Selection Combining Upgrade Schemes for Mobile Units in Wireless Networks
|
|
- Gary Pearson
- 5 years ago
- Views:
Transcription
1 Selectio Combiig Upgade Scemes fo Mobile Uits i Wieless Netwoks GILL R. TSOURI ad DOV WULICH Depatmet of Electical ad Compute Egieeig Be-Guio Uivesity of te Negev Bee-Seva 845 ISRAEL tsoui@ee.bgu.ac.il Abstact: - Selectio combiig is cosideed fo upgadig te pefomace of mobile uits i wieless etwoks. Tee upgade scemes ae cosideed: ateas aay, ateas aay i cicula geometical settig ad ateas i liea geometical settig. Te poblem of divesity loss due to ateas poximity is addessed ad a appoac fo deceasig te loss is poposed. Te appoac is based o te Kaue-Loeve tasfom wic is deived fom te cael covaiace matix. As a example, te upgade of mobile uits i a IS-6 etwok is aalyzed fo Rayleig fadig caels. Pefomace is evaluated by computig te bit eo ate, outage pobability, aveage sigal to oise atio ad mea switcig ate of te cosideed scemes. Key-Wods: Divesity metods, fadig caels, wieless etwoks Itoductio Wieless etwoks opeate ude a costat demad fo ige tougput, due to te icease i uses ad multimedia sevices. Te developmet ad layout of ew etwok ifastuctue is costly ad upgade scemes ae pefeable if tey povide te adequate icease i capacity. A pomisig appoac to icease cael capacity ivolves te use of multiple ateas. Te optimal way of usig a multiple ateas eceptio aay is to combie te atea outputs usig Maximal Ratio Combiig (MRC) []. Tis appoac equies dow covesio of all ateas outputs to basebad ad good cael estimatio. MRC is ot suitable fo upgadig a existig eceive wic uses oly oe dow covesio cai fo a sigle atea. A alteative to MRC is Selectio Combiig (SC) [-7,]. SC scemes wee well eseaced i te past ad ecetly eceived eewed academic attetio [-4]. I SC te atea wit te igest Istataeous Sigal to Noise Ratio (ISNR) is cose by a Radio Fequecy (RF) switc ad is fed to a sigle dow covesio cai. It follows, tat SC scemes may offe a suitable solutio fo upgadig existig wieless etwoks by eplacig te sigle atea fot ed wit a multiple ateas fot ed ad te accompayig switc ad logic. I tis pape we aalyze tee SC upgade scemes. I may wieless eceives te ateas ae foced to be close to oe aote, suc is te case of mobile uits i a cellula etwoks. SC scemes suffe fom divesity loss we te ateas ae close togete. Liea aay RF fot ed KLT switc logic Double aay eceive Cicula aay Fig. Sceme of upgaded eceives Te loss is due to statistical coelatio betwee te ateas outputs [4-6]. Pefomace aalysis of dual bac SC scemes i coelated fadig caels is eadily available fo vaious types of caels. Howeve, fo lage aays ad abitay ateas settigs, pefomace aalysis is limited [-,7,]. Te followig pefomace paametes ae commoly cosideed: Bit Eo Rate (BER), outage pobability ad Aveage Sigal to Noise Ratio (ASNR). I tis pape we also examie te mea switcig ate. Tis paamete is impotat i te cotext of cellula etwoks wee te mobile uits
2 x z z z KLT (matix P) selecto logic Fig. Low pass equivalet model of te tiple ateas scemes ave limited powe supply. A ig switcig ate would icease powe cosumptio. Also, fo systems utilizig cotiuous pase modulatio, eac switc equies ealigmet of pase. Switcig ate cosideatio is give i [7] as well. A slow flat fadig cael is assumed. Fadig caels commoly cosideed ae Rayleig, Ricia ad Nakagami. I tis pape we coside Rayleig fadig. Tis fadig descibes a o lie of sigt ad ic scatteig sceaio ad is cosideed sevee. Fo te Rayleig fadig sceaio te covaiace matix may be detemied offlie ad teefoe te KLT is also kow offlie ad is costat fo a give caie fequecy ad atea settig. It sould be oted tat i te case of a asymmetic etwok, suc as a cellula etwok wee eac mobile uit is upgaded to multiple ateas ad te base statio emais wit oe atea, te duality atue of SC ca be used to select a atea fo tasmissio at te mobile uit. It follows, tat symmety i sigal quality is acieved. Tis appoac equies cael state ifomatio at te mobile uit. Suc ifomatio ca be deduced by te mobile uit we te same fequecy bad is used fo tasmissio ad eceptio ad may be tasmitted fom te base statio as side ifomatio otewise. I tis pape we popose a tecique fo educig te divesity loss icued by statistical coelatio of te ateas outputs. It ivolves de-coelatig te ateas outputs wit te Kaue Loeve Tasfom (KLT) [] pio to te switcig pocess. Te tecique equies te applicatio of a liea tasfomatio o te ateas outputs wic educes to a weigted sum of te aalog sigals. Te KLT depeds o te cael covaiace matix aloe ad is costat ad kow offlie fo Rayleig fadig caels. We ame SC afte KLT as Vitual Selectio Combiig (VSC). v eceive Te KLT is used extesively i applicatios wee a data set wit lage dimesios is to be educed fo pocessig. Suc is te case i ype spectal imagig teciques, wee a lage set of pictues is to be educed fo pocessig by a olie compute. Te KLT peseves te most of te ifomatio i te oigial set ad is teefoe used as a pepocessig tecique, commoly efeed to as Piciple Compoet Aalysis (PCA). Te motivatio fo usig KLT fo switced divesity metods suc as selectio combiig stems fom te obsevatio tat te selectio pocess is i fact a eductio i te dimesios of te obsevatio space ad it makes sese to apply PCA pio to te eductio. Tee SC scemes ae cosideed. Te fist uses a ateas aay. Te secod uses ateas i a cicula geometical settig (equally spaced o a cicle i space). Te tid uses ateas i a liea geometical settig (equally spaced o a lie i space). Te est of te pape is ogaized as follows. I sectio te upgaded scemes ae descibed matematically, i sectio te KLT is applied, i sectio 4 pefomace paametes ae evaluated, i sectio 5 esults ae aalyzed ad i sectio 6 coclusios ae daw. System Desciptio We coside tee SC scemes as depicted i fig.. Tee ateas ae laid out i a cicula o liea geometical settig. Te powe coelatio coefficiet (ρ) may be computed usig te followig fomula [8]: π ρ J d, () λ wee J is te zeo ode Bessel fuctio, d is te distace betwee te ateas ad λ is te caie wavelegt. Notice tat fo aow bad sigals ρ is pactically costat witi te bad. As a example, we assume tat te distace betwee cosecutive ateas is cm fo te double ateas aay,.5 cm fo te tiple ateas cicula aay ad 5 cm fo te tiple ateas liea aay. Tese sceaios fit a cellula wieless telepoy mobile uit wee tee is limited space fo atea placig. We coside a caie fequecy of 85MHz, as is te case i te IS-6 wieless stadad. It follows fom () tat te coelatio betwee eac pai of cosecutive ateas outputs is ρ. fo te double ateas aay, ρ.8 fo te tiple cicula aay ad ρ.67 fo te tiple liea aay.
