Interval Valued Neutrosophic Soft Topological Spaces
|
|
- Marjorie George
- 5 years ago
- Views:
Transcription
1 8 Interval Valued Neutrosoph Soft Topologal njan Mukherjee Mthun Datta Florentn Smarandah Department of Mathemats Trpura Unversty Suryamannagar gartala-7990 Trpura Indamal: Department of Mathemats Trpura Unversty Suryamannagar gartala-7990 Trpura Indamal: 3 Department of Mathemats Unversty of New Mexo Gallup USmal: bstrat In ths paper we ntrodue the onept of nterval valued neutrosoph soft topologal spae together wth nterval valued neutrosoph soft fner and nterval valued neutrosoph soft oarser topology We also defne nterval valued neutrosoph nteror and loser of an nterval valued neutrosoph soft set Some theorems and examples are tes Interval valued neutrosoph soft subspae topology are studed Some examples and theorems regardng ths onept are presented Keywords: Soft set nterval valued neutrosoph set nterval valued neutrosoph soft set nterval valued neutrosoph soft topologal spae Introduton In 999 Molodtsov [9] ntrodued the onept of soft set theory whh s ompletely new approah for modelng unertanty In ths paper [9] Molodtsov establshed the fundamental results of ths new theory and suessfully appled the soft set theory nto several dretons Maj et al [7] defned and studed several bas notons of soft set theory n 003 Pe and Mao [] ktas and Cagman [] and l et al [] mproved the work of Maj et al [7] The ntutonst fuzzy set s ntrodued by tanaasov [4] as a generalzaton of fuzzy set [5] where he added degree of non-membershp wth degree of membershp Neutrosoph set ntrodued by F Smarandahe n 995 [] Smarandahe [3] ntrodued the onept of neutrosoph set whh s a mathematal tool for handlng problems nvolvng mprese ndetermnay and nonstant data Maj [8] ombned neutrosoph set and soft set and establshed some operatons on these sets Wang et al [4] ntrodued nterval neutrosoph sets Del [6] ntrodued the onept of nterval-valued neutrosoph soft sets In ths paper we form a topologal struture on nterval valued neutrosoph soft sets and establsh some propertes of nterval valued neutrosoph soft topologal spae wth supportng proofs and examples Prelmnares In ths seton we reall some bas notons relevant to soft sets nterval-valued neutrosoph sets and nterval-valued neutrosoph soft sets Defnton : [9] Let U be an ntal unverse and be PU denotes the power set of U a set of parameters Let and Then the par overu where f s a mappng gven by f : PU f s alled a soft set Defnton : [3] neutrosoph set on the unverse of dsourse U s defned as x x x x x U where 0 are funtons suh that the U ondton: x U x x x 0 3 s satsfed Here x x x represent the truthmembershp ndetermnay-membershp and falstymembershp respetvely of the element x U From phlosophal pont of vew the neutrosoph set takes the value from real standard or non-standard subsets of 0 But n real lfe applaton n sentf and engneerng problems t s dffult to use neutrosoph set wth value from real standard or non-standard subset of 0 Hene we onsder the neutrosoph set whh takes the value from the subset of 0 Defnton 3: [4] n nterval valued neutrosoph set on the unverse of dsourse U s defned as x x x x x U where U Int 0 are funtons suh that the njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
2 9 ondton: x U 0 sup x sup x sup x 3 s satsfed In real lfe applatons t s dffult to use nterval valued neutrosoph set wth nterval-value from real standard or non-standard subset of Int 0 Hene we onsder the nterval valued neutrosoph set whh takes the nterval-value from the subset of Int 0 (where Int 0 denotes the set of all losed sub ntervals of 0 ) The set of all nterval valued neutrosoph sets on U s denoted by IVNS(U) Defnton 4: [6] Let U be an unverse set be a set of parameters and Let IVNs(U) denotes the set of all nterval valued neutrosoph sets of U Then the par f s alled an nterval valued neutrosoph soft set (IVNSs n short) over U where f s a mappng gven by f IVNsU The olleton of all nterval valued neutrosoph soft sets over U s denoted by IVNSs(U) Defnton 5: [6] Let U be a unverse set and be a f g B IVNSs U where set of parameters Let f IVNsU s defned by ( ) x x x x f a x U f a f a f a and g B IVNsU s defned by g( b) x x x x x U g b g b g b where x x x x x x Int 0 U Then f s alled nterval valued neutrosoph subset of f a f a f a g b g b g b for x () gb (denoted by f g B x ge x x ge x x ge x e x U x ge x nf sup x sup x sup ) f B and Where ff nf g e and sup g e x ff g e nf f e nf g e sup g e x nf and nf and g e ff ge sup ge () Ther unon denoted by f g B h C (say) s an nterval valued neutrosoph soft set overu where C B h C IVNS U s defned by and for e C h e h e h e h e x x x x x U where for x U x B x h e ge x B x ge x B x B x h e ge x B x ge x B x B x h e ge x B x ge x B () Ther nterseton denoted by f g B h C (say) s an nterval valued neutrosoph soft set of overu where C B and for e C h C IVNS U s defned by x x x x h e h e h e h e x U where for xu and e C x x x x x x he ge he ge and x x x h e g e (v) The omplement of f denoted by f s an nterval valued neutrosoph soft set over U and s defned as f f f IVNS U s defned by where x x sup x nf x x f a x U f a f a f a f a for a Defnton 6:[56] n IVNSs f over the unverse U s sad to be unverse IVNSs wth respet to f x x 00 x 00 f a f a f a x U a It s denoted by I njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
