Minimal Detectable Biases of GPS observations for a weighted ionosphere

Size: px
Start display at page:

Download "Minimal Detectable Biases of GPS observations for a weighted ionosphere"

Transcription

1 LETTER Eath Planets Space, 52, , 2000 Mnmal Detectable Bases of GPS obsevatons fo a weghted onosphee K. de Jong and P. J. G. Teunssen Depatment of Mathematcal Geodesy and Postonng, Delft Unvesty of Technology, Thjsseweg 11, 2629 JA Delft, The Nethelands (Receved Novembe 25, 1999; Revsed May 19, 2000; Accepted May 19, 2000) The theoy and applcaton of statstcal qualty contol s well establshed n pecse postonng, navgaton and geodesy. Qualty contol s made up of seveal contbutng factos, one of whch s ntenal elablty. Intenal elablty descbes the ablty to fnd bases n obsevatonal data and s epesented by the Mnmal Detectable Bas (MDB). The MDB povdes a dagnostc tool to nfe the stength wth whch postonng models can be valdated. In ths contbuton closed-fom expessons wll be gven fo the MDBs of GPS code and cae obsevatons fo thee dffeent baselne models: the geomety-fee model and two vaants of the geomety-based model. These expessons apply to any numbe of cae fequences. The expessons take nto account the pesence of onosphec dstubances by weghtng these effects. As such, they ae applcable to baselnes of any length. 1. Intoducton Mnmal Detectable Bases (MDBs) as ntoduced by Baada (1967, 1968) ae mpotant dagnostc tools fo nfeng the stength of model valdaton. They ae sad to descbe the ntenal elablty of a system. MDBs can also be used to study the stength of the vaous GPS postonng models (sngle eceve, baselne and netwok). In de Jong (1999) analytc expessons ae gven fo the MDBs of outles and cycle slps n GPS code and cae obsevatons fo a sngle baselne. In devng these expessons, t was assumed that onosphec effects may not always be elmnated when dffeencng between eceves. Snce the nfluence of the onosphee wll ncease wth nceasng baselne length, an onosphec weghtng facto was ntoduced to account fo the onosphec effects. Settng ths facto to zeo coesponds to the shot baselne case. The MDBs fo shot baselnes wee aleady deved n Teunssen (1998). In ths pape, smplfed expessons, whch ae easy to mplement, wll be gven fo the code and cae MDBs fo thee dffeent baselne models. These expessons ae vald not only fo sngle- and dual-fequency data, but fo any numbe of cae fequences. In Secton 2 a bef evew s gven of the concept of ntenal elablty. Secton 3 gves a summay of the measuement models fo the thee sngle-baselne models, ntoduced n Teunssen (1998), togethe wth the stochastc model. In the last two sectons the smplfed expessons fo the MDBs of code and cae obsevatons ae gven. 2. Intenal Relablty Intenal elablty, as epesented by the MDBs, descbes the sze of the model eos that can just be detected usng the appopate test statstcs. Fo moe detals, the eade s efeed to, fo example, Baada (1968) o Teunssen (1985). Copy ght c The Socety of Geomagnetsm and Eath, Planetay and Space Scences (SGEPSS); The Sesmologcal Socety of Japan; The Volcanologcal Socety of Japan; The Geodetc Socety of Japan; The Japanese Socety fo Planetay Scences. The null hypothess H 0 descbes the case model eos ae absent. The altenatve hypothess H a consdeed hee assumes thee s a bas n one of the obsevatons. These two hypotheses ae defned as H 0 : E{y} =Ax, D{y} =Q y, (1) H a : E{y} =Ax + c, D{y} =Q y, (2) whee E{.} and D{.} ae the expectaton and dspeson opeatos, espectvely, y the m-vecto of obsevatons, x the n-vecto of unknown paametes, A the mxn desgn matx, c a known m-vecto, whch specfes the type of model eo, and ts unknown sze. The unfomly most poweful test statstc fo testng H 0 aganst H a s gven as whee the pojecto P A P A T = ct Q 1 y PA y c T Q 1 y PA c (3) s defned as = I A(AT Q 1 y A) 1 A T Q 1 y. (4) The test statstc T has a Ch-squaed dstbuton, whch s cental unde H 0 and non-cental unde H a. The noncentalty paamete λ 0 s a measue of the dstance between H 0 and H a. Ths non-centalty paamete can be computed once efeence values ae chosen fo the level of sgnfcance (the pobablty of ejectng H 0 when t s tue) and the detecton powe (the pobablty of ejectng H 0 when H a s tue). Once the paamete s known, the coespondng sze of the bas that can just be detected s gven as λ 0 = c T Q 1 y PA c. (5) Ths s the Mnmal Detectable Bas. Fo most pactcal applcatons, α 0 = and γ 0 = 0.80, esultng n a noncentalty paamete λ 0 = 17. As can be seen fom (5), 857