3 . Tiple ateas scemes Te systems low pass equivalet fo te tiple ateas scemes is sow i Fig.. Notice tat placig te KLT ad switcig afte dow covesio fits te liea model. It is assumed tat te cael betwee te tasmit atea ad eac oe of te eceive ateas as flat (o-fequecy selective) fadig, i.e., its low pass equivalet may be epeseted by a vecto of complex valued cael atteuatios ( ) T,,, + j. Cosequetly, te eceived vecto of ateas outputs is E s x + z, wee x is a complex valued symbol to be tasmitted, E s is its eegy ad z is a vecto of additive, zeo mea complex oise assumed to be spatially i.i.d. wit equal vaiace N. We assume as te followig popeties: (A) },,, ; (A) E{ },,,; m,, ; m * E.5, i.e., E ( i ) ( i ) ( q ) m E m (A) { } { } { } E ; (A4) { } { } E. We use * to ote te cojugate opeatio ad E{ } to deote expectatio. Suc popeties ae caacteistic fo may wieless caels [8,9]. Note tat (A) meas tat te i-pase ad quadatue compoets ae otogoal ad tat (A) meas tat te ASNR is te same fo all atea outputs (omogeous baces). Te covaiace matix is ied as: Fo te cicula aay sceme: ρ H C E{ } ρ ρ ρ ρ ρ (a) Fo te liea aay sceme: ρ ρ C ρ ρ (b) ρ ρ We use H to ote te cojugate taspose opeatio. Te iitios i (a) ad (b) ae i accodace wit te costat coelatio model ad expoetial coelatio model accodigly as give i []. We assume positive values of C. Howeve, tey may be egative as well. I ay case, te give aalysis emais te same. Rayleig fadig meas tat as a Gaussia distibutio, wic togete wit (A)-(A4) meas tat te joit Pobability Desity Fuctio (PDF) of te eal valued adom vecto (,,,, ) T, as te followig fom: f ( x) wee (, x x ) ad C det T x, T x C x exp N ( π ) () x is te agumet of te PDF C is te covaiace matix of. Fom (A)-(A4) we obtai: C.5,,,, * wee E{ } follows tat, m m m m,,,,,,,,, (4), ad fom (A)-(A4) it also,.. Double ateas sceme Te deivatio fo te double ateas sceme is essetially te same as tat of te tiple ateas scemes ad is omitted fo bevity. We ie: ρ C (c) ρ Cael de-coelatio. Tiple ateas scemes Te vecto is compised of samples i space geeated by te aay outputs. Applyig te KLT, i te fom of te matix P, o esults i: v P P( ES x + z) (5) ~ E P x + P z S ~ E x + ~ z wee P ad ~ z P z. We use te followig otatio: ~ ~ ~ ~ ( ) T ~ ~ ) ( ),,, ad ( i ~ q + j. Accodig to te popeties of te KLT, te matix P H is a uitay oe ad its colums ae te eigevectos of C. It follows tat te poposed de-coelatio pocedue depeds oly o te cael covaiace matix. Te auto-covaiace matix of ~ is diagoal ad: C PC P H diag λ, λ, ~ ( λ S ), (6)
4 wee { } λ ae te eigevalues of C ad ae also te vaiaces of te vitual cael atteuatios. We may aage te eigevalues suc tat λ λ λ. P is also uitay, so te statistical popeties of ~ z ae te same as tose of z. Te sum of te eigevalues is equal to te sum of te vaiaces of te atteuatios i. Equivaletly, sice te oise vaiace is ucaged by P, te sum of te ASNRs of te compoets i is equal to te sum of te ASNRs of te compoets i v. I ote wods, te KLT distibutes te total ASNR uevely, so tat ucoelated o omogeous baces ae ceated. We teat te compoets i v as te outputs of vitual ateas. As te coelatio coefficiet ρ becomes lage (te distace betwee te ateas i te aay becomes smalle), te diffeece i ASNR betwee te vitual ateas iceases. It follows tat as ρ iceases te SC switc as bette baces to coose fom afte KLT ad ece a divesity gai is acieved wic couteacts te divesity loss. Sice te KLT is a liea tasfom ~ as a Gaussia distibutio ad te followig PDF is tue: T det C ~ x C ~ x ( ) exp f x, (7) N ( π ) wee te matix C ~ is te ivese covaiace matix ~ ~ ~ ~ ~ ~ ~,,,,,. All compoets of ~ ae mutually ucoelated ad λ λ λ. (8) C ~.5 λ λ λ of te vecto: ( ) T Fo te case we ρ.8 we obtai: Fo te cicula aay sceme: P (9a) λ.945, λ.945, λ.8 Fo te Liea aay sceme: P (9b) λ.65, λ.8, λ Double ateas sceme Te deivatio fo te double ateas sceme is essetially te same as tat of te tiple ateas scemes ad is omitted fo bevity. We obtai: P (9c) λ.6485, λ.55 Note tat P emais ucaged fo ay give ρ ad tat it ca implemeted by just summig ad subtactig te ateas outputs. 4 Pefomace evaluatio 4. Tiple ateas scemes We evaluate pefomace by computig BER, outage pobability (P out ), ASNR ad mea switcig ate (R SW ). Te outage pobability is ied as P out P ( SNR < t, SNR < t, SNR < t), () wee Es is te ISNR at te -t bac SNR N ad t is a miimal equied SNR eeded fo acceptable pefomace of te eceive. Note tat i view of (A.) SNR Es N. Te mea switcig ate is ied as [7] R π p () SW wee π is te pobability tat te selecto cooses atea ad p is te pobability to move fom atea to aote. Let us ie Π ( π ) T, π, π. BER depeds o te type of modulatio beig used. We aalyze te BER of BPSK as a example. Te classical appoac to obtai closed fom expessios of te pefomace paametes is fist to acieve a closed fom expessio of te ISNR at te switc output. Pefomace paametes ae te calculated i a staigtfowad fasio. A diffeet appoac is to use te momet geeatig fuctio [-4,]. I wat follows we obtai closed fom expessios fo most of te paametes ad use Mote Calo metods to obtai te otes. Pefomace of SC Te outage pobability may be witte as: SC P f ( x, x,., x5, x6 ) dxdx dx5dx () 6 out D D x, x : x + x <, wee D ( ) { },, ad N t is te ISNR tesold omalized by te Es ASNR of a sigle bac pio to KLT.