3 0 Defnton 7: n IVNSs f over the unverse U s sad to be null IVNSs wth respet to f x 00 f a x f a x f a x U a It s denoted by 3 Interval Valued Neutrosoph Soft Topologal In ths seton we gve the defnton of nterval valued neutrosoph soft topologal spaes wth some examples and results We also defne dsrete and ndsrete nterval valued neutrosoph soft topologal spae along wth nterval valued neutrosoph soft fner and oarser topology Let U be an unverse set be the set of U parameters be the set of all subsets of U IVNs(U) be the set of all nterval valued neutrosoph sets n U and IVSNs(U;) be the famly of all nterval valued neutrosoph soft sets over U va parameters n Defnton 3: Let be an element of IVNSs(U;) be the olleton of all nterval valued neutrosoph soft subsets of sub famly of s alled an nterval valued neutrosoph soft topology (n short IVNS-topology) on f the followng axoms are satsfed: () () k k f : k K f kk () If g h then g h The trplet s alled nterval valued neutrosoph soft topologal spae (n short IVNStopologal spae) over The members of are alled open IVNS sets (or smply open sets) Here : IVNS ( U) s defned as e x 00 : x U e xampl: Let U u u u3 e e e3 e4 e e e The tabular representaton of 3 gven by U e e u ([58][35][7]) ([47][3][3]) u ([47][34][]) ([69][][]) u 3 ([5][0][36]) ([68][4][3]) ([39][0][0]) ([48][][05]) ([49][3][4]) Table:Tabular representaton of The tabular representaton of s gven by U e e u ([00][][]) ([00][][]) u ([00][][]) ([00][][]) u 3 ([00][][]) ([00][][]) ([00][][]) ([00][][]) ([00][][]) Table:Tabular representaton of The tabular representaton of f s gven by U e e u ([7][48][3]) ([3][46][6]) u ([3][67][8]) ([05][58][4]) u 3 ([48][67][69]) ([03][47][8]) ([5][89][49]) ([03][69][7]) ([3][68][37]) Table3:Tabular representaton of f The tabular representaton of f s gven by U e e u ([47][57][49]) ([3][45][79]) u ([35][48][4]) ([46][35][5]) u 3 ([39][][67]) ([57][67][34]) ([37][58][]) ([3][35][68]) ([6][35][58]) Table4: Tabular representaton of f 3 Let f f f representaton of f 3 then the tabular s gven by njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
4 U e e u ([7][58][4]) ([3][46][79]) u ([3][68][8]) ([05][58][4]) u 3 ([38][67][69]) ([03][67][38]) ([5][89][49]) ([03][69][68]) ([3][68][58]) Table5:Tabular representaton of f 3 4 Let f f f representaton of f 4 then the tabular s gven by U e e u ([47][47][39]) ([3][45][6]) u ([35][47][4]) ([46][35][5]) u 3 ([49][][67]) ([57][47][4]) ([37][58][]) ([3][35][7]) ([6][35][37]) Table6:Tabular representaton of f 4 Here we observe that the sub-famly 3 4 f f f f of s a IVNS-topology on the neessary three axoms of topology and as t satsfes s a IVNS-topologal spae But the sub-famly f f of s not an IVNS-topology on 4 f f f as the unon does not belong to Defnton 33: s every IVNS-topology on must ontans the sets and so the famly forms a IVNS-topology on The topology s alled ndsrete IVNS-topology and the trplet s alled an ndsrete nterval valued neutrosoph soft topologal spae (or smply ndsrete IVNS-topologal spae) Defnton 34: Let denotes the famly of all IVNSsubsets of Then we observe that satsfes all the axoms of topology on Ths topology s alled dsrete nterval valued neutrosoph soft topology and the trplet s alled dsrete nterval valued neutrosoph soft topologal spae (or smply dsrete IVNS-topologal spae) Theorem 35: Let : I be any olleton of IVNStopology on Then ther nterseton s also a IVNS-topology on Proof: () Sne Hene () Let k I for eah I I f : k K be an arbtrary famly of nterval valued neutrosoph soft sets where f k for eah k K Then for eah I I f k for k K and sne for eah I a a IVNS-topology therefore k kk Hene f k kk I () Let f for eah I I f f then f f for eah I Sne for eah s an IVNS-topology therefore for eah I Hene f f Hene I Thus I I f f I satsfes all the axoms of topology forms a IVNS-topology But unon of IVNStopologes need not be a IVNS-topology Let us show ths wth the followng example xampl6: In exampl the sub famles 3 f and 4 f are IVNS-topologes n But ther unon 3 4 f f s not a IVNS-topology n Defnton 37: Let be an IVNS-topologal spae over n nterval valued neutrosoph soft njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
5 subset f of s alled nterval valued neutrosoph soft losed set (n short IVNS-losed set) f ts omplement f s a member of xampl8: Let us onsder exampl then the IVNSlosed sets n are U e e u ([7][57][58]) ([3][78][47]) u ([][67][47]) ([][89][69]) u 3 ([36][9][5]) ([3][68][68]) ([0][9][39]) ([05][89][48]) ([4][79][49]) Table7:Tabular representaton of U e e u ([] [00][00]) ([] [00][00]) u ([] [00][00]) ([] [00][00]) u 3 ([] [00][00]) ([] [00][00]) Table8:Tabular representaton of ([] [00][00]) ([] [00][00]) ([] [00][00]) U e e u ([3][6][7]) ([6][46][3]) u ([8][34][3]) ([4][5][05]) u 3 ([69[34][48]) ([8][36][03]) ([49][][5]) ([6][4][03]) ([37][4][3]) Table9:Tabular representaton of f U e e u ([49][35][47]) ([79][56][3]) u ([4][6][35]) ([5][57][46]) u 3 ([67][89][39]) ([34][34][57]) ([][5][37]) ([68][57][3]) ([58][57][6]) Table0:Tabular representaton of f U e e u ([4][5][7]) ([79][46][3]) u ([8][4][3]) ([4][5][05]) u 3 ([69][34][38]) ([38][34][03]) ([49][][5]) ([68][4][03]) ([58][4][3]) Table:Tabular representaton of f 3 U e e u ([39][36][47]) ([6][56][3]) u ([4][36][35]) ([5][57][46]) u 3 ([67][89][49]) ([4][36][57]) ([][5][37]) ([7][57][3]) ([37][57][6]) Table:Tabular representaton of f 4 are the IVNS-losed sets n Theorem 39: Let be an IVNS-topologal spae over Then are IVNS-losed sets rbtrary nterseton of IVNS-losed sets s IVNS-losed set 3 Fnte unon of IVNS-losed sets s IVNS-losed set therefore Proof: Sne Let k are IVNS-losed sets f : k K be an arbtrary famly of IVNS-losed sets n f f k kk and let njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