2 858 K. DE JONG AND P. J. G. TEUNISSEN: MDBS OF GPS OBSERVATIONS the MDB not only depends on α 0 and γ 0, but also on the functonal and stochastc model, though the desgn matx A and the covaance matx Q y, and the altenatve hypothess consdeed, as epesented by the vecto c. The altenatve hypotheses consdeed hee consst of outles and cycle slps n GPS code and cae obsevatons, espectvely. 3. Baselne Models The double dffeence (DD) measuement model fo two eceves each tackng the satelltes and s at an epoch t, can be wtten as p s (t) = ρ s (t) + µ I s (t) + n s φ s p (t), (t) = ρ s (t) µ I s (t) + λ N s = 1 f + n s φ (t) (6) whee f s the numbe of fequences, p s and φ s ae the DD code and cae obsevatons, expessed n metes, ρ s the unknown satellte-eceve DD ange, N s the DD / cae ambgutes, λ the cae wavelengths, µ = (λ λ1 ) 2, I s the DD onosphec effect and n s p and n s φ the DD measuement nose of code and cae. It s assumed hee that toposphec effects ae ethe absent o accounted fo usng the appopate models. Intoducng the onosphec pseudoobsevable I P, wth sample values taken e.g. fom an extenal onosphec model, the onosphec paamete can be elmnated fom (6), esultng n p s φ s (t) = p s (t) µ IP s (t) = ρ s (t) + n s p (t), (t) = φ s (t) + µ I s = ρ s (t) + λ N s = 1 f P (t) + n s φ (t) (7) Usng (7) the measuement model can be fomulated fo the thee baselne models, consdeed hee. Geomety-fee. Fo the geomety-fee (GF) model the obsevaton equatons eman paametzed n tems of the unknown DD eceve-satellte anges. As a esult, they eman lnea and the eceve-satellte geomety s not explctly pesent n the measuement model. Ths means that the eceves may ethe be statonay o movng. Ths model has been studed n patcula fo cae phase ambguty esoluton (Eule and Goad, 1991; Teunssen, 1996; Jonkman, 1998), and valdaton of GPS code and cae obsevatons (de Jong, 1996, 1997, 1998). Thus, when m satelltes ae tacked, thee ae 2(m 1) DD measuements pe fequency fo each epoch. The edundancy of the model equals (m 1)((2 f 1)k f ), whee k denotes the numbe of obsevaton epochs. In ode to have edundancy, at least two satelltes should be obseved and the numbe of epochs k should be geate than f/(2 f 1). Fo f = 1, ths means k should be geate than one, fo all othe (mult-fequency) cases, k should at least be equal to one. Rovng eceve. Fo the ovng eceve (RR) model, one eceve s statonay, wheeas the othe one s movng. The DD obsevaton equatons ae paametzed n tems of the unknown baselne components. Fo each obsevaton epoch, a new baselne s ntoduced. The RR model s a geometybased model, snce the eceve-satellte geomety appeas n the obsevaton equatons though the lneazed (n tems of the baselne components) DD anges. Fo a sngle epoch the lneazed expesson fo ρ(t) (contanng the DD anges fo m 1 satellte pas) s gven by ρ(t) = ρ(t) ρ(t) 0 = G(t) b(t) (8) whee ρ(t) 0 denotes the DD ange, computed at some ntal value, b(t) the coectons to the ntal baselne vecto b(t) 0 at epoch t and G(t) the (m 1)x3 DD desgn matx, whch takes nto account the elatve eceve-satellte geomety. Ths geomety changes only slowly wth tme, due to the hgh alttude of the GPS satelltes. In ou futhe analyss we wll consde only shot obsevaton tme spans. Theefoe G(t) wll be assumed tme-nvaant,.e., G(t) = G fo all k epochs. The edundancy fo ths model equals f (m 1)(2k 1) 3k. Fo the baselne components to be estmable, the mnmum value of m s fou. If k = 1 and f = 1, edundancy exsts f m > 4; fo all othe cases, m should at least be equal to fou. Statonay eceve. Ths s also a geomety-based model. Fo the statonay eceve (SR) model, both eceves ae statonay. The DD obsevaton equatons ae agan paametzed n tems of the baselne components. Fo ths model, the baselne s the same fo all obsevaton epochs. As a consequence, the edundancy, compaed to the ovng eceve model, s nceased by 3(k 1) and equal to f (m 1)(2k 1) 3. It follows fom (5) that n ode to compute MDBs, the stochastc model of the obsevatons s equed. In Teunssen (1998) and de Jong (1999) the MDBs ae deved fo a vey geneal model, whch allows fo coelaton between obsevatons and a dffeent pecson fo each fequency. Hee we wll consde only a vey smple stochastc model, whch s wdely used n pactce. The stochastc model fo the sngle-dffeenced code, cae and onosphec obsevatons to a patcula satellte s, s assumed to be gven by C s pφ = w s dag(c 2 p I f c 2 φ I f ), σ 2 I s P = w s s 2 (9) whee w s s a satellte-dependent weghtng facto and I f the f x f dentty matx. Though the weghtng facto t s possble to assgn dffeent weghts to each satellte, fo example, dependng on the elevaton. In that case the weghtng facto becomes tme-dependent. Howeve, as was done fo the geomety, fo shot obsevaton tme spans t s taken as a constant. Elmnatng the onosphec paametes usng the obsevable I P esults n the covaance matx C s pφi of the obsevatons (( ) C s pφi = w c 2 p s I f cφ 2 I f ( )( + s 2 µ µ µ µ ) T (10)

3 K. DE JONG AND P. J. G. TEUNISSEN: MDBS OF GPS OBSERVATIONS 859 whee µ = (µ 1...µ f ) T. If the onosphee s absent o assumed known, s 2 = 0; f the onosphec behavo s completely unknown, s 2. Addng a pseudo-obsevable wth nfnte vaance s equvalent to ntoducng an addtonal paamete. Theefoe, the edundancy of each of the thee baselne models deceases by k(m 1). The two exteme cases ae geneally efeed to as onosphee fxed and onosphee float. In pactce s 2 may often vay between these two exteme values, dependng on the baselne length (Schaffn and Bock, 1988). 4. Code Outle MDBs The MDBs fo outles n code data wll be gven, based on the devatons n de Jong (1999) and Teunssen (1998) fo the sngle dffeence (SD) obsevables. The cae-tocode vaance ato, whch n pactce s of the ode of 10 4, can be neglected hee. Togethe wth the assumptons of constant eceve-satellte geomety and constant weghtng factos, ths esults n elatvely smple expessons. Fo an outle at epoch l, 1 l k, n the SD code obsevable p, = 1,..., f, to satellte {1,...,m}, we get fo the geomety-fee model { [ p =σ p λ 0 / {1 1 k [F 1(µ )F 2 (c 2 p ) Fg. 1. Dual- and tple-fequency geomety-fee L1 code MDBs as functon of onosphec vaance; numbe of satelltes s equal to fve. +F 3 (µ )]}(1 w ) and fo the ovng eceve model [ p =σ p {λ 0 {1 1 k [F 1(µ )F 2 (c 2 p ) ]} 1/2 (11) + F 3 (µ )]}(1 w ) ]} 1/2. (12) Wthn the appoxmatons used, the code outle MDBs fo the ovng and statonay eceve models ae the same. The quanttes that appea n (11) and (12) ae defned as F 1 (x) = s 2 x/(c 2 φ + s2 F 2 (x) = (1 + x/(s 2 F 3 (x) = (c 2 p + s2 µ = 1 f µ 2 j ), (13) µ 2 j )) 1, (14) µ j (µ j x)) 2 { / f (c 2 p + s2 µ 2 j ) } (c 2 p + s2 (µ j µ) 2 ), (15) µ j, (16) P [Gem ] = (Ge m )[(Ge m ) T (Ge m )] 1 (Ge m ) T, (17) whee (Ge m ) s the mx4 sngle dffeence desgn matx. If D T s the (m 1)xm matx whch tansfoms sngle nto Fg. 2. Dual- and tple-fequency geomety-based L1 code MDBs as functon of onosphec vaance; numbe of satelltes s equal to fve. double dffeences, then G = D T G and D T e m = 0. The m-vecto e m has all ones as ts entes. If all satelltes ae assgned the same weght, we get 1 w / = 1 1/m (18) a stuaton whch s assumed by most softwae packages developed fo pocessng GPS data. In that case the MDBs fo all satelltes, fo a patcula fequency and baselne model, ae the same. If m, the numbe of tacked satelltes, equals fou, the desgn matx (Ge m ) s a squae matx and the pojecto P [Gem ] educes to the dentty matx. As a esult, the tem 1 c T P [Gem ]c becomes zeo and the MDBs fo all thee baselne models become the same. A futhe appoxmaton s possble by ealzng that c T P [Gem ]c s the -th dagonal element of the pojecto P [Gem ] and that the tace of ths matx s equal to ts ank, whch s fou. The aveage value of the dagonal elements of ths mxm matx s theefoe equal to 4/m, esultng n an aveage value of 1 c T P [Gem ]c = (m 4)/m.