5 a c Fig. BER as fuctio of SNR i db a) Double ateas, ρ. b) Tiple cicula aay, ρ.8 c) Tiple liea aay, ρ.67 b To calculate R SW we use iitio (), i.e., we ave to fid p ad Π. We ave: p SC K ( x, x,., x5, x6 ) dxdx dxdx 5 6 dxi dxi f Di D wee D ( x, x ) () { : x + x },,,, {( x, x ): x + x < x + x }, i,, i Di i i i i, ad f ( ) is give by (). Sice te baces ae omogeous: SC SC p p,,., (4a) π i, i,, (4b) Usig te iitio fo R SW we ave: SC R SW. (5) Te ASNR is evaluated diectly as: SC ASNR f ( x, x,., x5, x6 ) xdx xdx x5dx5x6dx (6) 6 D D Te itegals () ad (6) wee umeically evaluated usig Mote Calo metods. Te esults wee veified usig compute simulatio of te low pass equivalet model. BER is evaluated usig compute simulatio of te low pass equivalet model. Statistics wee gateed fo 5 istaces ad bits pe cael. cael Pefomace of VSC Sice te baces ae ucoelated, aalytic calculatios fo VSC is easie ta fo SC. Usig (7), i te same mae as was doe fo SC, outie calculatios obtai: VSC ASNR exp j λ j λλλ λ + λ + λ + λ + λ + λ λλ λλ λλ λ + λ λ + λ λ + λ VSC P out (7) (8) R SW ad BER fo BPSK wee obtaied toug Mote Calo computatio ad validated wit compute simulatio as was doe fo BPSK BER of SC. expessios fo most of te paametes ad use Mote Calo metods to obtai te otes. 4. Double ateas sceme Recall tat pio to KLT te baces ae idetically distibuted ad statistically coelated ad tat afte KLT tey ae ucoelated but ubalaced i ASNR. We use te esults obtaied i [] fo P out
6 P out ASNR MRC t t exp exp t SC t exp L + + π ( ρ) π t( + ρ siϑ) exp ρ ( ) dϑ ( + ρ ρ siϑ) π + ρ a VSC exp o exp o t ( + ρ ) L t ( ρ ) ρ.5 + Tab. P out, ASNR fo te double ateas sceme b Fig.4 R SW at switc output as fuctio of ρ a) Double ateas, ρ. b) Tiple ateas-cicula aay, ρ.8 ; liea aay, ρ.67 ad ASNR of dual coelated ad ubalaced baces i Nakagami-m fadig wit te pope adjustmet to Rayleig fadig (m) ad system paametes. Tab.. summaized esults fo P out ad ASNR. R SW fo SC may be deived i te same mae as was doe fo te tiple ateas scemes. We obtai: SC R SW (9) R SW fo VSC may be deived by usig a Makov cai model as was doe i [7] fo fidig te SSC mea switcig ate fo ubalaced baces. Te deivatio is essetially te same ad is omitted fo bevity. We obtai: VSC ρ R SW () 5. Results I fig. BER as a fuctio of te ASNR at a sigle bac pio to KLT is sow. Te MRC cuve is displayed as a lowe boud, sice it is te optimal metod. Te sigle atea cuve epesets system pefomace pio to te suggested upgade. Te double atea ad tiple atea cuves epeset te pefomace of a sigle atea wit double ad tiple te eceptio suface accodigly. Tis is doe to evaluate te divesity gai acieved by usig multiple ateas istead of a sigle big atea ad elps evaluate te beefits of usig a aay. Fo te double atea sceme we fid tat te KLT offes o gai to te system ad tat a divesity gai is always acieved by SC compaed to te doubled suface atea. Notice, tat at db SC pefoms 5db bette ta te doubled suface atea ad tat SC pefoms oly ~db wose ta MRC. It follows tat fo te IS-6 stadad two ateas spaced cm apat ae a good upgade solutio fo mobile uits ad tat te divesity loss is sevee eoug to justify te use of KLT pio to switcig. Fo te tiple cicula aay sceme, we fid tat at low SNR SC offes o cosideable divesity gai as compaed to te tiple atea ad is actually outpefomed by te tiple atea by db. Howeve, VSC pefoms as te tiple atea. It follows, tat fo low SNR te KLT gais db i BER pefomace. Fo ig SNR SC gives cosideable divesity gais of 5db ad moe as compaed to te tiple atea. VSC always pefoms bette ta SC,
7 Fig.5 Outage pobability as fuctio of ρ fo te tiple cicula aay but pefoms almost te same as SC fo SNR>db. Te same teds ae appaet fo te tiple liea aay sceme, but sice ρ is sigificatly lowe te KLT offes egligible gais fo SNR>5db. It follows, tat te tiple atea SC scemes offe a good upgade solutio ad te KLT ca be used to potect te system fom divesity loss at low SNR. I fig.4 R SW is displayed as a fuctio of ρ. Fo all scemes, we fid tat altoug R SW is costat fo SC, R SW fo VSC deceases damatically as ρ iceases. Fo te tiple cicula sceme wit ρ.8 R SW is. compaed to.67 fo SC. Fo te tiple liea sceme wit ρ.67 R SW is. compaed to.67 fo SC. Fo te double ateas sceme wit ρ. R SW is.44 compaed to.5 fo SC. Fig.5-6 illustate te way i wic te KLT potects te system fom divesity loss. Te displayed esults ae fo te tiple cicula aay sceme wit vayig ρ (due to diffeet atea spacig ad/o diffeet caie fequecies). Te esults fo te tiple liea aay sceme ae vey simila to te esults fo te cicula aay sceme ad ae omitted fo bevity. Also, te esults fo te double bac sceme exibit te same teds o a smalle scale ad ae omitted as well to avoid epetitio. I fig.5 P out is displayed as a fuctio of ρ. P out is calculated wit te tesold beig te ASNR at a sigle bac pio to KLT. We fid tat as ρ iceases P out iceases fo SC. Howeve, fo VSC it is costaied low ad is almost te same as tat of a tiple atea fo all ρ. P out fo MRC ises to a poit wee it is almost te same as VSC. Tese esults illustate te way i wic te KLT costais divesity loss. I fig.6 te ASNR at te switc output is displayed as a fuctio of ρ. Notice tat MRC, beig te optimal appoac, pefoms as a tiple atea. Fig.6 ASNR at switc output as fuctio of ρ fo te tiple cicula aay We fid tat as ρ iceases SC exibits iceasig divesity loss to te poit wee it acts as a sigle atea. Howeve, fo VSC te ASNR ises as ρ iceases to te poit wee it is almost te same as MRC. 6. Coclusio Tee selectio combiig upgade scemes wee suggested fo eceives of mobile uits i wieless etwoks. Te upgade cosisted of eplacig te sigle atea fot ed wit a double o tiple ateas aay, followed by te Kaue Loeve tasfom ad a selectio combiig switc. Te Kaue Loeve tasfom depeds o te cael covaiace matix wic is kow offlie fo Rayleig fadig. Fo te upgade sceme based o tee ateas aaged i a cicula geometical settig wit a caie fequecy of 85MHz ad ateas spacig of.5 cm, as is expected fom a adeld mobile uit i te IS-6 stadad, te system suffes fom divesity loss ad te Kaue Loeve tasfom impoved BER pefomace fo low SNR by db. Te switcig ate is deceased damatically ad te aveage SNR is impoved as well. Fo te same system wit te ateas aaged i a liea geometical settig 5 cm apat a less damatic gai is acieved. Fo te upgade sceme based o a double ateas aay wit a caie fequecy of 85MHz ad ateas spacig of cm, te Kaue Loeve tasfom offes o cosideable gai. It was sow tat te Kaue Loeve tasfom potects selectio system fom divesity loss ad impoves outage pobabilities ad aveage SNR at selecto output.