6 3 Now for eah k Thus k and k K k K k k f f f f k K so kk f s IVNS-losed set 3 Let IVNS-losed sets n f g f Hene f f : 3 n be a famly of and let n g f n Now for 3 n g f f n and n so Thus g s IVNS-losed set f Hene Defnton 30: Let and IVNS-topologal spaes over f mples f be two Iah then s alled nterval valued neutrosoph soft fner topology than and s alled nterval valued neutrosoph soft oarser topology than xampl: In exampl and 36 s nterval valued neutrosoph soft fner topology than 3 and 3 s alled nterval valued neutrosoph soft oarser topology than Defnton 3: Let be a IVNS-topologal spae over and ß be a subfamly of Ivery element of an be express as the arbtrary nterval valued neutrosoph soft unon of some elements of ß then ß s alled an nterval valued neutrosoph soft bass for the IVNS-topology xampl3: In exampl for the IVNStopology 3 4 f f f f the 3 subfamly ß= f f f of s a nterval valued neutrosoph soft bass for the IVNS-topology 4 Some Propertes of Interval Valued Neutrosoph Soft Topologal In ths seton some propertes of nterval valued neutrosoph soft topologal spaes are ntrodued Some results on IVNSInt and IVNSCl are also ntodued Defnton 4: Let be a IVNS-topologal spae and let f IVNSS ( U ; ) The nterval valued neutrosoph soft nteror and loser of f s denoted by IVNSInt(f ) and IVNSCl(f ) are defned as IVNSInt f g : g f and g : f g respetvely INVNSCl f xample 4: Let us onsder exampl and take an IVNSS f 5 as U e e u ([8][36][8]) ([4][46][4]) u ([6][45][7]) ([6][57][7]) u 3 ([58][56][58]) ([4][46][5]) ([6][78][34]) ([4][5][5]) ([5][58][4]) Table3:Tabular representaton of f 5 5 Now IVNSInt f f and IVNSCl f f 5 Theorem 43: Let be a IVNS-topologal spae and f g IVNSS U ; then the followng propertes hold IVNSInt f f f g IVNSInt f IVNSInt g 3 IVNSInt f 4 f IVNSInt f f 5 IVNSInt IVNSInt f IVNSInt f 6 IVNSInt IVNSInt U U Proof: Straght forward f g mples all the IVNS-open sets ontaned n f also ontaned n g e * * * * f : f f g : g g njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
7 4 e * * * * f : f f g : g g e IVNSInt f IVNSInt g * * 3 IVNSInt f f : f f * * It s lear that f : f f So IVNSInt f 4 Let f then by () IVNSInt f f Now sne f and f f Theorem 44: Let be a IVNS-topologal spae and f g IVNSs U ; then the followng propertes hold f IVNSCl f f g IVNSCl f IVNSCl g 3 IVNSCl f 4 f IVNSCl f f 5 IVNSCl IVNSCl f IVNSCl f 6 IVNSCl IVNSCl U U Proof: straght forward Theorem 45: Let be an IVNS-topologal spae on and let f ; g IVNSs U Then the followng propertes hold IVNSInt f g IVNSInt f IVNSInt g Proof: IVNSInt f g IVNSInt f IVNSInt g 3 IVNSCl f g IVNSCl f IVNSCl g 4 IVNSCl f g IVNSCl f IVNSCl g 5 IVNSInt f IVNSCl f 6 IVNSCl f IVNSInt f By theorem 4 () IVNSInt f f Therefore and IVNSInt g g Thus * * f g : g g IVNSInt f IVNSInt f IVNSInt g f g Hene e f IVNSInt f IVNSInt f IVNSInt g IVNSInt f g Thus IVNSInt f f () Conversly let IVNSInt f f gan sne f g f By theorem 4 () IVNSInt f g IVNSInt f Sne by (3) IVNSInt f Therefore f Smlarly 5 By (3) IVNSInt f IVNSInt f g IVNSInt g Hene By (4) IVNSInt IVNSInt f IVNSInt f IVNSInt f g IVNSInt f IVNSInt g () 6 We know that U Usng () and () we get By (4) IVNSInt IVNSInt U U IVNSInt f g IVNSInt f IVNSInt g Sne f f g By theorem 4 () IVNSInt f IVNSInt f g Smlarly IVNSInt g IVNSInt f g Hene IVNSInt f g IVNSInt f IVNSInt g 3 Smlar to 4 Smlar to 5 IVNSInt f g : g f g : f g IVNSCl f njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
8 5 6 Smlar to 5 qualty does not hold n theorem 44 () (4) Let us show ths by an example xample 46: Let U u u e e e 3 e e The tabular representaton of s gven by U e e u ([58][35][7]) ([39][][0]) u ([46][34][]) ([48][3][]) Table4:Tabular representaton of The tabular representaton of s gven by U e e u ([00] [] []) ([00] [] []) u ([00] [] []) ([00] [] []) Table5:Tabular representaton of The tabular representaton of f s gven by U e e u ([7][48][3]) ([5][79][37]) u ([][67][7]) ([03][58][4]) Table6:Tabular representaton of f Clearly f s a IVNS-topology on Let us now take two nterval valued neutrosoph soft sets g and h as U e e u ([6][49][4]) ([5][79][38]) u ([][67][8]) ([0][59][4]) Table7:Tabular representaton of g U e e u ([07][58][3]) ([5][8][67]) u ([][68][37]) ([03][68][5]) Table8:Tabular representaton of h Now g h f IVNSInt g h IVNSInt f f IVNSInt h lso IVNSInt g IVNSInt g IVNSInt h Thus IVNSInt f g IVNSInt f IVNSInt g Therefore equalty does not hold for () By theorem 44 (5) IVNSCl g IVNSl g Smlarly IVNSl h Therefore IVNSCl g IVNSCl h lso IVNSCl g h IVNSCl g h IVNSInt g h IVNSInt f f Thus IVNSCl f g IVNSCl f IVNSCl g Therefore equalty doesnot hold n (4) 5 Interval Valued Neutrosoph Soft Subspae Topology In ths seton we ntrodue the onept of nterval valued neutrosoph soft subspae topology along wth some examples and results Theorem 5: Let be an IVNS-topologal spae on f Then the and olleton f : f g g an IVNS-topology on Proof: () Sne f f f s therefore and f f f () Let k f k f f g where k K Now f k K Then g for eah k k k f f g f g f kk kk kk g k as eah g k (sne kk () Let f f f then f f g and f f g where g g njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