4 860 K. DE JONG AND P. J. G. TEUNISSEN: MDBS OF GPS OBSERVATIONS Fg. 3. Dual- and tple-fequency geomety-fee L1 cae MDBs as functon of onosphec vaance and fo a slp wndow of one epoch; numbe of satelltes s equal to fve. Fg. 5. Dual- and tple-fequency ovng-eceve L1 cae MDBs as functon of onosphec vaance and fo a slp wndow of one epoch; numbe of epochs s equal to two. Fg. 4. Dual- and tple-fequency geomety-fee L1 cae MDBs as functon of onosphec vaance and fo a slp wndow of one epoch; numbe of epochs s equal to two. Fg. 6. Dual-fequency geomety-fee onosphee float L1 cae MDBs as functon of numbe of obsevaton epochs and sze of slp wndow; numbe of satelltes s equal to fou. Based on these smplfyng assumptons, dual- and tplefequency geomety-fee and geomety-based code outle MDBs wee computed as a functon of the onosphec vaance fo k = 1 and k = 10. They ae shown n Fg. 1 and 2. Fo these and all othe examples that follow, the noncentalty paamete λ 0 was set to 17 and the sngle dffeence standad devatons of code and cae to 0.3 m and m, espectvely. Fo the dual-fequency geomety-fee onosphee float case thee s no edundancy and as a consequence the MDB becomes nfnte. Compang the MDBs of Fg. 1 and 2 we may conclude that when the numbe of epochs nceases, the dual- and tple-fequency MDBs fo both baselne models become moe o less the same. In othe wods, the numbe of epochs becomes the man contbutng facto to the edundancy. 5. Cae Slp MDBs Cae slp MDBs wll be expessed n unts of ange athe than n unts of cycles. Whee appopate, the cae-to- code vaance ato wll be gnoed. Fo a slp at epoch l, 1 l k, n the SD cae obsevable φ, = 1,..., f,to satellte {1,...,m}, we get fo the thee baselne models (geomety-fee, ovng eceve and statonay eceve, espectvely) φ = σ φ {λ 0 /[(1 N N k )(1 w ) {1 F 1 (µ ) F 4 (µ )}]} 1/2, (19) φ = σ φ N {λ 0 /[(1 N k ){(1 F 1(µ ) F 4(µ ) F 5 (µ ) )(1 w ) + F 4(µ ) } 1/2, F 5 (µ ) (1 ct P [Gem ]c )}] (20)

5 K. DE JONG AND P. J. G. TEUNISSEN: MDBS OF GPS OBSERVATIONS 861 φ = σ φ {λ 0 /[(1 N N k )(1 w ) (1 F 1 (µ ))]} 1/2 (21) whee N s the slp wndow,.e., the peod fo whch the slp s assumed pesent n the data, defned as N = k l + 1. Functons F 4 and F 5 ae defned as F 4 (x) = F 5 (x) = (c 2 φ + s2 ( c φ 2 + s 2 {(1 + ε) (1 ε)x µ 2 j ) µ 2 j 2 µ j }), (22) ( f (1 + ε) {c 2 φ + s2 (1 + ε) s 2 (1 ε) 2 ( µ 2 j } µ j ) 2) (23) whee ε s the cae-to-code vaance ato. It appeas that ths ato s sgnfcant only fo the geomety-fee baselne model fo lage values of s 2 ; fo the geomety-based models, t can be gnoed. Note that f N = k the cae slp MDBs become nfnte. In ths case a slp cannot (and does not have to) be sepaated fom the cae ambguty. As a consequence, cae MDBs can only be computed fo 1 < k < N. Unlke the code outle MDBs, the cae slp MDBs fo the ovng and statonay eceve ae not the same. Lke the geomety-fee cae MDBs, the statonay eceve cae MDBs ae ndependent of the eceve-satellte geomety. The geomety-fee MDBs ae lage than the statonay eceve MDBs, snce F 4 (µ )/F 5 (µ )>0. The ovng eceve MDBs ae n between those of the geomety-fee and statonay eceve models. In ths case addtonal edundancy makes a dffeence wth egad to ntenal elablty. If the numbe of satelltes m s equal to fou, the geometyfee and ovng eceve MDBs become the same. Shown n Fg. 3 ae the dual- and tple-fequency L1 cae MDBs, agan as a functon of the onosphec vaance, fo k = 2 and k = 10. The slp wndow N was set to one. Even fo the dual-fequency geomety-fee onosphee float model thee s edundancy when k = 2 and the MDBs ae fnte. Howeve, the dual-fequency cae MDBs ncease apdly to ove one cycle wth nceasng onosphec vaance. Fo the tple-fequency case, howeve, all MDBs eman well below the sngle cycle level. The geomety-fee cae MDBs wee computed agan, ths tme not as a functon of the numbe of epochs, but as a functon of the numbe of satelltes. The esults ae shown n Fg. 4, fom whch we may conclude that the dualfequency geomety-fee cae MDBs ae of the same ode of magntude as those of Fg 3. Fo compason, the ovng eceve L1 cae MDBs ae shown n Fg 5. As aleady mentoned, when the numbe of satelltes s equal to fou, the geomety-fee and ovng-eceve MDBs ae the same. When, howeve, the numbe of satelltes s nceased fom fou to fve, we see a sgnfcant decease n the sze of the MDBs. Ths decease may be attbuted to the nfluence of the eceve-satellte geomety. The statonay-eceve cae MDBs, not shown hee, ae of the ode of a few cm and ae hadly affected by the numbe of fequences, the numbe of satelltes and the onosphec vaance. It s possble to decease the sze of the dual-fequency geomety-fee cae MDBs to below the sngle cycle level. Ths s accomplshed by nceasng both the numbe of epochs k and the sze of the slp wndow N. The dualfequency geomety-fee onosphee float cae MDBs fo fou satelltes as a functon of these two paametes ae shown n Fg 6. The MDBs ae symmetc aound k/2 and ae aleady of the ode of 0.15 m fo k = 10 and N = 3o N = Conclusons Expessons wee gven fo code and cae outle MDBs fo thee dffeent baselne models, whch apply to any numbe of cae fequences. The expessons ae vald fo baselnes of any length, snce onosphec dstubances ae taken nto account by weghtng these effects. The specfc cases consdeed hee appled to dual- and tple-fequency data. If onosphec effects cannot be gnoed, addng a thd fequency s less mpotant fo educng the sze of the code MDBs than nceasng the numbe of epochs. Aleady when the numbe of epochs s equal to ten, the onosphee float MDBs ae vtually the same as the onosphee fxed countepats fo all dual- and tplefequency baselne models. Fo the geomety-fee cae MDBs addng a thd fequency does make a sgnfcant dffeence fo longe baselnes n case the slp wndow s equal to just a sngle epoch. Fo dual-fequency obsevatons the MDBs ae always geate than one cycle, wheeas fo the tple-fequency case they ae well below the sngle cycle level. The only way to bng the dual-fequency geomety-fee MDBs below ths level s by extendng the slp wndow and nceasng the numbe of epochs. Fo the geomety-based models, the cae MDBs ae much smalle than one cycle fo both dual- and tple-fequency obsevatons as long as the numbe of satelltes s geate than fou. Thus, f the pope obsevaton scenao, whch depends on the numbe of fequences, satelltes and obsevaton epochs and the sze of the slp wndow, s chosen, t s always possble to fnd even the smallest cycle slp. Refeences Baada, W., Statstcal Concepts n Geodesy, Nethelands Geodetc Commsson, Publcatons on Geodesy, New Sees, vol. 2, no. 4, 74 pp., Baada, W., A testng pocedue fo use n geodetc netwoks, Nethelands Geodetc Commsson, Publcatons on Geodesy, New Sees, vol. 2, no. 5, 97 pp., Eule, H. J. and C. Goad, On optmal flteng of GPS dual-fequency obsevatons wthout usng obt nfomaton, Bulletn Géodésque, 65, pp , de Jong, C. D., Real-tme ntegty montong of dual-fequency GPS obsevatons fo a sngle eceve, Acta Geodaetca et Geophysca Hungaca, 31, pp , 1996.