8 Refeeces: [] Y-C. Ko, M-S. Alouii, M. K. Simo, Aalysis ad Optimizatio of Switced Divesity Systems, IEEE Tas. o Veicula Tecology, Vol. 49., No.5. Sept., pp [] Q. T. Zag, H. G. Lu, A Geeal Aalytical Appoac to Multi-Bac Selectio Combiig Ove Vaious Spatially Coelated Fadig Caels, IEEE Tas. o Comm., Vol. 5, No. 7, July. [] C. Tellambua, A. Aamalai, V. K. Bagava, Uified Aalysis of Switced Divesity Systems i Idepedet ad Coelated Fadig Caels, IEEE Tas. o Comm., Vol. 49, No., Novembe. [4] M. A. Blaco ad K. J. Zduek, Pefomace ad optimizatio of switced divesity systems fo te detectio of sigals wit Rayleig fadig, IEEE Tas. O Comm., vol. COM-7, Decembe 979, pp [] M. K. Simo, M. S. Alouii, Digital Commuicatio ove Fadig Caels, Wiley, New Yok,. [] N. C. Sagias, G. K. Kaagiaidis, D. A. Zogas, P. T. Matiopoulos, ad G. S. Tombas, Pefomace Aalysis of Dual Selectio Divesity i Coelated Weibull Fadig Caels, IEEE Tas. Commu., Vol. 5, No. 8, pp. 6-67, July 4. [] G. K. Kaagiaidis, Pefomace Aalysis of SIR-Based Dual Selectio Divesity ove Coelated Nakagami-m Fadig Caels, IEEE Tas. Veic. Tec., Vol. 5, No. 5, pp. 9-6, Septembe. [4] L. Xiao ad Xiaodai Dog, New Results o te BER of Switced Divesity Combiig ove Nakagami Fadig Caels, IEEE Commu. Lettes, Vol. 9, pp. 6-8, Feb. 5. [5] A.M.D. Tukmai, A. A. Aowojolu, P.A. Jeffod, C.J. Kellett: A expeimetal evaluatio of te pefomace of two-bac space ad polaizatio divesity scemes at8 MHz, IEEE Tas. o Veicula Tecology, Vol. 44., No.. May 995, pp [6] C. M. Lo, W. H. Lam, Aveage SER fo M-ay modulatio systems wit space divesity ove idepedet ad coelated Nakagami fadig caels, IEE Poc.-Comm..,Vol 48, No. 6. Dec., pp [7] H. Yag ad M. S. Alouii, Makov cais ad pefomace compaiso of switced divesity scemes, Poceedigs 6t Aual Cofeece o Ifomatio Scieces ad Systems (CISS'), pp., Piceto, New Jesey, USA, Mac. [8] W. C. Lee, Mobile Commuicatio Egieeig, McGaw-Hill, New Yok, 98. [9] J. M. Wozecaft ad L. M. Jacobs, Piciples of Commuicatio Egieeig, J. Wiley, 965, pp [] A. Leo-Gacia, Pobability ad Radom Pocesses fo Electical Egieeig, d ed., Addiso Wesely, 994.
SVD ( ) Linear Algebra for. A bit of repetition. Lecture: 8. Let s try the factorization. Is there a generalization? = Q2Λ2Q (spectral theorem!
Liea Algeba fo Wieless Commuicatios Lectue: 8 Sigula Value Decompositio SVD Ove Edfos Depatmet of Electical ad Ifomatio echology Lud Uivesity it 00-04-06 Ove Edfos A bit of epetitio A vey useful matix
More information12.6 Sequential LMMSE Estimation
12.6 Sequetial LMMSE Estimatio Same kid if settig as fo Sequetial LS Fied umbe of paametes (but hee they ae modeled as adom) Iceasig umbe of data samples Data Model: [ H[ θ + w[ (+1) 1 p 1 [ [[0] [] ukow
More informationTHE ANALYSIS OF SOME MODELS FOR CLAIM PROCESSING IN INSURANCE COMPANIES
Please cite this atle as: Mhal Matalyck Tacaa Romaiuk The aalysis of some models fo claim pocessig i isuace compaies Scietif Reseach of the Istitute of Mathemats ad Compute Sciece 004 Volume 3 Issue pages
More informationCHAPTER 5 : SERIES. 5.2 The Sum of a Series Sum of Power of n Positive Integers Sum of Series of Partial Fraction Difference Method
CHAPTER 5 : SERIES 5.1 Seies 5. The Sum of a Seies 5..1 Sum of Powe of Positive Iteges 5.. Sum of Seies of Patial Factio 5..3 Diffeece Method 5.3 Test of covegece 5.3.1 Divegece Test 5.3. Itegal Test 5.3.3
More informationMATH Midterm Solutions
MATH 2113 - Midtem Solutios Febuay 18 1. A bag of mables cotais 4 which ae ed, 4 which ae blue ad 4 which ae gee. a How may mables must be chose fom the bag to guaatee that thee ae the same colou? We ca
More information= 5! 3! 2! = 5! 3! (5 3)!. In general, the number of different groups of r items out of n items (when the order is ignored) is given by n!
0 Combiatoial Aalysis Copyight by Deiz Kalı 4 Combiatios Questio 4 What is the diffeece betwee the followig questio i How may 3-lette wods ca you wite usig the lettes A, B, C, D, E ii How may 3-elemet
More informationTHE ANALYTIC LARGE SIEVE
THE ANALYTIC LAGE SIEVE 1. The aalytic lage sieve I the last lectue we saw how to apply the aalytic lage sieve to deive a aithmetic fomulatio of the lage sieve, which we applied to the poblem of boudig
More informationKEY. Math 334 Midterm II Fall 2007 section 004 Instructor: Scott Glasgow
KEY Math 334 Midtem II Fall 7 sectio 4 Istucto: Scott Glasgow Please do NOT wite o this exam. No cedit will be give fo such wok. Rathe wite i a blue book, o o you ow pape, pefeably egieeig pape. Wite you
More informationMultivector Functions
I: J. Math. Aal. ad Appl., ol. 24, No. 3, c Academic Pess (968) 467 473. Multivecto Fuctios David Hestees I a pevious pape [], the fudametals of diffeetial ad itegal calculus o Euclidea -space wee expessed
More informationComplementary Dual Subfield Linear Codes Over Finite Fields
1 Complemetay Dual Subfield Liea Codes Ove Fiite Fields Kiagai Booiyoma ad Somphog Jitma,1 Depatmet of Mathematics, Faculty of Sciece, Silpao Uivesity, Naho Pathom 73000, hailad e-mail : ai_b_555@hotmail.com
More informationCombining age-based and channelaware scheduling in wireless systems
HELSINKI UNIVERSITY OF TECHNOLOGY CLOWN semia 8.8.008 Combiig age-based ad chaelawae schedulig i wieless systems Samuli Aalto ad Pasi Lassila Netwokig Laboatoy Helsiki Uivesity of Techology Email: {Samuli.Aalto
More informationAdvanced Physical Geodesy
Supplemetal Notes Review of g Tems i Moitz s Aalytic Cotiuatio Method. Advaced hysical Geodesy GS887 Chistophe Jekeli Geodetic Sciece The Ohio State Uivesity 5 South Oval Mall Columbus, OH 4 7 The followig
More informationChapter 2 Sampling distribution
[ 05 STAT] Chapte Samplig distibutio. The Paamete ad the Statistic Whe we have collected the data, we have a whole set of umbes o desciptios witte dow o a pape o stoed o a compute file. We ty to summaize
More informationOn ARMA(1,q) models with bounded and periodically correlated solutions
Reseach Repot HSC/03/3 O ARMA(,q) models with bouded ad peiodically coelated solutios Aleksade Weo,2 ad Agieszka Wy oma ska,2 Hugo Steihaus Cete, Woc aw Uivesity of Techology 2 Istitute of Mathematics,
More informationBy the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences
Chapte : Theoy of Modula Aithmetic 8 Sectio D Chiese Remaide Theoem By the ed of this sectio you will be able to pove the Chiese Remaide Theoem apply this theoem to solve simultaeous liea cogueces The
More informationa) The average (mean) of the two fractions is halfway between them: b) The answer is yes. Assume without loss of generality that p < r.