9 6 Now f f f g f g f g g f (sne g g as g g ) Defnton 5: Let be an IVNS-topologal spae on and f Then the IVNS-topology f g : g f s alled nterval valued neutrosoph soft subspae topology and f f s alled nterval valued neutrosoph soft subspae of xample 53: Let us onsder the IVNS-topology 3 4 f f f f as n exampl and an IVNSS f : U e e u ([46][67][35]) ([57][46][03]) u ([3][36][57]) ([68][45][3]) u 3 ([57][46][34]) ([45][79][67]) ([35][58][3]) ([58][57][3]) ([3][79][57]) Table9:Tabular representaton of f Then f f : U e e u ([00][][]) ([00][][]) u ([00][][]) ([00][][]) u 3 ([00][][]) ([00][][]) ([00][][]) ([00][][]) ([00][][]) Table0:Tabular representaton of f g f f : U e e u ([6][67][3]) ([3][46][6]) u ([3][67][58]) ([05][45][4]) u 3 ([47][46][69]) ([03][79][68]) ([5][58][49]) ([03][69][7]) ([3][79][57]) Table:Tabular representaton of g g f f : U e e u ([46][67][49]) ([3][46][79]) u ([3][48][57]) ([46][45][5]) u 3 ([37][46][67]) ([45][79][67]) ([35][58][3]) ([3][57][68]) ([3][79][38]) Table:Tabular representaton of g 3 3 g f f : U e e u ([6][68][4]) ([3][46][79]) u ([3][68][58]) ([05][45][4]) u 3 ([37][46][69]) ([03][79][68]) ([5][58][49]) ([03][69][68]) ([3][79][58]) Table3:Tabular representaton of g 4 4 g f f : U e e u ([5][58][49]) ([5][58][49]) u ([03][69][68]) ([03][69][68]) u 3 ([3][79][58]) ([3][79][58]) 3 ([35][58][3]) ([3][57][7]) ([3][79][57]) Table4:Tabular representaton of g 4 4 Then f g g g s an nterval valued neutrosoph soft subspae njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
10 7 topology for and f f s alled nterval valued neutrosoph soft subspae of Theorem 54: Let be an IVNS-topologal spae on f f g f g ß be an IVNS-bass for and Then the famly ß = : ß s an IVNS-bass for subspae topology f h be arbtrary then there exsts Proof: Let f an IVNSS g suh that h f g Sne ß s a bass for therefore there exsts a sub olleton : I of ß suh that g Now I h f g f I Sne f ß f therefore ß f s an IVNS-bass for the subspae topology f Conluson In ths paper we ntrodue the onept of nterval valued neutrosoph soft topology Some bas theorem and propertes of the above onept are also studed IVN nteror and IVN loser of an nterval valued neutrosoph soft set are also defned Interval valued neutrosoph soft subspae topology s also studed In future there wll be more researh work n ths onept takng the bas defntons and results from ths artle Referenes [] H ktas N Cagman Soft Sets and soft groups Inform S 77(007) [] M I l F Feng X Lu W K Mn and M Shabr On some new operatons n soft set theory Computers and Mathemats wth pplatons 57(9)(009) [3]I rokaran I R Sumath J Martna Jeny Fuzzy neutrosoph soft topologal spaes Internatonal Journal of Mathematal rhve4(0)( 03) 5-38 [4] K tanassov Intutonst fuzzy sets Fuzzy Sets and Systems 0(986) [5] S Broum I Del and F Smarandahe Relatons on Interval Valued Neutrosoph Soft Sets Journal of New Results n Sene 5 (04) -0 [6] I Del Interval-valued neutrosoph soft sets and ts deson makng Kls 7 ralık Unversty Kls Turkey I [7] P K Maj R Bswas and R Roy Soft Set Theory Computers and Mathemats wth pplatons 45(003) [8] P K Maj Neutrosoph soft set nnals of Fuzzy Mathemats and Informaton 5()(03) [9] D Molodtsov Soft set theory-frst results Computers and Mathemats wth pplatons 37(4-5)(999) 9-3 [0] njan Mukherjee joy Kant Das bhjt Saha Interval valued ntutonst fuzzy soft topologal spaes nnals of Fuzzy Mathemats and Informats 6 (3) ( 03) [] D Pe D Mao From soft sets to nformaton systems Pro I Int Conf Granular Comput (005) 67-6 [] F Smarandahe Neutrosoph Log and Set mss [3] F Smarandahe Neutrosoph set- a generalsaton of the ntutonst fuzzy sets nt J Pure ppl Math 4(005) [4] H Wang F Smarandahe YQ Zhang R Sunderraman Interval Neutrosoph Sets and log: Theory and pplatons n Computng Hexs; Neutrosoph book seres No: [5] L Zadeh Fuzzy sets Informaton and Control 8 (965) Reeved: September epted: Otober 5 04 njan Mukherjee Mthun Datta Florentn Smarandahe Interval Valued Neutrosoph Soft Topologal
Complement of an Extended Fuzzy Set
Internatonal Journal of Computer pplatons (0975 8887) Complement of an Extended Fuzzy Set Trdv Jyot Neog Researh Sholar epartment of Mathemats CMJ Unversty, Shllong, Meghalaya usmanta Kumar Sut ssstant
More informationFuzzy Rings and Anti Fuzzy Rings With Operators
OSR Journal of Mathemats (OSR-JM) e-ssn: 2278-5728, p-ssn: 2319-765X. Volume 11, ssue 4 Ver. V (Jul - ug. 2015), PP 48-54 www.osrjournals.org Fuzzy Rngs and nt Fuzzy Rngs Wth Operators M.Z.lam Department
More informationNeutrosophic Vague Set Theory
9 Netrosoph Vage Set Theory Shawkat lkhazaleh Department of Mathemats Falty of Sene and rt Shaqra Unersty Sad raba shmk79@gmal.om bstrat In 99 Ga and Behrer proposed the theory of age sets as an etenson
More informationSoft Neutrosophic Bi-LA-semigroup and Soft Neutrosophic N-LA-seigroup
Neutrosophc Sets and Systems, Vol. 5, 04 45 Soft Neutrosophc B-LA-semgroup and Soft Mumtaz Al, Florentn Smarandache, Muhammad Shabr 3,3 Department of Mathematcs, Quad--Azam Unversty, Islamabad, 44000,Pakstan.