6 862 K. DE JONG AND P. J. G. TEUNISSEN: MDBS OF GPS OBSERVATIONS de Jong, C. D., Pncples and Applcatons of Pemanent GPS Aays, 105 pp., Delft Unvesty Pess, Delft, de Jong, C. D., A unfed appoach to eal-tme ntegty montong of sngleand dual fequency GPS and Glonass obsevatons, Acta Geodaetca et Geophysca Hungaca, 33, pp , de Jong, C. D., Relablty of GPS obsevatons usng a weghted onosphee, 1999 (n pepaaton). Jonkman, N. F., Intege GPS Ambguty Resoluton wthout the Recevesatellte Geomety, LGR-sees, no. 18, 95 pp., Delft Geodetc Computng Cente, Delft, Schaffn, B. and Y. Bock, A unfed scheme fo pocessng GPS dual-band phase obsevatons, Bulletne Géodésque, 62, pp , Teunssen, P. J. G., Qualty contol n geodetc netwoks, n Optmzaton and Desgn of Geodetc Netwoks, edted by E. W. Gafaend and F. Sanso, pp , Spnge, Beln Hedelbeg New Yok, Teunssen, P. J. G., An analytcal study of ambguty decoelaton usng dual-fequency code and cae phase, J. Geod., 70, pp , Teunssen, P. J. G., Mnmal Detectable Bases of GPS data, J. Geod., 72, pp , K. de Jong (e-mal: k.dejong@geo.tudelft.nl), P. J. G. Teunssen

Multistage Median Ranked Set Sampling for Estimating the Population Median

Multistage Median Ranked Set Sampling for Estimating the Population Median Jounal of Mathematcs and Statstcs 3 (: 58-64 007 ISSN 549-3644 007 Scence Publcatons Multstage Medan Ranked Set Samplng fo Estmatng the Populaton Medan Abdul Azz Jeman Ame Al-Oma and Kamaulzaman Ibahm

More information

Thermodynamics of solids 4. Statistical thermodynamics and the 3 rd law. Kwangheon Park Kyung Hee University Department of Nuclear Engineering

Thermodynamics of solids 4. Statistical thermodynamics and the 3 rd law. Kwangheon Park Kyung Hee University Department of Nuclear Engineering Themodynamcs of solds 4. Statstcal themodynamcs and the 3 d law Kwangheon Pak Kyung Hee Unvesty Depatment of Nuclea Engneeng 4.1. Intoducton to statstcal themodynamcs Classcal themodynamcs Statstcal themodynamcs

More information

Physics 2A Chapter 11 - Universal Gravitation Fall 2017

Physics 2A Chapter 11 - Universal Gravitation Fall 2017 Physcs A Chapte - Unvesal Gavtaton Fall 07 hese notes ae ve pages. A quck summay: he text boxes n the notes contan the esults that wll compse the toolbox o Chapte. hee ae thee sectons: the law o gavtaton,

More information

Correspondence Analysis & Related Methods

Correspondence Analysis & Related Methods Coespondence Analyss & Related Methods Ineta contbutons n weghted PCA PCA s a method of data vsualzaton whch epesents the tue postons of ponts n a map whch comes closest to all the ponts, closest n sense

More information

Set of square-integrable function 2 L : function space F

Set of square-integrable function 2 L : function space F Set of squae-ntegable functon L : functon space F Motvaton: In ou pevous dscussons we have seen that fo fee patcles wave equatons (Helmholt o Schödnge) can be expessed n tems of egenvalue equatons. H E,

More information

P 365. r r r )...(1 365

P 365. r r r )...(1 365 SCIENCE WORLD JOURNAL VOL (NO4) 008 www.scecncewoldounal.og ISSN 597-64 SHORT COMMUNICATION ANALYSING THE APPROXIMATION MODEL TO BIRTHDAY PROBLEM *CHOJI, D.N. & DEME, A.C. Depatment of Mathematcs Unvesty

More information

Rigid Bodies: Equivalent Systems of Forces

Rigid Bodies: Equivalent Systems of Forces Engneeng Statcs, ENGR 2301 Chapte 3 Rgd Bodes: Equvalent Sstems of oces Intoducton Teatment of a bod as a sngle patcle s not alwas possble. In geneal, the se of the bod and the specfc ponts of applcaton

More information

Scalars and Vectors Scalar

Scalars and Vectors Scalar Scalas and ectos Scala A phscal quantt that s completel chaacteed b a eal numbe (o b ts numecal value) s called a scala. In othe wods a scala possesses onl a magntude. Mass denst volume tempeatue tme eneg

More information

A. Thicknesses and Densities

A. Thicknesses and Densities 10 Lab0 The Eath s Shells A. Thcknesses and Denstes Any theoy of the nteo of the Eath must be consstent wth the fact that ts aggegate densty s 5.5 g/cm (ecall we calculated ths densty last tme). In othe

More information

Tian Zheng Department of Statistics Columbia University

Tian Zheng Department of Statistics Columbia University Haplotype Tansmsson Assocaton (HTA) An "Impotance" Measue fo Selectng Genetc Makes Tan Zheng Depatment of Statstcs Columba Unvesty Ths s a jont wok wth Pofesso Shaw-Hwa Lo n the Depatment of Statstcs at

More information

The Greatest Deviation Correlation Coefficient and its Geometrical Interpretation

The Greatest Deviation Correlation Coefficient and its Geometrical Interpretation By Rudy A. Gdeon The Unvesty of Montana The Geatest Devaton Coelaton Coeffcent and ts Geometcal Intepetaton The Geatest Devaton Coelaton Coeffcent (GDCC) was ntoduced by Gdeon and Hollste (987). The GDCC

More information

Distinct 8-QAM+ Perfect Arrays Fanxin Zeng 1, a, Zhenyu Zhang 2,1, b, Linjie Qian 1, c

Distinct 8-QAM+ Perfect Arrays Fanxin Zeng 1, a, Zhenyu Zhang 2,1, b, Linjie Qian 1, c nd Intenatonal Confeence on Electcal Compute Engneeng and Electoncs (ICECEE 15) Dstnct 8-QAM+ Pefect Aays Fanxn Zeng 1 a Zhenyu Zhang 1 b Lnje Qan 1 c 1 Chongqng Key Laboatoy of Emegency Communcaton Chongqng

More information

19 The Born-Oppenheimer Approximation

19 The Born-Oppenheimer Approximation 9 The Bon-Oppenheme Appoxmaton The full nonelatvstc Hamltonan fo a molecule s gven by (n a.u.) Ĥ = A M A A A, Z A + A + >j j (883) Lets ewte the Hamltonan to emphasze the goal as Ĥ = + A A A, >j j M A