Solutios to MAML Olympiad Level 00. Factioated a) The aveage (mea) of the two factios is halfway betwee them: p ps+ q ps+ q + q s qs qs b) The aswe is yes. Assume without loss of geeality that p
More informationOn composite conformal mapping of an annulus to a plane with two holes
O composite cofomal mappig of a aulus to a plae with two holes Mila Batista (July 07) Abstact I the aticle we coside the composite cofomal map which maps aulus to ifiite egio with symmetic hole ad ealy
More information13.8 Signal Processing Examples
13.8 Sigal Pocessig Eamples E. 13.3 Time-Vaig Chael Estimatio T Mlti Path v(t) (t) Diect Path R Chael chages with time if: Relative motio betwee R, T Reflectos move/chage with time ( t) = T ht ( τ ) v(
More informationSums of Involving the Harmonic Numbers and the Binomial Coefficients
Ameica Joual of Computatioal Mathematics 5 5 96-5 Published Olie Jue 5 i SciRes. http://www.scip.og/oual/acm http://dx.doi.og/.46/acm.5.58 Sums of Ivolvig the amoic Numbes ad the Biomial Coefficiets Wuyugaowa
More informationSome Integral Mean Estimates for Polynomials
Iteatioal Mathematical Foum, Vol. 8, 23, o., 5-5 HIKARI Ltd, www.m-hikai.com Some Itegal Mea Estimates fo Polyomials Abdullah Mi, Bilal Ahmad Da ad Q. M. Dawood Depatmet of Mathematics, Uivesity of Kashmi
More informationMinimal order perfect functional observers for singular linear systems
Miimal ode efect fuctioal obseves fo sigula liea systems Tadeusz aczoek Istitute of Cotol Idustial lectoics Wasaw Uivesity of Techology, -66 Waszawa, oszykowa 75, POLAND Abstact. A ew method fo desigig
More informationBINOMIAL THEOREM An expression consisting of two terms, connected by + or sign is called a
BINOMIAL THEOREM hapte 8 8. Oveview: 8.. A epessio cosistig of two tems, coected by + o sig is called a biomial epessio. Fo eample, + a, y,,7 4 5y, etc., ae all biomial epessios. 8.. Biomial theoem If
More informationRevision of Lecture Eight
Revision of Lectue Eight Baseband equivalent system and equiements of optimal tansmit and eceive filteing: (1) achieve zeo ISI, and () maximise the eceive SNR Thee detection schemes: Theshold detection
More informationBINOMIAL THEOREM NCERT An expression consisting of two terms, connected by + or sign is called a
8. Oveview: 8.. A epessio cosistig of two tems, coected by + o sig is called a biomial epessio. Fo eample, + a, y,,7 4, etc., ae all biomial 5y epessios. 8.. Biomial theoem BINOMIAL THEOREM If a ad b ae
More information( ) 1 Comparison Functions. α is strictly increasing since ( r) ( r ) α = for any positive real number c. = 0. It is said to belong to
Compaiso Fuctios I this lesso, we study stability popeties of the oautoomous system = f t, x The difficulty is that ay solutio of this system statig at x( t ) depeds o both t ad t = x Thee ae thee special
More informationLecture 24: Observability and Constructibility
ectue 24: Obsevability ad Costuctibility 7 Obsevability ad Costuctibility Motivatio: State feedback laws deped o a kowledge of the cuet state. I some systems, xt () ca be measued diectly, e.g., positio
More informationFinite q-identities related to well-known theorems of Euler and Gauss. Johann Cigler
Fiite -idetities elated to well-ow theoems of Eule ad Gauss Joha Cigle Faultät fü Mathemati Uivesität Wie A-9 Wie, Nodbegstaße 5 email: oha.cigle@uivie.ac.at Abstact We give geealizatios of a fiite vesio
More informationDiversity Combining Techniques
Diversity Combiig Techiques Whe the required sigal is a combiatio of several waves (i.e, multipath), the total sigal amplitude may experiece deep fades (i.e, Rayleigh fadig), over time or space. The major
More informationLesson 5. Chapter 7. Wiener Filters. Bengt Mandersson. r k s r x LTH. September Prediction Error Filter PEF (second order) from chapter 4
Optimal Sigal oceig Leo 5 Capte 7 Wiee Filte I ti capte we will ue te model ow below. Te igal ito te eceie i ( ( iga. Nomally, ti igal i ditubed by additie wite oie (. Te ifomatio i i (. Alo, we ofte ued
More information2012 GCE A Level H2 Maths Solution Paper Let x,
GCE A Level H Maths Solutio Pape. Let, y ad z be the cost of a ticet fo ude yeas, betwee ad 5 yeas, ad ove 5 yeas categoies espectively. 9 + y + 4z =. 7 + 5y + z = 8. + 4y + 5z = 58.5 Fo ude, ticet costs
More informationStrong Result for Level Crossings of Random Polynomials
IOSR Joual of haacy ad Biological Scieces (IOSR-JBS) e-issn:78-8, p-issn:19-7676 Volue 11, Issue Ve III (ay - Ju16), 1-18 wwwiosjoualsog Stog Result fo Level Cossigs of Rado olyoials 1 DKisha, AK asigh
More informationUsing Counting Techniques to Determine Probabilities
Kowledge ticle: obability ad Statistics Usig outig Techiques to Detemie obabilities Tee Diagams ad the Fudametal outig iciple impotat aspect of pobability theoy is the ability to detemie the total umbe
More informationUsing Difference Equations to Generalize Results for Periodic Nested Radicals
Usig Diffeece Equatios to Geealize Results fo Peiodic Nested Radicals Chis Lyd Uivesity of Rhode Islad, Depatmet of Mathematics South Kigsto, Rhode Islad 2 2 2 2 2 2 2 π = + + +... Vieta (593) 2 2 2 =
More informationMapping Radius of Regular Function and Center of Convex Region. Duan Wenxi
d Iteatioal Cofeece o Electical Compute Egieeig ad Electoics (ICECEE 5 Mappig adius of egula Fuctio ad Cete of Covex egio Dua Wexi School of Applied Mathematics Beijig Nomal Uivesity Zhuhai Chia 363463@qqcom
More informationDirection of Arrival Estimation Using the Extended Kalman Filter
SEI 7 4 th Iteatioal Cofeece: Scieces of Electoic, echologies of Ifomatio elecommuicatios Mach 5-9, 7 UISIA Diectio of Aival Estimatio Usig the Exteded alma Filte Feid Haabi*, Hatem Chaguel*, Ali Ghasallah*
More informationAcoustic Level Dynamic Compression Characteristics with FPGA Implementation
Poceedigs of te 7t WSEAS Iteatioal Cofeece o Sigal, Speec ad Image Pocessig, Beijig, Cia, Septembe 5-7, 27 8 Acoustic Level Dyamic Compessio Caacteistics wit FPGA Implemetatio Sugag Wei Depatmet of Poducatio
More informationThe Application of a Maximum Likelihood Approach to an Accelerated Life Testing with an Underlying Three- Parameter Weibull Model
Iteatioal Joual of Pefomability Egieeig Vol. 4, No. 3, July 28, pp. 233-24. RAMS Cosultats Pited i Idia The Applicatio of a Maximum Likelihood Appoach to a Acceleated Life Testig with a Udelyig Thee- Paamete
More informationChapter 8 Complex Numbers
Chapte 8 Complex Numbes Motivatio: The ae used i a umbe of diffeet scietific aeas icludig: sigal aalsis, quatum mechaics, elativit, fluid damics, civil egieeig, ad chaos theo (factals. 8.1 Cocepts - Defiitio
More informationTutorial on Strehl ratio, wavefront power series expansion, Zernike polynomials expansion in small aberrated optical systems By Sheng Yuan
Tutoial on Stel atio, wavefont powe seies expansion, Zenike polynomials expansion in small abeated optical systems By Seng Yuan. Stel Ratio Te wave abeation function, (x,y, is defined as te distance, in
More informationThe Multivariate-t distribution and the Simes Inequality. Abstract. Sarkar (1998) showed that certain positively dependent (MTP 2 ) random variables
The Multivaiate-t distibutio ad the Simes Iequality by Hey W. Block 1, Saat K. Saka 2, Thomas H. Savits 1 ad Jie Wag 3 Uivesity of ittsbugh 1,Temple Uivesity 2,Gad Valley State Uivesity 3 Abstact. Saka
More informationZERO - ONE INFLATED POISSON SUSHILA DISTRIBUTION AND ITS APPLICATION
ZERO - ONE INFLATED POISSON SUSHILA DISTRIBUTION AND ITS APPLICATION CHOOKAIT PUDPROMMARAT Depatmet of Sciece, Faculty of Sciece ad Techology, Sua Suadha Rajabhat Uivesity, Bagkok, Thailad E-mail: chookait.pu@ssu.ac.th
More informationApplied Mathematical Sciences, Vol. 2, 2008, no. 9, Parameter Estimation of Burr Type X Distribution for Grouped Data
pplied Mathematical Scieces Vol 8 o 9 45-43 Paamete stimatio o Bu Type Distibutio o Gouped Data M ludaat M T lodat ad T T lodat 3 3 Depatmet o Statistics Yamou Uivesity Ibid Joda aludaatm@hotmailcom ad
More informationAn Achievable Rate for the MIMO Individual Channel
A Achievable Rate fo the MIMO Idividual Chael Yuval Lomitz, Mei Fede Tel Aviv Uivesity, Dept. of EE-Systems Eml: {yuvall,mei}@eg.tau.ac.il Abstact We coside the poblem of commuicatig ove a multiple-iput
More informationProgression. CATsyllabus.com. CATsyllabus.com. Sequence & Series. Arithmetic Progression (A.P.) n th term of an A.P.