More informationThe Multi-Interval-Valued Fuzzy Soft Set with Application in Decision Making
ppled Mathemats, 205, 6, 250-262 Pblshed Onlne Jly 205 n SRes http://wwwsrporg/jornal/am http://dxdoorg/0426/am205688 The Mlt-Interval-Valed Fzzy Soft Set wth pplaton n Deson Mang Shawat lhazaleh Department
More informationNeutrosophic Sets and Systems
04 ISS 33-6055 (prnt) ISS 33-608X (onlne) eutrosoph Sets and Systems n Internatonal Journal n Informaton Sene and ngneerng Quarterly dtor-n-chef: Prof Florentn Smarandahe ddress: eutrosoph Sets and Systems
More informationResearch Article Relative Smooth Topological Spaces
Advances n Fuzzy Systems Volume 2009, Artcle ID 172917, 5 pages do:10.1155/2009/172917 Research Artcle Relatve Smooth Topologcal Spaces B. Ghazanfar Department of Mathematcs, Faculty of Scence, Lorestan
More informationController Design for Networked Control Systems in Multiple-packet Transmission with Random Delays
Appled Mehans and Materals Onlne: 03-0- ISSN: 66-748, Vols. 78-80, pp 60-604 do:0.408/www.sentf.net/amm.78-80.60 03 rans eh Publatons, Swtzerland H Controller Desgn for Networed Control Systems n Multple-paet
More informationSmooth Neutrosophic Topological Spaces
65 Unversty of New Mexco Smooth Neutrosophc opologcal Spaces M. K. EL Gayyar Physcs and Mathematcal Engneerng Dept., aculty of Engneerng, Port-Sad Unversty, Egypt.- mohamedelgayyar@hotmal.com Abstract.
More informationOn Similarity Measures of Fuzzy Soft Sets
Int J Advance Soft Comput Appl, Vol 3, No, July ISSN 74-853; Copyrght ICSRS Publcaton, www-csrsorg On Smlarty Measures of uzzy Soft Sets PINAKI MAJUMDAR* and SKSAMANTA Department of Mathematcs MUC Women
More informationSome Concepts on Constant Interval Valued Intuitionistic Fuzzy Graphs
IOS Journal of Mathematcs (IOS-JM) e-issn: 78-578, p-issn: 39-765X. Volume, Issue 6 Ver. IV (Nov. - Dec. 05), PP 03-07 www.osrournals.org Some Concepts on Constant Interval Valued Intutonstc Fuzzy Graphs
More informationSome Results on the Counterfeit Coins Problem. Li An-Ping. Beijing , P.R.China Abstract
Some Results on the Counterfet Cons Problem L An-Png Bejng 100085, P.R.Chna apl0001@sna.om Abstrat We wll present some results on the ounterfet ons problem n the ase of mult-sets. Keywords: ombnatoral
More informationThe 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 informationAppendix 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 informationOn Generalized Fractional Hankel Transform
Int. ournal o Math. nalss Vol. 6 no. 8 883-896 On Generaled Fratonal ankel Transorm R. D. Tawade Pro.Ram Meghe Insttute o Tehnolog & Researh Badnera Inda rajendratawade@redmal.om. S. Gudadhe Dept.o Mathemats
More informationTHE RING AND ALGEBRA OF INTUITIONISTIC SETS
Hacettepe Journal of Mathematcs and Statstcs Volume 401 2011, 21 26 THE RING AND ALGEBRA OF INTUITIONISTIC SETS Alattn Ural Receved 01:08 :2009 : Accepted 19 :03 :2010 Abstract The am of ths study s to
More information20. 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 informationNeutrosophic Bi-LA-Semigroup and Neutrosophic N-LA- Semigroup
Neutrosophc Sets Systems, Vol. 4, 04 9 Neutrosophc B-LA-Semgroup Neutrosophc N-LA- Semgroup Mumtaz Al *, Florentn Smarache, Muhammad Shabr 3 Munazza Naz 4,3 Department of Mathematcs, Quad--Azam Unversty,
More informationNeutrosophic Relations Database
nternatonal Journal of nformaton ene and ntellgent stem 3: -3 4 eutrosoph elatons Database.. alama Mohamed Esa and M. M. bdelmoghn 3 3 Department of Mathemats and Computer ene Fault of enes Port ad Unverst
More informationJournal of Engineering and Applied Sciences. Ultraspherical Integration Method for Solving Beam Bending Boundary Value Problem
Journal of Engneerng and Appled Senes Volue: Edton: Year: 4 Pages: 7 4 Ultraspheral Integraton Method for Solvng Bea Bendng Boundary Value Proble M El-Kady Matheats Departent Faulty of Sene Helwan UnverstyEgypt
More informationAPPENDIX 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 informationSubset 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 informationREAL 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 informationIntuitionistic Fuzzy G δ -e-locally Continuous and Irresolute Functions
Intern J Fuzzy Mathematcal rchve Vol 14, No 2, 2017, 313-325 ISSN 2320 3242 (P), 2320 3250 (onlne) Publshed on 11 December 2017 wwwresearchmathscorg DOI http//dxdoorg/1022457/jmav14n2a14 Internatonal Journal
More informationMatrix-Norm Aggregation Operators
IOSR Journal of Mathematcs (IOSR-JM) e-issn: 78-578, p-issn: 39-765X. PP 8-34 www.osrournals.org Matrx-Norm Aggregaton Operators Shna Vad, Sunl Jacob John Department of Mathematcs, Natonal Insttute of
More informationON DUALITY FOR NONSMOOTH LIPSCHITZ OPTIMIZATION PROBLEMS
Yugoslav Journal of Oeratons Researh Vol 9 (2009), Nuber, 4-47 DOI: 0.2298/YUJOR09004P ON DUALITY FOR NONSMOOTH LIPSCHITZ OPTIMIZATION PROBLEMS Vasle PREDA Unversty of Buharest, Buharest reda@f.unbu.ro
More informationBitopological spaces via Double topological spaces
topologcal spaces va Double topologcal spaces KNDL O TNTWY SEl-Shekh M WFE Mathematcs Department Faculty o scence Helwan Unversty POox 795 aro Egypt Mathematcs Department Faculty o scence Zagazg Unversty
More informationAntipodal Interval-Valued Fuzzy Graphs
Internatonal Journal of pplcatons of uzzy ets and rtfcal Intellgence IN 4-40), Vol 3 03), 07-30 ntpodal Interval-Valued uzzy Graphs Hossen Rashmanlou and Madhumangal Pal Department of Mathematcs, Islamc
More informationJSM Survey Research Methods Section. Is it MAR or NMAR? Michail Sverchkov