More information

Khintchine-Type Inequalities and Their Applications in Optimization

Khintchine-Type Inequalities and Their Applications in Optimization Khntchne-Type Inequaltes and The Applcatons n Optmzaton Anthony Man-Cho So Depatment of Systems Engneeng & Engneeng Management The Chnese Unvesty of Hong Kong ISDS-Kolloquum Unvestaet Wen 29 June 2009

More information

A Brief Guide to Recognizing and Coping With Failures of the Classical Regression Assumptions

A Brief Guide to Recognizing and Coping With Failures of the Classical Regression Assumptions A Bef Gude to Recognzng and Copng Wth Falues of the Classcal Regesson Assumptons Model: Y 1 k X 1 X fxed n epeated samples IID 0, I. Specfcaton Poblems A. Unnecessay explanatoy vaables 1. OLS s no longe

More information

Engineering Mechanics. Force resultants, Torques, Scalar Products, Equivalent Force systems

Engineering Mechanics. Force resultants, Torques, Scalar Products, Equivalent Force systems Engneeng echancs oce esultants, Toques, Scala oducts, Equvalent oce sstems Tata cgaw-hll Companes, 008 Resultant of Two oces foce: acton of one bod on anothe; chaacteed b ts pont of applcaton, magntude,

More information

3. A Review of Some Existing AW (BT, CT) Algorithms

3. A Review of Some Existing AW (BT, CT) Algorithms 3. A Revew of Some Exstng AW (BT, CT) Algothms In ths secton, some typcal ant-wndp algothms wll be descbed. As the soltons fo bmpless and condtoned tansfe ae smla to those fo ant-wndp, the pesented algothms

More information

Chapter 23: Electric Potential

Chapter 23: Electric Potential Chapte 23: Electc Potental Electc Potental Enegy It tuns out (won t show ths) that the tostatc foce, qq 1 2 F ˆ = k, s consevatve. 2 Recall, fo any consevatve foce, t s always possble to wte the wok done

More information

Physics 11b Lecture #2. Electric Field Electric Flux Gauss s Law

Physics 11b Lecture #2. Electric Field Electric Flux Gauss s Law Physcs 11b Lectue # Electc Feld Electc Flux Gauss s Law What We Dd Last Tme Electc chage = How object esponds to electc foce Comes n postve and negatve flavos Conseved Electc foce Coulomb s Law F Same

More information

UNIT10 PLANE OF REGRESSION

UNIT10 PLANE OF REGRESSION UIT0 PLAE OF REGRESSIO Plane of Regesson Stuctue 0. Intoducton Ojectves 0. Yule s otaton 0. Plane of Regesson fo thee Vaales 0.4 Popetes of Resduals 0.5 Vaance of the Resduals 0.6 Summay 0.7 Solutons /

More information

Chapter 13 - Universal Gravitation

Chapter 13 - Universal Gravitation Chapte 3 - Unesal Gataton In Chapte 5 we studed Newton s thee laws of moton. In addton to these laws, Newton fomulated the law of unesal gataton. Ths law states that two masses ae attacted by a foce gen

More information

N = N t ; t 0. N is the number of claims paid by the

N = N t ; t 0. N is the number of claims paid by the Iulan MICEA, Ph Mhaela COVIG, Ph Canddate epatment of Mathematcs The Buchaest Academy of Economc Studes an CECHIN-CISTA Uncedt Tac Bank, Lugoj SOME APPOXIMATIONS USE IN THE ISK POCESS OF INSUANCE COMPANY

More information

Generating Functions, Weighted and Non-Weighted Sums for Powers of Second-Order Recurrence Sequences

Generating Functions, Weighted and Non-Weighted Sums for Powers of Second-Order Recurrence Sequences Geneatng Functons, Weghted and Non-Weghted Sums fo Powes of Second-Ode Recuence Sequences Pantelmon Stăncă Aubun Unvesty Montgomey, Depatment of Mathematcs Montgomey, AL 3614-403, USA e-mal: stanca@studel.aum.edu

More information

LASER ABLATION ICP-MS: DATA REDUCTION

LASER ABLATION ICP-MS: DATA REDUCTION Lee, C-T A Lase Ablaton Data educton 2006 LASE ABLATON CP-MS: DATA EDUCTON Cn-Ty A. Lee 24 Septembe 2006 Analyss and calculaton of concentatons Lase ablaton analyses ae done n tme-esolved mode. A ~30 s

More information

Amplifier Constant Gain and Noise

Amplifier Constant Gain and Noise Amplfe Constant Gan and ose by Manfed Thumm and Wene Wesbeck Foschungszentum Kalsuhe n de Helmholtz - Gemenschaft Unvestät Kalsuhe (TH) Reseach Unvesty founded 85 Ccles of Constant Gan (I) If s taken to

More information

Energy in Closed Systems

Energy in Closed Systems Enegy n Closed Systems Anamta Palt palt.anamta@gmal.com Abstact The wtng ndcates a beakdown of the classcal laws. We consde consevaton of enegy wth a many body system n elaton to the nvese squae law and

More information

Recursive Least-Squares Estimation in Case of Interval Observation Data

Recursive Least-Squares Estimation in Case of Interval Observation Data Recusve Least-Squaes Estmaton n Case of Inteval Obsevaton Data H. Kuttee ), and I. Neumann 2) ) Geodetc Insttute, Lebnz Unvesty Hannove, D-3067 Hannove, Gemany, kuttee@gh.un-hannove.de 2) Insttute of Geodesy

More information

Part V: Velocity and Acceleration Analysis of Mechanisms

Part V: Velocity and Acceleration Analysis of Mechanisms Pat V: Velocty an Acceleaton Analyss of Mechansms Ths secton wll evew the most common an cuently pactce methos fo completng the knematcs analyss of mechansms; escbng moton though velocty an acceleaton.

More information

COMPLEMENTARY ENERGY METHOD FOR CURVED COMPOSITE BEAMS

COMPLEMENTARY ENERGY METHOD FOR CURVED COMPOSITE BEAMS ultscence - XXX. mcocd Intenatonal ultdscplnay Scentfc Confeence Unvesty of skolc Hungay - pl 06 ISBN 978-963-358-3- COPLEENTRY ENERGY ETHOD FOR CURVED COPOSITE BES Ákos József Lengyel István Ecsed ssstant

More information

4 Recursive Linear Predictor

4 Recursive Linear Predictor 4 Recusve Lnea Pedcto The man objectve of ths chapte s to desgn a lnea pedcto wthout havng a po knowledge about the coelaton popetes of the nput sgnal. In the conventonal lnea pedcto the known coelaton

More information

24-2: Electric Potential Energy. 24-1: What is physics

24-2: Electric Potential Energy. 24-1: What is physics D. Iyad SAADEDDIN Chapte 4: Electc Potental Electc potental Enegy and Electc potental Calculatng the E-potental fom E-feld fo dffeent chage dstbutons Calculatng the E-feld fom E-potental Potental of a

More information

If there are k binding constraints at x then re-label these constraints so that they are the first k constraints.