Pogessio Sequece & Seies A set of umbes whose domai is a eal umbe is called a SEQUENCE ad sum of the sequece is called a SERIES. If a, a, a, a 4,., a, is a sequece, the the expessio a + a + a + a 4 + a
More informationStrong Result for Level Crossings of Random Polynomials. Dipty Rani Dhal, Dr. P. K. Mishra. Department of Mathematics, CET, BPUT, BBSR, ODISHA, INDIA
Iteatioal Joual of Reseach i Egieeig ad aageet Techology (IJRET) olue Issue July 5 Available at http://wwwijetco/ Stog Result fo Level Cossigs of Rado olyoials Dipty Rai Dhal D K isha Depatet of atheatics
More informationphysicsandmathstutor.com
physicsadmathstuto.com physicsadmathstuto.com Jauay 2009 2 a 7. Give that X = 1 1, whee a is a costat, ad a 2, blak (a) fid X 1 i tems of a. Give that X + X 1 = I, whee I is the 2 2 idetity matix, (b)
More informationALLOCATING SAMPLE TO STRATA PROPORTIONAL TO AGGREGATE MEASURE OF SIZE WITH BOTH UPPER AND LOWER BOUNDS ON THE NUMBER OF UNITS IN EACH STRATUM
ALLOCATING SAPLE TO STRATA PROPORTIONAL TO AGGREGATE EASURE OF SIZE WIT BOT UPPER AND LOWER BOUNDS ON TE NUBER OF UNITS IN EAC STRATU Lawrece R. Erst ad Cristoper J. Guciardo Erst_L@bls.gov, Guciardo_C@bls.gov
More informationA note on random minimum length spanning trees
A ote o adom miimum legth spaig tees Ala Fieze Miklós Ruszikó Lubos Thoma Depatmet of Mathematical Scieces Caegie Mello Uivesity Pittsbugh PA15213, USA ala@adom.math.cmu.edu, usziko@luta.sztaki.hu, thoma@qwes.math.cmu.edu
More informationLESSON 15: COMPOUND INTEREST
High School: Expoeial Fuctios LESSON 15: COMPOUND INTEREST 1. You have see this fomula fo compoud ieest. Paamete P is the picipal amou (the moey you stat with). Paamete is the ieest ate pe yea expessed
More informationAuchmuty High School Mathematics Department Sequences & Series Notes Teacher Version
equeces ad eies Auchmuty High chool Mathematics Depatmet equeces & eies Notes Teache Vesio A sequece takes the fom,,7,0,, while 7 0 is a seies. Thee ae two types of sequece/seies aithmetic ad geometic.
More informationThis web appendix outlines sketch of proofs in Sections 3 5 of the paper. In this appendix we will use the following notations: c i. j=1.
Web Appedix: Supplemetay Mateials fo Two-fold Nested Desigs: Thei Aalysis ad oectio with Nopaametic ANOVA by Shu-Mi Liao ad Michael G. Akitas This web appedix outlies sketch of poofs i Sectios 3 5 of the
More informationFitting the Generalized Logistic Distribution. by LQ-Moments
Applied Mathematical Scieces, Vol. 5, 0, o. 54, 66-676 Fittig the Geealized Logistic Distibutio by LQ-Momets Ai Shabi Depatmet of Mathematic, Uivesiti Teologi Malaysia ai@utm.my Abdul Aziz Jemai Scieces
More informationModelling rheological cone-plate test conditions
ANNUAL TRANSACTIONS OF THE NORDIC RHEOLOGY SOCIETY, VOL. 16, 28 Modellig heological coe-plate test coditios Reida Bafod Schülle 1 ad Calos Salas-Bigas 2 1 Depatmet of Chemisty, Biotechology ad Food Sciece,
More informationECEN 5014, Spring 2013 Special Topics: Active Microwave Circuits and MMICs Zoya Popovic, University of Colorado, Boulder
ECEN 5014, Spig 013 Special Topics: Active Micowave Cicuits ad MMICs Zoya Popovic, Uivesity of Coloado, Boulde LECTURE 7 THERMAL NOISE L7.1. INTRODUCTION Electical oise is a adom voltage o cuet which is
More informationDisjoint Sets { 9} { 1} { 11} Disjoint Sets (cont) Operations. Disjoint Sets (cont) Disjoint Sets (cont) n elements
Disjoit Sets elemets { x, x, } X =, K Opeatios x Patitioed ito k sets (disjoit sets S, S,, K Fid-Set(x - etu set cotaiig x Uio(x,y - make a ew set by combiig the sets cotaiig x ad y (destoyig them S k
More informationLecture 2: Stress. 1. Forces Surface Forces and Body Forces
Lectue : Stess Geophysicists study pheomea such as seismicity, plate tectoics, ad the slow flow of ocks ad mieals called ceep. Oe way they study these pheomea is by ivestigatig the defomatio ad flow of
More informationLacunary Almost Summability in Certain Linear Topological Spaces
BULLETIN of te MLYSİN MTHEMTİCL SCİENCES SOCİETY Bull. Malays. Mat. Sci. Soc. (2) 27 (2004), 27 223 Lacuay lost Suability i Cetai Liea Topological Spaces BÜNYMIN YDIN Cuuiyet Uivesity, Facutly of Educatio,
More information4 Conditional Distribution Estimation
4 Coditioal Distributio Estimatio 4. Estimators Te coditioal distributio (CDF) of y i give X i = x is F (y j x) = P (y i y j X i = x) = E ( (y i y) j X i = x) : Tis is te coditioal mea of te radom variable
More informationConsider unordered sample of size r. This sample can be used to make r! Ordered samples (r! permutations). unordered sample
Uodeed Samples without Replacemet oside populatio of elemets a a... a. y uodeed aagemet of elemets is called a uodeed sample of size. Two uodeed samples ae diffeet oly if oe cotais a elemet ot cotaied
More informationA Method for Solving Fuzzy Differential Equations using fourth order Runge-kutta Embedded Heronian Means
ISSN (Pit) : 2347-6710 Iteatioal Joual of Iovative Reseac i Sciece, Egieeig ad Tecology (A ISO 3297: 2007 Cetified Ogaizatio) Vol. 5, Issue 3, Mac 2016 A Metod fo Solvig Fuzzy Diffeetial Equatios usig
More informationr, this equation is graphed in figure 1.