JSM 2013 - Survey Researh Methods Seton Is t MAR or NMAR? Mhal Sverhkov Bureau of Labor Statsts 2 Massahusetts Avenue, NE, Sute 1950, Washngton, DC. 20212, Sverhkov.Mhael@bls.gov Abstrat Most methods that
More informationLinear, 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 informationInternational Journal of Mathematical Archive-3(3), 2012, Page: Available online through ISSN
Internatonal Journal of Mathematcal Archve-3(3), 2012, Page: 1136-1140 Avalable onlne through www.ma.nfo ISSN 2229 5046 ARITHMETIC OPERATIONS OF FOCAL ELEMENTS AND THEIR CORRESPONDING BASIC PROBABILITY
More informationWeighted Neutrosophic Soft Sets
Neutrosophi Sets and Systems, Vol. 6, 2014 6 Weighted Neutrosophi Soft Sets Pabitra Kumar Maji 1 ' 2 1 Department of Mathematis, B. C. College, Asansol, West Bengal, 713 304, India. E-mail: pabitra_maji@yahoo.om
More informationFirst 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 informationarxiv: 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 informationCOMPLEX 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 informationMAT 578 Functional Analysis
MAT 578 Functonal Analyss John Qugg Fall 2008 Locally convex spaces revsed September 6, 2008 Ths secton establshes the fundamental propertes of locally convex spaces. Acknowledgment: although I wrote these
More informationRandić Energy and Randić Estrada Index of a Graph
EUROPEAN JOURNAL OF PURE AND APPLIED MATHEMATICS Vol. 5, No., 202, 88-96 ISSN 307-5543 www.ejpam.com SPECIAL ISSUE FOR THE INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND ALGEBRA 29 JUNE -02JULY 20, ISTANBUL
More informationLectures - 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 informationAffine 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 informationCHAPTER-5 INFORMATION MEASURE OF FUZZY MATRIX AND FUZZY BINARY RELATION
CAPTER- INFORMATION MEASURE OF FUZZY MATRI AN FUZZY BINARY RELATION Introducton The basc concept of the fuzz matr theor s ver smple and can be appled to socal and natural stuatons A branch of fuzz matr
More informationA CLASS OF RECURSIVE SETS. Florentin Smarandache University of New Mexico 200 College Road Gallup, NM 87301, USA
A CLASS OF RECURSIVE SETS Florentn Smarandache Unversty of New Mexco 200 College Road Gallup, NM 87301, USA E-mal: smarand@unmedu In ths artcle one bulds a class of recursve sets, one establshes propertes
More information763622S ADVANCED QUANTUM MECHANICS Solution Set 1 Spring c n a n. c n 2 = 1.
7636S ADVANCED QUANTUM MECHANICS Soluton Set 1 Sprng 013 1 Warm-up Show that the egenvalues of a Hermtan operator  are real and that the egenkets correspondng to dfferent egenvalues are orthogonal (b)
More informationThe Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices
Internatonal Mathematcal Forum, Vol 11, 2016, no 11, 513-520 HIKARI Ltd, wwwm-hkarcom http://dxdoorg/1012988/mf20166442 The Jacobsthal and Jacobsthal-Lucas Numbers va Square Roots of Matrces Saadet Arslan
More informationOn the set of natural numbers
On the set of natural numbers by Jalton C. Ferrera Copyrght 2001 Jalton da Costa Ferrera Introducton The natural numbers have been understood as fnte numbers, ths wor tres to show that the natural numbers
More informationBinomial transforms of the modified k-fibonacci-like sequence
Internatonal Journal of Mathematcs and Computer Scence, 14(2019, no. 1, 47 59 M CS Bnomal transforms of the modfed k-fbonacc-lke sequence Youngwoo Kwon Department of mathematcs Korea Unversty Seoul, Republc
More informationFAULT DETECTION AND IDENTIFICATION BASED ON FULLY-DECOUPLED PARITY EQUATION
Control 4, Unversty of Bath, UK, September 4 FAUL DEECION AND IDENIFICAION BASED ON FULLY-DECOUPLED PARIY EQUAION C. W. Chan, Hua Song, and Hong-Yue Zhang he Unversty of Hong Kong, Hong Kong, Chna, Emal:
More informationPOWER ON DIGRAPHS. 1. Introduction
O P E R A T I O N S R E S E A R H A N D D E I S I O N S No. 2 216 DOI: 1.5277/ord1627 Hans PETERS 1 Judth TIMMER 2 Rene VAN DEN BRINK 3 POWER ON DIGRAPHS It s assumed that relatons between n players are
More informationExpected Value and Variance
MATH 38 Expected Value and Varance Dr. Neal, WKU We now shall dscuss how to fnd the average and standard devaton of a random varable X. Expected Value Defnton. The expected value (or average value, or
More information8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS
SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 493 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces you have studed thus far n the text are real vector spaces because the scalars
More informationInterval Valued Fuzzy Neutrosophic Soft Structure Spaces
Neutrosop Sets ad Systems Vol 5 0 6 Iterval Valued Fuzzy Neutrosop Sot Struture Spaes Iroara & IRSumat Nrmala College or Wome Combatore- 608 Tamladu Ida E-mal: sumat_rama005@yaooo bstrat I ts paper we
More informationInference-based Ambiguity Management in Decentralized Decision-Making: Decentralized Diagnosis of Discrete Event Systems
1 Inferene-based Ambguty Management n Deentralzed Deson-Makng: Deentralzed Dagnoss of Dsrete Event Systems Ratnesh Kumar Department of Eletral and Computer Engneerng, Iowa State Unversty Ames, Iowa 50011-3060,
More informationOn 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 informationVARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES
VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES BÂRZĂ, Slvu Faculty of Mathematcs-Informatcs Spru Haret Unversty barza_slvu@yahoo.com Abstract Ths paper wants to contnue