If there are k binding constraints at x then re-label these constraints so that they are the first k constraints. Mathematcal Foundatons -1- Constaned Optmzaton Constaned Optmzaton Ma{ f ( ) X} whee X {, h ( ), 1,, m} Necessay condtons fo to be a soluton to ths mamzaton poblem Mathematcally, f ag Ma{ f ( ) X}, then

More information

LINEAR MOMENTUM. product of the mass m and the velocity v r of an object r r

LINEAR MOMENTUM. product of the mass m and the velocity v r of an object r r LINEAR MOMENTUM Imagne beng on a skateboad, at est that can move wthout cton on a smooth suace You catch a heavy, slow-movng ball that has been thown to you you begn to move Altenatvely you catch a lght,

More information

Learning the structure of Bayesian belief networks

Learning the structure of Bayesian belief networks Lectue 17 Leanng the stuctue of Bayesan belef netwoks Mlos Hauskecht mlos@cs.ptt.edu 5329 Sennott Squae Leanng of BBN Leanng. Leanng of paametes of condtonal pobabltes Leanng of the netwok stuctue Vaables:

More information

Event Shape Update. T. Doyle S. Hanlon I. Skillicorn. A. Everett A. Savin. Event Shapes, A. Everett, U. Wisconsin ZEUS Meeting, October 15,

Event Shape Update. T. Doyle S. Hanlon I. Skillicorn. A. Everett A. Savin. Event Shapes, A. Everett, U. Wisconsin ZEUS Meeting, October 15, Event Shape Update A. Eveett A. Savn T. Doyle S. Hanlon I. Skllcon Event Shapes, A. Eveett, U. Wsconsn ZEUS Meetng, Octobe 15, 2003-1 Outlne Pogess of Event Shapes n DIS Smla to publshed pape: Powe Coecton

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 151 Lectue 18 Hamltonan Equatons of Moton (Chapte 8) What s Ahead We ae statng Hamltonan fomalsm Hamltonan equaton Today and 11/6 Canoncal tansfomaton 1/3, 1/5, 1/10 Close lnk to non-elatvstc

More information

Contact, information, consultations

Contact, information, consultations ontact, nfomaton, consultatons hemsty A Bldg; oom 07 phone: 058-347-769 cellula: 664 66 97 E-mal: wojtek_c@pg.gda.pl Offce hous: Fday, 9-0 a.m. A quote of the week (o camel of the week): hee s no expedence

More information

APPLICATIONS OF SEMIGENERALIZED -CLOSED SETS

APPLICATIONS OF SEMIGENERALIZED -CLOSED SETS Intenatonal Jounal of Mathematcal Engneeng Scence ISSN : 22776982 Volume Issue 4 (Apl 202) http://www.mes.com/ https://stes.google.com/ste/mesounal/ APPLICATIONS OF SEMIGENERALIZED CLOSED SETS G.SHANMUGAM,

More information

Chapter Fifiteen. Surfaces Revisited

Chapter Fifiteen. Surfaces Revisited Chapte Ffteen ufaces Revsted 15.1 Vecto Descpton of ufaces We look now at the vey specal case of functons : D R 3, whee D R s a nce subset of the plane. We suppose s a nce functon. As the pont ( s, t)

More information

Integral Vector Operations and Related Theorems Applications in Mechanics and E&M

Integral Vector Operations and Related Theorems Applications in Mechanics and E&M Dola Bagayoko (0) Integal Vecto Opeatons and elated Theoems Applcatons n Mechancs and E&M Ι Basc Defnton Please efe to you calculus evewed below. Ι, ΙΙ, andιιι notes and textbooks fo detals on the concepts

More information

CS649 Sensor Networks IP Track Lecture 3: Target/Source Localization in Sensor Networks

CS649 Sensor Networks IP Track Lecture 3: Target/Source Localization in Sensor Networks C649 enso etwoks IP Tack Lectue 3: Taget/ouce Localaton n enso etwoks I-Jeng Wang http://hng.cs.jhu.edu/wsn06/ png 006 C 649 Taget/ouce Localaton n Weless enso etwoks Basc Poblem tatement: Collaboatve

More information

8 Baire Category Theorem and Uniform Boundedness

8 Baire Category Theorem and Uniform Boundedness 8 Bae Categoy Theoem and Unfom Boundedness Pncple 8.1 Bae s Categoy Theoem Valdty of many esults n analyss depends on the completeness popety. Ths popety addesses the nadequacy of the system of atonal

More information

Pattern Analyses (EOF Analysis) Introduction Definition of EOFs Estimation of EOFs Inference Rotated EOFs

Pattern Analyses (EOF Analysis) Introduction Definition of EOFs Estimation of EOFs Inference Rotated EOFs Patten Analyses (EOF Analyss) Intoducton Defnton of EOFs Estmaton of EOFs Infeence Rotated EOFs . Patten Analyses Intoducton: What s t about? Patten analyses ae technques used to dentfy pattens of the

More information

4 SingularValue Decomposition (SVD)

4 SingularValue Decomposition (SVD) /6/00 Z:\ jeh\self\boo Kannan\Jan-5-00\4 SVD 4 SngulaValue Decomposton (SVD) Chapte 4 Pat SVD he sngula value decomposton of a matx s the factozaton of nto the poduct of thee matces = UDV whee the columns

More information

A. P. Sakis Meliopoulos Power System Modeling, Analysis and Control. Chapter 7 3 Operating State Estimation 3

A. P. Sakis Meliopoulos Power System Modeling, Analysis and Control. Chapter 7 3 Operating State Estimation 3 DRAF and INCOMPLEE able of Contents fom A. P. Saks Melopoulos Powe System Modelng, Analyss and Contol Chapte 7 3 Opeatng State Estmaton 3 7. Intoducton 3 7. SCADA System 4 7.3 System Netwok Confguato 7

More information

PHYS 705: Classical Mechanics. Derivation of Lagrange Equations from D Alembert s Principle

PHYS 705: Classical Mechanics. Derivation of Lagrange Equations from D Alembert s Principle 1 PHYS 705: Classcal Mechancs Devaton of Lagange Equatons fom D Alembet s Pncple 2 D Alembet s Pncple Followng a smla agument fo the vtual dsplacement to be consstent wth constants,.e, (no vtual wok fo

More information

Experimental study on parameter choices in norm-r support vector regression machines with noisy input

Experimental study on parameter choices in norm-r support vector regression machines with noisy input Soft Comput 006) 0: 9 3 DOI 0.007/s00500-005-0474-z ORIGINAL PAPER S. Wang J. Zhu F. L. Chung Hu Dewen Expemental study on paamete choces n nom- suppot vecto egesson machnes wth nosy nput Publshed onlne:

More information

Theo K. Dijkstra. Faculty of Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE Groningen THE NETHERLANDS

Theo K. Dijkstra. Faculty of Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE Groningen THE NETHERLANDS RESEARCH ESSAY COSISE PARIAL LEAS SQUARES PAH MODELIG heo K. Djksta Faculty of Economcs and Busness, Unvesty of Gonngen, ettelbosje, 9747 AE Gonngen HE EHERLADS {t.k.djksta@ug.nl} Jög Hensele Faculty of

