabelian Lie algebra

Fixed points of IA-endomorphisms of a free metabelian Lie algebra Proc. Indan Acad. Sc. (Math. Sc.) Vol. 121, No. 4, November 2011, pp. 405 416. c Indan Academy of Scences Fxed ponts of IA-endomorphsms of a free metabelan Le algebra NAIME EKICI 1 and DEMET PARLAK SÖNMEZ

More information

Physics 107 HOMEWORK ASSIGNMENT #20

Physics 107 HOMEWORK ASSIGNMENT #20 Physcs 107 HOMEWORK ASSIGNMENT #0 Cutnell & Jhnsn, 7 th etn Chapter 6: Prblems 5, 7, 74, 104, 114 *5 Cncept Smulatn 6.4 prves the ptn f explrng the ray agram that apples t ths prblem. The stance between

More information

_J _J J J J J J J J _. 7 particles in the blue state; 3 particles in the red state: 720 configurations _J J J _J J J J J J J J _

_J _J J J J J J J J _. 7 particles in the blue state; 3 particles in the red state: 720 configurations _J J J _J J J J J J J J _ Dsrder and Suppse I have 10 partcles that can be n ne f tw states ether the blue state r the red state. Hw many dfferent ways can we arrange thse partcles amng the states? All partcles n the blue state:

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also

More information

Self-complementing permutations of k-uniform hypergraphs

Self-complementing permutations of k-uniform hypergraphs Dscrete Mathematcs Theoretcal Computer Scence DMTCS vol. 11:1, 2009, 117 124 Self-complementng permutatons of k-unform hypergraphs Artur Szymańsk A. Paweł Wojda Faculty of Appled Mathematcs, AGH Unversty

More information

MATH 5707 HOMEWORK 4 SOLUTIONS 2. 2 i 2p i E(X i ) + E(Xi 2 ) ä i=1. i=1

MATH 5707 HOMEWORK 4 SOLUTIONS 2. 2 i 2p i E(X i ) + E(Xi 2 ) ä i=1. i=1 MATH 5707 HOMEWORK 4 SOLUTIONS CİHAN BAHRAN 1. Let v 1,..., v n R m, all lengths v are not larger than 1. Let p 1,..., p n [0, 1] be arbtrary and set w = p 1 v 1 + + p n v n. Then there exst ε 1,..., ε

More information

CALCULUS CLASSROOM CAPSULES

CALCULUS CLASSROOM CAPSULES CALCULUS CLASSROOM CAPSULES SESSION S86 Dr. Sham Alfred Rartan Valley Communty College salfred@rartanval.edu 38th AMATYC Annual Conference Jacksonvlle, Florda November 8-, 202 2 Calculus Classroom Capsules

More information

and problem sheet 2

and problem sheet 2 -8 and 5-5 problem sheet Solutons to the followng seven exercses and optonal bonus problem are to be submtted through gradescope by :0PM on Wednesday th September 08. There are also some practce problems,

More information

Modelli Clamfim Equazione del Calore Lezione ottobre 2014

Modelli Clamfim Equazione del Calore Lezione ottobre 2014 CLAMFIM Bologna Modell 1 @ Clamfm Equazone del Calore Lezone 17 15 ottobre 2014 professor Danele Rtell danele.rtell@unbo.t 1/24? Convoluton The convoluton of two functons g(t) and f(t) s the functon (g

More information

where a is any ideal of R. Lemma 5.4. Let R be a ring. Then X = Spec R is a topological space Moreover the open sets

where a is any ideal of R. Lemma 5.4. Let R be a ring. Then X = Spec R is a topological space Moreover the open sets 5. Schemes To defne schemes, just as wth algebrac varetes, the dea s to frst defne what an affne scheme s, and then realse an arbtrary scheme, as somethng whch s locally an affne scheme. The defnton of

More information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

arxiv: v1 [math.co] 1 Mar 2014

arxiv: v1 [math.co] 1 Mar 2014 Unon-ntersectng set systems Gyula O.H. Katona and Dánel T. Nagy March 4, 014 arxv:1403.0088v1 [math.co] 1 Mar 014 Abstract Three ntersecton theorems are proved. Frst, we determne the sze of the largest