More informationSeparation Axioms of Fuzzy Bitopological Spaces
IJCSNS Internatonal Journal of Computer Scence and Network Securty VOL3 No October 3 Separaton Axom of Fuzzy Btopologcal Space Hong Wang College of Scence Southwet Unverty of Scence and Technology Manyang
More informationGeneral viscosity iterative method for a sequence of quasi-nonexpansive mappings
Avalable onlne at www.tjnsa.com J. Nonlnear Sc. Appl. 9 (2016), 5672 5682 Research Artcle General vscosty teratve method for a sequence of quas-nonexpansve mappngs Cuje Zhang, Ynan Wang College of Scence,
More informationImproving the Performance of Fading Channel Simulators Using New Parameterization Method
Internatonal Journal of Eletrons and Eletral Engneerng Vol. 4, No. 5, Otober 06 Improvng the Performane of Fadng Channel Smulators Usng New Parameterzaton Method Omar Alzoub and Moheldn Wanakh Department
More informationاولت ارص من نوع -c. الخلاصة رنا بهجت اسماعیل مجلة ابن الهیثم للعلوم الصرفة والتطبیقیة المجلد 22 (3) 2009
مجلة ابن الهیثم للعلوم الصرفة والتطبیقیة المجلد 22 (3) 2009 الت ارص من نوع -C- - جامعة بغداد رنا بهجت اسماعیل قسم الریاضیات - كلیة التربیة- ابن الهیثم الخلاصة قمنا في هذا البحث بتعریف نوع جدید من الت ارص
More informationNeryškioji dichotominių testo klausimų ir socialinių rodiklių diferencijavimo savybių klasifikacija
Neryškoj dchotomnų testo klausmų r socalnų rodklų dferencjavmo savybų klasfkacja Aleksandras KRYLOVAS, Natalja KOSAREVA, Julja KARALIŪNAITĖ Technologcal and Economc Development of Economy Receved 9 May
More informationDesign maintenanceand reliability of engineering systems: a probability based approach
Desg mateaead relablty of egeerg systems: a probablty based approah CHPTER 2. BSIC SET THEORY 2.1 Bas deftos Sets are the bass o whh moder probablty theory s defed. set s a well-defed olleto of objets.
More informationFuzzy Boundaries of Sample Selection Model
Proceedngs of the 9th WSES Internatonal Conference on ppled Mathematcs, Istanbul, Turkey, May 7-9, 006 (pp309-34) Fuzzy Boundares of Sample Selecton Model L. MUHMD SFIIH, NTON BDULBSH KMIL, M. T. BU OSMN
More informationRedesigning Decision Matrix Method with an indeterminacy-based inference process
Redesgnng Decson Matrx Method wth an ndetermnacy-based nference process Jose L. Salmeron a* and Florentn Smarandache b a Pablo de Olavde Unversty at Sevlle (Span) b Unversty of New Mexco, Gallup (USA)
More informationarxiv: v1 [quant-ph] 6 Sep 2007
An Explct Constructon of Quantum Expanders Avraham Ben-Aroya Oded Schwartz Amnon Ta-Shma arxv:0709.0911v1 [quant-ph] 6 Sep 2007 Abstract Quantum expanders are a natural generalzaton of classcal expanders.
More informationContinuous Time Markov Chain
Contnuous Tme Markov Chan Hu Jn Department of Electroncs and Communcaton Engneerng Hanyang Unversty ERICA Campus Contents Contnuous tme Markov Chan (CTMC) Propertes of sojourn tme Relatons Transton probablty
More informationWeek 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 informationSUPER PRINCIPAL FIBER BUNDLE WITH SUPER ACTION
talan journal of pure appled mathematcs n. 33 2014 (63 70) 63 SUPER PRINCIPAL FIBER BUNDLE WITH SUPER ACTION M.R. Farhangdoost Department of Mathematcs College of Scences Shraz Unversty Shraz, 71457-44776
More informationMATH CLASS 27. Contents
MATH 6280 - CLASS 27 Contents 1. Reduced and relatve homology and cohomology 1 2. Elenberg-Steenrod Axoms 2 2.1. Axoms for unreduced homology 2 2.2. Axoms for reduced homology 4 2.3. Axoms for cohomology
More informationGenericity of Critical Types
Genercty of Crtcal Types Y-Chun Chen Alfredo D Tllo Eduardo Fangold Syang Xong September 2008 Abstract Ely and Pesk 2008 offers an nsghtful characterzaton of crtcal types: a type s crtcal f and only f
More informationON 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 informationThe binomial transforms of the generalized (s, t )-Jacobsthal matrix sequence
Int. J. Adv. Appl. Math. and Mech. 6(3 (2019 14 20 (ISSN: 2347-2529 Journal homepage: www.jaamm.com IJAAMM Internatonal Journal of Advances n Appled Mathematcs and Mechancs The bnomal transforms of the
More informationDouble Layered Fuzzy Planar Graph
Global Journal of Pure and Appled Mathematcs. ISSN 0973-768 Volume 3, Number 0 07), pp. 7365-7376 Research Inda Publcatons http://www.rpublcaton.com Double Layered Fuzzy Planar Graph J. Jon Arockaraj Assstant
More informationDOAEstimationforCoherentSourcesinBeamspace UsingSpatialSmoothing
DOAEstmatonorCoherentSouresneamspae UsngSpatalSmoothng YnYang,ChunruWan,ChaoSun,QngWang ShooloEletralandEletronEngneerng NanangehnologalUnverst,Sngapore,639798 InsttuteoAoustEngneerng NorthwesternPoltehnalUnverst,X
More informationFACTORIZATION 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 informationfind (x): given element x, return the canonical element of the set containing x;
COS 43 Sprng, 009 Dsjont Set Unon Problem: Mantan a collecton of dsjont sets. Two operatons: fnd the set contanng a gven element; unte two sets nto one (destructvely). Approach: Canoncal element method:
More informationALGEBRAIC SCHUR COMPLEMENT APPROACH FOR A NON LINEAR 2D ADVECTION DIFFUSION EQUATION
st Annual Internatonal Interdsplnary Conferene AIIC 03 4-6 Aprl Azores Portugal - Proeedngs- ALGEBRAIC SCHUR COMPLEMENT APPROACH FOR A NON LINEAR D ADVECTION DIFFUSION EQUATION Hassan Belhad Professor
More informationInstance-Based Learning and Clustering
Instane-Based Learnng and Clusterng R&N 04, a bt of 03 Dfferent knds of Indutve Learnng Supervsed learnng Bas dea: Learn an approxmaton for a funton y=f(x based on labelled examples { (x,y, (x,y,, (x n,y