More information

A Study about One-Dimensional Steady State. Heat Transfer in Cylindrical and. Spherical Coordinates

A Study about One-Dimensional Steady State. Heat Transfer in Cylindrical and. Spherical Coordinates Appled Mathematcal Scences, Vol. 7, 03, no. 5, 67-633 HIKARI Ltd, www.m-hka.com http://dx.do.og/0.988/ams.03.38448 A Study about One-Dmensonal Steady State Heat ansfe n ylndcal and Sphecal oodnates Lesson

More information

Efficiency of the principal component Liu-type estimator in logistic

Efficiency of the principal component Liu-type estimator in logistic Effcency of the pncpal component Lu-type estmato n logstc egesson model Jbo Wu and Yasn Asa 2 School of Mathematcs and Fnance, Chongqng Unvesty of Ats and Scences, Chongqng, Chna 2 Depatment of Mathematcs-Compute

More information

Optimal System for Warm Standby Components in the Presence of Standby Switching Failures, Two Types of Failures and General Repair Time

Optimal System for Warm Standby Components in the Presence of Standby Switching Failures, Two Types of Failures and General Repair Time Intenatonal Jounal of ompute Applcatons (5 ) Volume 44 No, Apl Optmal System fo Wam Standby omponents n the esence of Standby Swtchng Falues, Two Types of Falues and Geneal Repa Tme Mohamed Salah EL-Shebeny

More information

Remember: When an object falls due to gravity its potential energy decreases.

Remember: When an object falls due to gravity its potential energy decreases. Chapte 5: lectc Potental As mentoned seveal tmes dung the uate Newton s law o gavty and Coulomb s law ae dentcal n the mathematcal om. So, most thngs that ae tue o gavty ae also tue o electostatcs! Hee

More information

An Approach to Inverse Fuzzy Arithmetic

An Approach to Inverse Fuzzy Arithmetic An Appoach to Invese Fuzzy Athmetc Mchael Hanss Insttute A of Mechancs, Unvesty of Stuttgat Stuttgat, Gemany mhanss@mechaun-stuttgatde Abstact A novel appoach of nvese fuzzy athmetc s ntoduced to successfully

More information

On a New Definition of a Stochastic-based Accuracy Concept of Data Reconciliation-Based Estimators

On a New Definition of a Stochastic-based Accuracy Concept of Data Reconciliation-Based Estimators On a New Defnton of a Stochastc-based Accuacy Concept of Data Reconclaton-Based Estmatos M. Bagajewcz Unesty of Olahoma 100 E. Boyd St., Noman OK 73019, USA Abstact Tadtonally, accuacy of an nstument s

More information

Multipole Radiation. March 17, 2014

Multipole Radiation. March 17, 2014 Multpole Radaton Mach 7, 04 Zones We wll see that the poblem of hamonc adaton dvdes nto thee appoxmate egons, dependng on the elatve magntudes of the dstance of the obsevaton pont,, and the wavelength,

More information

State Estimation. Ali Abur Northeastern University, USA. Nov. 01, 2017 Fall 2017 CURENT Course Lecture Notes

State Estimation. Ali Abur Northeastern University, USA. Nov. 01, 2017 Fall 2017 CURENT Course Lecture Notes State Estmaton Al Abu Notheasten Unvesty, USA Nov. 0, 07 Fall 07 CURENT Couse Lectue Notes Opeatng States of a Powe System Al Abu NORMAL STATE SECURE o INSECURE RESTORATIVE STATE EMERGENCY STATE PARTIAL

More information

Vibration Input Identification using Dynamic Strain Measurement

Vibration Input Identification using Dynamic Strain Measurement Vbaton Input Identfcaton usng Dynamc Stan Measuement Takum ITOFUJI 1 ;TakuyaYOSHIMURA ; 1, Tokyo Metopoltan Unvesty, Japan ABSTRACT Tansfe Path Analyss (TPA) has been conducted n ode to mpove the nose

More information

Detection and Estimation Theory

Detection and Estimation Theory ESE 54 Detecton and Etmaton Theoy Joeph A. O Sullvan Samuel C. Sach Pofeo Electonc Sytem and Sgnal Reeach Laboatoy Electcal and Sytem Engneeng Wahngton Unvety 411 Jolley Hall 314-935-4173 (Lnda anwe) jao@wutl.edu

More information

A Method of Reliability Target Setting for Electric Power Distribution Systems Using Data Envelopment Analysis

A Method of Reliability Target Setting for Electric Power Distribution Systems Using Data Envelopment Analysis 27 กก ก 9 2-3 2554 ก ก ก A Method of Relablty aget Settng fo Electc Powe Dstbuton Systems Usng Data Envelopment Analyss ก 2 ก ก ก ก ก 0900 2 ก ก ก ก ก 0900 E-mal: penjan262@hotmal.com Penjan Sng-o Psut

More information

Test 1 phy What mass of a material with density ρ is required to make a hollow spherical shell having inner radius r i and outer radius r o?

Test 1 phy What mass of a material with density ρ is required to make a hollow spherical shell having inner radius r i and outer radius r o? Test 1 phy 0 1. a) What s the pupose of measuement? b) Wte all fou condtons, whch must be satsfed by a scala poduct. (Use dffeent symbols to dstngush opeatons on ectos fom opeatons on numbes.) c) What

More information

V. Principles of Irreversible Thermodynamics. s = S - S 0 (7.3) s = = - g i, k. "Flux": = da i. "Force": = -Â g a ik k = X i. Â J i X i (7.

V. Principles of Irreversible Thermodynamics. s = S - S 0 (7.3) s = = - g i, k. Flux: = da i. Force: = -Â g a ik k = X i. Â J i X i (7. Themodynamcs and Knetcs of Solds 71 V. Pncples of Ievesble Themodynamcs 5. Onsage s Teatment s = S - S 0 = s( a 1, a 2,...) a n = A g - A n (7.6) Equlbum themodynamcs detemnes the paametes of an equlbum

More information

CSJM University Class: B.Sc.-II Sub:Physics Paper-II Title: Electromagnetics Unit-1: Electrostatics Lecture: 1 to 4

CSJM University Class: B.Sc.-II Sub:Physics Paper-II Title: Electromagnetics Unit-1: Electrostatics Lecture: 1 to 4 CSJM Unvesty Class: B.Sc.-II Sub:Physcs Pape-II Ttle: Electomagnetcs Unt-: Electostatcs Lectue: to 4 Electostatcs: It deals the study of behavo of statc o statonay Chages. Electc Chage: It s popety by

More information

SOME NEW SELF-DUAL [96, 48, 16] CODES WITH AN AUTOMORPHISM OF ORDER 15. KEYWORDS: automorphisms, construction, self-dual codes

SOME NEW SELF-DUAL [96, 48, 16] CODES WITH AN AUTOMORPHISM OF ORDER 15. KEYWORDS: automorphisms, construction, self-dual codes Факултет по математика и информатика, том ХVІ С, 014 SOME NEW SELF-DUAL [96, 48, 16] CODES WITH AN AUTOMORPHISM OF ORDER 15 NIKOLAY I. YANKOV ABSTRACT: A new method fo constuctng bnay self-dual codes wth