Washigto Uivesity i St Louis Spig 8 Depatmet of Ecoomics Pof James Moley Ecoomics 4 Homewok # 3 Suggested Solutio Note: This is a suggested solutio i the sese that it outlies oe of the may possible aswes
More informationL8b - Laplacians in a circle
L8b - Laplacias i a cicle Rev //04 `Give you evidece,' the Kig epeated agily, `o I'll have you executed, whethe you'e evous o ot.' `I'm a poo ma, you Majesty,' the Hatte bega, i a temblig voice, `--ad
More informationSupplementary materials. Suzuki reaction: mechanistic multiplicity versus exclusive homogeneous or exclusive heterogeneous catalysis
Geeal Pape ARKIVOC 009 (xi 85-03 Supplemetay mateials Suzui eactio: mechaistic multiplicity vesus exclusive homogeeous o exclusive heteogeeous catalysis Aa A. Kuohtia, Alexade F. Schmidt* Depatmet of Chemisty
More informationLacunary Weak I-Statistical Convergence
Ge. Mat. Notes, Vol. 8, No., May 05, pp. 50-58 ISSN 9-784; Copyigt ICSRS Publicatio, 05 www.i-css.og vailable ee olie at ttp//www.gema.i Lacuay Wea I-Statistical Covegece Haize Gümüş Faculty o Eegli Educatio,
More informationGeneralized Near Rough Probability. in Topological Spaces
It J Cotemp Math Scieces, Vol 6, 20, o 23, 099-0 Geealized Nea Rough Pobability i Topological Spaces M E Abd El-Mosef a, A M ozae a ad R A Abu-Gdaii b a Depatmet of Mathematics, Faculty of Sciece Tata
More informationSome Properties of the K-Jacobsthal Lucas Sequence
Deepia Jhala et. al. /Iteatioal Joual of Mode Scieces ad Egieeig Techology (IJMSET) ISSN 349-3755; Available at https://www.imset.com Volume Issue 3 04 pp.87-9; Some Popeties of the K-Jacobsthal Lucas
More informationMATH /19: problems for supervision in week 08 SOLUTIONS
MATH10101 2018/19: poblems fo supevisio i week 08 Q1. Let A be a set. SOLUTIONS (i Pove that the fuctio c: P(A P(A, defied by c(x A \ X, is bijective. (ii Let ow A be fiite, A. Use (i to show that fo each
More informationDANIEL YAQUBI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD
MIXED -STIRLING NUMERS OF THE SEOND KIND DANIEL YAQUI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD Abstact The Stilig umbe of the secod id { } couts the umbe of ways to patitio a set of labeled balls ito
More informationIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 61, NO. 8, OCTOBER
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 61, NO. 8, OCTOBER 2012 3615 Powe Allocatio ad Goup Assigmet fo Reducig Netwo Codig Noise i Multi-Uicast Wieless Systems Zaha Mobii, Studet Membe, IEEE,
More informationA Galerkin Finite Element Method for Two-Point Boundary Value Problems of Ordinary Differential Equations
Applied ad Computatioal Matematics 5; 4(: 64-68 Publised olie Mac 9, 5 (ttp://www.sciecepublisiggoup.com/j/acm doi:.648/j.acm.54.5 ISS: 38-565 (Pit; ISS: 38-563 (Olie A Galeki Fiite Elemet Metod fo Two-Poit
More informationTechnical Report: Bessel Filter Analysis
Sasa Mahmoodi 1 Techical Repot: Bessel Filte Aalysis 1 School of Electoics ad Compute Sciece, Buildig 1, Southampto Uivesity, Southampto, S17 1BJ, UK, Email: sm3@ecs.soto.ac.uk I this techical epot, we
More informationApplications of the Dirac Sequences in Electrodynamics
Poc of the 8th WSEAS It Cof o Mathematical Methods ad Computatioal Techiques i Electical Egieeig Buchaest Octobe 6-7 6 45 Applicatios of the Diac Sequeces i Electodyamics WILHELM W KECS Depatmet of Mathematics
More informationMinimization of the quadratic test function
Miimizatio of the quadatic test fuctio A quadatic fom is a scala quadatic fuctio of a vecto with the fom f ( ) A b c with b R A R whee A is assumed to be SPD ad c is a scala costat Note: A symmetic mati
More informationOn a Problem of Littlewood
Ž. JOURAL OF MATHEMATICAL AALYSIS AD APPLICATIOS 199, 403 408 1996 ARTICLE O. 0149 O a Poblem of Littlewood Host Alze Mosbache Stasse 10, 51545 Waldbol, Gemay Submitted by J. L. Bee Received May 19, 1995
More informationINVERSE CAUCHY PROBLEMS FOR NONLINEAR FRACTIONAL PARABOLIC EQUATIONS IN HILBERT SPACE
IJAS 6 (3 Febuay www.apapess.com/volumes/vol6issue3/ijas_6_3_.pdf INVESE CAUCH POBLEMS FO NONLINEA FACTIONAL PAABOLIC EQUATIONS IN HILBET SPACE Mahmoud M. El-Boai Faculty of Sciece Aleadia Uivesit Aleadia
More informationModels of network routing and congestion control
Models of etok outig ad cogestio cotol Fak Kelly, Cambidge statslabcamacuk/~fak/tlks/amhesthtml Uivesity of Massachusetts mhest, Mach 26, 28 Ed-to-ed cogestio cotol sedes eceives Sedes lea though feedback
More informationVRS Virtual Observations Generation Algorithm
Joual of Gloal Positioig Systems (006) Vol. 5 No. -:76-8 VRS Vitual Osevatios Geeatio Algoithm Ehu Wei Hua Chai Zhiguo A School of Geodesy ad Geomatics Wuha Uivesity 9 Luoyu RoadWuha 430079Chia Jiga Liu
More informationOn the Explicit Determinants and Singularities of r-circulant and Left r-circulant Matrices with Some Famous Numbers
O the Explicit Detemiats Sigulaities of -ciculat Left -ciculat Matices with Some Famous Numbes ZHAOLIN JIANG Depatmet of Mathematics Liyi Uivesity Shuaglig Road Liyi city CHINA jzh08@siacom JUAN LI Depatmet
More informationGeneralized Fibonacci-Lucas Sequence
Tuish Joual of Aalysis ad Numbe Theoy, 4, Vol, No 6, -7 Available olie at http://pubssciepubcom/tjat//6/ Sciece ad Educatio Publishig DOI:6/tjat--6- Geealized Fiboacci-Lucas Sequece Bijeda Sigh, Ompaash
More informationThe Pigeonhole Principle 3.4 Binomial Coefficients
Discete M athematic Chapte 3: Coutig 3. The Pigeohole Piciple 3.4 Biomial Coefficiets D Patic Cha School of Compute Sciece ad Egieeig South Chia Uivesity of Techology Ageda Ch 3. The Pigeohole Piciple
More informationThe Discrete Fourier Transform
(7) The Discete Fouie Tasfom The Discete Fouie Tasfom hat is Discete Fouie Tasfom (DFT)? (ote: It s ot DTFT discete-time Fouie tasfom) A liea tasfomatio (mati) Samples of the Fouie tasfom (DTFT) of a apeiodic
More informationChapter 2 The Monte Carlo Method
Chapter 2 The Mote Carlo Method The Mote Carlo Method stads for a broad class of computatioal algorithms that rely o radom sampligs. It is ofte used i physical ad mathematical problems ad is most useful
More informationLecture 7 Testing Nonlinear Inequality Restrictions 1
Eco 75 Lecture 7 Testig Noliear Iequality Restrictios I Lecture 6, we discussed te testig problems were te ull ypotesis is de ed by oliear equality restrictios: H : ( ) = versus H : ( ) 6= : () We sowed
More informationLesson 5. Chapter 7. Wiener Filters. Bengt Mandersson. r x k We assume uncorrelated noise v(n). LTH. September 2010
Optimal Sigal Poceig Leo 5 Chapte 7 Wiee Filte I thi chapte we will ue the model how below. The igal ito the eceive i ( ( iga. Nomally, thi igal i ditubed by additive white oie v(. The ifomatio i i (.