More information

On the smoothness and the totally strong properties for nearness frames

On the smoothness and the totally strong properties for nearness frames Int. Sc. Technol. J. Namba Vol 1, Issue 1, 2013 On the smoothness and the totally strong propertes for nearness frames Martn. M. Mugoch Department of Mathematcs, Unversty of Namba 340 Mandume Ndemufayo

More information

PRIMES 2015 reading project: Problem set #3

PRIMES 2015 reading project: Problem set #3 PRIMES 2015 readng project: Problem set #3 page 1 PRIMES 2015 readng project: Problem set #3 posted 31 May 2015, to be submtted around 15 June 2015 Darj Grnberg The purpose of ths problem set s to replace

More information

CHAPTER 3 ANALYSIS OF KY BOOST CONVERTER

CHAPTER 3 ANALYSIS OF KY BOOST CONVERTER 70 CHAPTER 3 ANALYSIS OF KY BOOST CONERTER 3.1 Intrductn The KY Bst Cnverter s a recent nventn made by K.I.Hwu et. al., (2007), (2009a), (2009b), (2009c), (2010) n the nn-slated DC DC cnverter segment,

More information

Homework Notes Week 7

Homework Notes Week 7 Homework Notes Week 7 Math 4 Sprng 4 #4 (a Complete the proof n example 5 that s an nner product (the Frobenus nner product on M n n (F In the example propertes (a and (d have already been verfed so we

More information

Circuits Op-Amp. Interaction of Circuit Elements. Quick Check How does closing the switch affect V o and I o?

Circuits Op-Amp. Interaction of Circuit Elements. Quick Check How does closing the switch affect V o and I o? Crcuts Op-Amp ENGG1015 1 st Semester, 01 Interactn f Crcut Elements Crcut desgn s cmplcated by nteractns amng the elements. Addng an element changes vltages & currents thrughut crcut. Example: clsng a

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

DIFFERENTIAL SCHEMES

DIFFERENTIAL SCHEMES DIFFERENTIAL SCHEMES RAYMOND T. HOOBLER Dedcated to the memory o Jerry Kovacc 1. schemes All rngs contan Q and are commutatve. We x a d erental rng A throughout ths secton. 1.1. The topologcal space. Let

More information

Admissibility Conditions and Asymptotic Behavior of Strongly Regular Graphs

Admissibility Conditions and Asymptotic Behavior of Strongly Regular Graphs Admissibility Cnditins and Asympttic Behavir f Strngly Regular Graphs VASCO MOÇO MANO Department f Mathematics University f Prt Oprt PORTUGAL vascmcman@gmailcm LUÍS ANTÓNIO DE ALMEIDA VIEIRA Department

More information

Restricted Lie Algebras. Jared Warner

Restricted Lie Algebras. Jared Warner Restrcted Le Algebras Jared Warner 1. Defntons and Examples Defnton 1.1. Let k be a feld of characterstc p. A restrcted Le algebra (g, ( ) [p] ) s a Le algebra g over k and a map ( ) [p] : g g called

More information

MULTIPLICATIVE FUNCTIONS: A REWRITE OF ANDREWS CHAPTER 6

MULTIPLICATIVE FUNCTIONS: A REWRITE OF ANDREWS CHAPTER 6 MULTIPLICATIVE FUNCTIONS: A REWRITE OF ANDREWS CHAPTER 6 In these notes we offer a rewrte of Andrews Chapter 6. Our am s to replace some of the messer arguments n Andrews. To acheve ths, we need to change

More information

SL n (F ) Equals its Own Derived Group

SL n (F ) Equals its Own Derived Group Internatonal Journal of Algebra, Vol. 2, 2008, no. 12, 585-594 SL n (F ) Equals ts Own Derved Group Jorge Macel BMCC-The Cty Unversty of New York, CUNY 199 Chambers street, New York, NY 10007, USA macel@cms.nyu.edu

More information