More informationPerron Vectors of an Irreducible Nonnegative Interval Matrix
Perron Vectors of an Irreducble Nonnegatve Interval Matrx Jr Rohn August 4 2005 Abstract As s well known an rreducble nonnegatve matrx possesses a unquely determned Perron vector. As the man result of
More informationSL 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 informationOn Tiling for Some Types of Manifolds. and their Folding
Appled Mathematcal Scences, Vol. 3, 009, no. 6, 75-84 On Tlng for Some Types of Manfolds and ther Foldng H. Rafat Mathematcs Department, Faculty of Scence Tanta Unversty, Tanta Egypt hshamrafat005@yahoo.com
More informationDesigning Fuzzy Time Series Model Using Generalized Wang s Method and Its application to Forecasting Interest Rate of Bank Indonesia Certificate
The Frst Internatonal Senar on Scence and Technology, Islac Unversty of Indonesa, 4-5 January 009. Desgnng Fuzzy Te Seres odel Usng Generalzed Wang s ethod and Its applcaton to Forecastng Interest Rate
More informationCOMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
More informationTHE WEIGHTED WEAK TYPE INEQUALITY FOR THE STRONG MAXIMAL FUNCTION
THE WEIGHTED WEAK TYPE INEQUALITY FO THE STONG MAXIMAL FUNCTION THEMIS MITSIS Abstract. We prove the natural Fefferman-Sten weak type nequalty for the strong maxmal functon n the plane, under the assumpton
More informationPHYSICS 212 MIDTERM II 19 February 2003
PHYSICS 1 MIDERM II 19 Feruary 003 Exam s losed ook, losed notes. Use only your formula sheet. Wrte all work and answers n exam ooklets. he aks of pages wll not e graded unless you so request on the front
More information3.1 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 informationLecture 3: Probability Distributions
Lecture 3: Probablty Dstrbutons Random Varables Let us begn by defnng a sample space as a set of outcomes from an experment. We denote ths by S. A random varable s a functon whch maps outcomes nto the
More informationPhase Transition in Collective Motion
Phase Transton n Colletve Moton Hefe Hu May 4, 2008 Abstrat There has been a hgh nterest n studyng the olletve behavor of organsms n reent years. When the densty of lvng systems s nreased, a phase transton
More informationThe probability that a pair of group elements is autoconjugate
Proc. Indan Acad. Sc. (Math. Sc.) Vol. 126, No. 1, February 2016, pp. 61 68. c Indan Academy of Scences The probablty that a par of group elements s autoconjugate MOHAMMAD REZA R MOGHADDAM 1,2,, ESMAT
More informationVolume 18 Figure 1. Notation 1. Notation 2. Observation 1. Remark 1. Remark 2. Remark 3. Remark 4. Remark 5. Remark 6. Theorem A [2]. Theorem B [2].
Bulletn of Mathematcal Scences and Applcatons Submtted: 016-04-07 ISSN: 78-9634, Vol. 18, pp 1-10 Revsed: 016-09-08 do:10.1805/www.scpress.com/bmsa.18.1 Accepted: 016-10-13 017 ScPress Ltd., Swtzerland
More informationCHAPTER 4 MAX-MIN AVERAGE COMPOSITION METHOD FOR DECISION MAKING USING INTUITIONISTIC FUZZY SETS
56 CHAPER 4 MAX-MIN AVERAGE COMPOSIION MEHOD FOR DECISION MAKING USING INUIIONISIC FUZZY SES 4.1 INRODUCION Intutonstc fuzz max-mn average composton method s proposed to construct the decson makng for
More informationCase Study of Markov Chains Ray-Knight Compactification
Internatonal Journal of Contemporary Mathematcal Scences Vol. 9, 24, no. 6, 753-76 HIKAI Ltd, www.m-har.com http://dx.do.org/.2988/cms.24.46 Case Study of Marov Chans ay-knght Compactfcaton HaXa Du and
More informationA CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS
Journal of Mathematcal Scences: Advances and Applcatons Volume 25, 2014, Pages 1-12 A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS JIA JI, WEN ZHANG and XIAOFEI QI Department of Mathematcs
More informationarxiv:quant-ph/ Feb 2000
Entanglement measures and the Hlbert-Schmdt dstance Masanao Ozawa School of Informatcs and Scences, Nagoya Unversty, Chkusa-ku, Nagoya 464-86, Japan Abstract arxv:quant-ph/236 3 Feb 2 In order to construct
More informationDeriving the X-Z Identity from Auxiliary Space Method
Dervng the X-Z Identty from Auxlary Space Method Long Chen Department of Mathematcs, Unversty of Calforna at Irvne, Irvne, CA 92697 chenlong@math.uc.edu 1 Iteratve Methods In ths paper we dscuss teratve
More informationExercise 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 informationOn the spectral norm of r-circulant matrices with the Pell and Pell-Lucas numbers
Türkmen and Gökbaş Journal of Inequaltes and Applcatons (06) 06:65 DOI 086/s3660-06-0997-0 R E S E A R C H Open Access On the spectral norm of r-crculant matrces wth the Pell and Pell-Lucas numbers Ramazan
More informationThe Quadratic Trigonometric Bézier Curve with Single Shape Parameter
J. Basc. Appl. Sc. Res., (3541-546, 01 01, TextRoad Publcaton ISSN 090-4304 Journal of Basc and Appled Scentfc Research www.textroad.com The Quadratc Trgonometrc Bézer Curve wth Sngle Shape Parameter Uzma
More informationU.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016
U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and
More informationLecture 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 informationBasic Regular Expressions. Introduction. Introduction to Computability. Theory. Motivation. Lecture4: Regular Expressions
Introducton to Computablty Theory Lecture: egular Expressons Prof Amos Israel Motvaton If one wants to descrbe a regular language, La, she can use the a DFA, Dor an NFA N, such L ( D = La that that Ths
More information12 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