More informationEffect of Material Gradient on Stresses of Thick FGM Spherical Pressure Vessels with Exponentially-Varying Properties
M. Zamai Nejad et al, Joual of Advaced Mateials ad Pocessig, Vol.2, No. 3, 204, 39-46 39 Effect of Mateial Gadiet o Stesses of Thick FGM Spheical Pessue Vessels with Expoetially-Vayig Popeties M. Zamai
More informationELEMENTARY AND COMPOUND EVENTS PROBABILITY
Euopea Joual of Basic ad Applied Scieces Vol. 5 No., 08 ELEMENTARY AND COMPOUND EVENTS PROBABILITY William W.S. Che Depatmet of Statistics The Geoge Washigto Uivesity Washigto D.C. 003 E-mail: williamwsche@gmail.com
More informationDepartment of Mathematics, IST Probability and Statistics Unit
Depatmet of Mathematics, IST Pobability ad Statistics Uit Reliability ad Quality Cotol d. Test ( Recuso) st. Semeste / Duatio: hm // 9:AM, Room V. Please justify you aswes. This test has two pages ad fou
More informationRange Symmetric Matrices in Minkowski Space
BULLETIN of the Bull. alaysia ath. Sc. Soc. (Secod Seies) 3 (000) 45-5 LYSIN THETICL SCIENCES SOCIETY Rae Symmetic atices i ikowski Space.R. EENKSHI Depatmet of athematics, amalai Uivesity, amalaiaa 608
More informationStability analysis of numerical methods for stochastic systems with additive noise
Stability aalysis of umerical metods for stoctic systems wit additive oise Yosiiro SAITO Abstract Stoctic differetial equatios (SDEs) represet pysical peomea domiated by stoctic processes As for determiistic
More informationIDENTITIES FOR THE NUMBER OF STANDARD YOUNG TABLEAUX IN SOME (k, l)-hooks
Sémiaie Lothaigie de Combiatoie 63 (010), Aticle B63c IDENTITIES FOR THE NUMBER OF STANDARD YOUNG TABLEAUX IN SOME (k, l)-hooks A. REGEV Abstact. Closed fomulas ae kow fo S(k,0;), the umbe of stadad Youg
More informationCalculation of Matrix Elements in the Foldy-Wouthuysen Representation
Calculatio of Matix Elemets i the Foldy-Wouthuyse Repesetatio V.P. Nezamov*, A.A.Sadovoy**, A.S.Ul yaov*** RFNC-VNIIEF, Saov, Russia Abstact The pape compaes the methods used to calculate matix elemets
More informationSOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES
#A17 INTEGERS 9 2009), 181-190 SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES Deick M. Keiste Depatmet of Mathematics, Pe State Uivesity, Uivesity Pak, PA 16802 dmk5075@psu.edu James A. Selles Depatmet
More informationTHE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 16, Number 2/2015, pp
THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Seies A, OF THE ROMANIAN ACADEMY Volume 6, Numbe 2/205, pp 2 29 ON I -STATISTICAL CONVERGENCE OF ORDER IN INTUITIONISTIC FUZZY NORMED SPACES Eem
More informationMath 166 Week-in-Review - S. Nite 11/10/2012 Page 1 of 5 WIR #9 = 1+ r eff. , where r. is the effective interest rate, r is the annual
Math 66 Week-i-Review - S. Nite // Page of Week i Review #9 (F-F.4, 4.-4.4,.-.) Simple Iteest I = Pt, whee I is the iteest, P is the picipal, is the iteest ate, ad t is the time i yeas. P( + t), whee A
More informationFault Tolerant Sensor Networks with Bernoulli Nodes
Fault Toleat Seso Netwoks with Beoulli Nodes Chih-Wei Yi Peg-Ju Wa iag-yag Li Ophi Fiede The Depatmet of Compute Sciece Illiois Istitute of Techology 0 West 3st Steet, Chicago, IL 6066, USA Email: yichihw@iit.edu,
More informationSTRUCTURE OF ATOM -2 (Test)
STRUTURE OF TOM - (Test) o s Model, Hydoge Spectum, Potoelectic effect RE THE INSTRUTIONS REFULLY. Te test is of ous duatio.. Te maximum maks ae 75. 3. Tis test cosists of 55 questios. 4. Fo eac questio
More informationIntroduction to the Theory of Inference
CSSM Statistics Leadeship Istitute otes Itoductio to the Theoy of Ifeece Jo Cye, Uivesity of Iowa Jeff Witme, Obeli College Statistics is the systematic study of vaiatio i data: how to display it, measue
More informationA Generalization of the Deutsch-Jozsa Algorithm to Multi-Valued Quantum Logic
A Geealizatio of the Deutsch-Jozsa Algoithm to Multi-Valued Quatum Logic Yale Fa The Catli Gabel School 885 SW Baes Road Potlad, OR 975-6599, USA yalefa@gmail.com Abstact We geealize the biay Deutsch-Jozsa
More informationCh 3.4 Binomial Coefficients. Pascal's Identit y and Triangle. Chapter 3.2 & 3.4. South China University of Technology
Disc ete Mathem atic Chapte 3: Coutig 3. The Pigeohole Piciple 3.4 Biomial Coefficiets D Patic Cha School of Compute Sciece ad Egieeig South Chia Uivesity of Techology Pigeohole Piciple Suppose that a
More informationME 354, MECHANICS OF MATERIALS LABORATORY MECHANICAL PROPERTIES AND PERFORMANCE OF MATERIALS: TORSION TESTING*
ME 354, MECHANICS OF MATEIALS LABOATOY MECHANICAL POPETIES AND PEFOMANCE OF MATEIALS: TOSION TESTING* MGJ/08 Feb 1999 PUPOSE The pupose of this execise is to obtai a umbe of expeimetal esults impotat fo
More information