More information

On Maneuvering Target Tracking with Online Observed Colored Glint Noise Parameter Estimation

On Maneuvering Target Tracking with Online Observed Colored Glint Noise Parameter Estimation Wold Academy of Scence, Engneeng and Technology 6 7 On Maneuveng Taget Tacng wth Onlne Obseved Coloed Glnt Nose Paamete Estmaton M. A. Masnad-Sha, and S. A. Banan Abstact In ths pape a compehensve algothm

More information

Department of Geomatics Engineering. Development of A Precision Pointing System Using an Integrated Multi-Sensor Approach. Robert Shaw Harvey

Department of Geomatics Engineering. Development of A Precision Pointing System Using an Integrated Multi-Sensor Approach. Robert Shaw Harvey Geomatcs Engneeng UCGE Repots Numbe 20117 Depatment of Geomatcs Engneeng Development of A Pecson Pontng System Usng an Integated Mult-Senso Appoach By Robet Shaw Havey Apl, 1998 Calgay, Albeta, Canada

More information

The Unique Solution of Stochastic Differential Equations With. Independent Coefficients. Dietrich Ryter.

The Unique Solution of Stochastic Differential Equations With. Independent Coefficients. Dietrich Ryter. The Unque Soluton of Stochastc Dffeental Equatons Wth Independent Coeffcents Detch Ryte RyteDM@gawnet.ch Mdatweg 3 CH-4500 Solothun Swtzeland Phone +4132 621 13 07 SDE s must be solved n the ant-itô sense

More information

Approximate Abundance Histograms and Their Use for Genome Size Estimation

Approximate Abundance Histograms and Their Use for Genome Size Estimation J. Hlaváčová (Ed.): ITAT 2017 Poceedngs, pp. 27 34 CEUR Wokshop Poceedngs Vol. 1885, ISSN 1613-0073, c 2017 M. Lpovský, T. Vnař, B. Bejová Appoxmate Abundance Hstogams and The Use fo Genome Sze Estmaton

More information

Backward Haplotype Transmission Association (BHTA) Algorithm. Tian Zheng Department of Statistics Columbia University. February 5 th, 2002

Backward Haplotype Transmission Association (BHTA) Algorithm. Tian Zheng Department of Statistics Columbia University. February 5 th, 2002 Backwad Haplotype Tansmsson Assocaton (BHTA) Algothm A Fast ult-pont Sceenng ethod fo Complex Tats Tan Zheng Depatment of Statstcs Columba Unvesty Febuay 5 th, 2002 Ths s a jont wok wth Pofesso Shaw-Hwa

More information

Groupoid and Topological Quotient Group

Groupoid and Topological Quotient Group lobal Jounal of Pue and Appled Mathematcs SSN 0973-768 Volume 3 Numbe 7 07 pp 373-39 Reseach nda Publcatons http://wwwpublcatoncom oupod and Topolocal Quotent oup Mohammad Qasm Manna Depatment of Mathematcs

More information

General Variance Covariance Structures in Two-Way Random Effects Models

General Variance Covariance Structures in Two-Way Random Effects Models Appled Mathematcs 3 4 64-63 http://dxdoog/436/am34486 Publshed Onlne Apl 3 (http://wwwscpog/jounal/am) Geneal aance Covaance Stuctues n wo-way Rom Effects Models Calos e Poes Jaya Kshnakuma epatment of

More information

GENERALIZED MULTIVARIATE EXPONENTIAL TYPE (GMET) ESTIMATOR USING MULTI-AUXILIARY INFORMATION UNDER TWO-PHASE SAMPLING

GENERALIZED MULTIVARIATE EXPONENTIAL TYPE (GMET) ESTIMATOR USING MULTI-AUXILIARY INFORMATION UNDER TWO-PHASE SAMPLING Pak. J. Statst. 08 Vol. (), 9-6 GENERALIZED MULTIVARIATE EXPONENTIAL TYPE (GMET) ESTIMATOR USING MULTI-AUXILIARY INFORMATION UNDER TWO-PHASE SAMPLING Ayesha Ayaz, Zahoo Ahmad, Aam Sanaullah and Muhammad

More information

Stellar Astrophysics. dt dr. GM r. The current model for treating convection in stellar interiors is called mixing length theory:

Stellar Astrophysics. dt dr. GM r. The current model for treating convection in stellar interiors is called mixing length theory: Stella Astophyscs Ovevew of last lectue: We connected the mean molecula weght to the mass factons X, Y and Z: 1 1 1 = X + Y + μ 1 4 n 1 (1 + 1) = X μ 1 1 A n Z (1 + ) + Y + 4 1+ z A Z We ntoduced the pessue

More information

Large scale magnetic field generation by accelerated particles in galactic medium

Large scale magnetic field generation by accelerated particles in galactic medium Lage scale magnetc feld geneaton by acceleated patcles n galactc medum I.N.Toptygn Sant Petesbug State Polytechncal Unvesty, depatment of Theoetcal Physcs, Sant Petesbug, Russa 2.Reason explonatons The

More information

Bayesian Assessment of Availabilities and Unavailabilities of Multistate Monotone Systems

Bayesian Assessment of Availabilities and Unavailabilities of Multistate Monotone Systems Dept. of Math. Unvesty of Oslo Statstcal Reseach Repot No 3 ISSN 0806 3842 June 2010 Bayesan Assessment of Avalabltes and Unavalabltes of Multstate Monotone Systems Bent Natvg Jøund Gåsemy Tond Retan June

More information

Optimization Methods: Linear Programming- Revised Simplex Method. Module 3 Lecture Notes 5. Revised Simplex Method, Duality and Sensitivity analysis

Optimization Methods: Linear Programming- Revised Simplex Method. Module 3 Lecture Notes 5. Revised Simplex Method, Duality and Sensitivity analysis Optmzaton Meods: Lnea Pogammng- Revsed Smple Meod Module Lectue Notes Revsed Smple Meod, Dualty and Senstvty analyss Intoducton In e pevous class, e smple meod was dscussed whee e smple tableau at each

More information

Machine Learning. Spectral Clustering. Lecture 23, April 14, Reading: Eric Xing 1

Machine Learning. Spectral Clustering. Lecture 23, April 14, Reading: Eric Xing 1 Machne Leanng -7/5 7/5-78, 78, Spng 8 Spectal Clusteng Ec Xng Lectue 3, pl 4, 8 Readng: Ec Xng Data Clusteng wo dffeent ctea Compactness, e.g., k-means, mxtue models Connectvty, e.g., spectal clusteng

More information

Dirichlet Mixture Priors: Inference and Adjustment

Dirichlet Mixture Priors: Inference and Adjustment Dchlet Mxtue Pos: Infeence and Adustment Xugang Ye (Wokng wth Stephen Altschul and Y Kuo Yu) Natonal Cante fo Botechnology Infomaton Motvaton Real-wold obects Independent obsevatons Categocal data () (2)

More information

4.4 Continuum Thermomechanics

4.4 Continuum Thermomechanics 4.4 Contnuum Themomechancs The classcal themodynamcs s now extended to the themomechancs of a contnuum. The state aables ae allowed to ay thoughout a mateal and pocesses ae allowed to be eesble and moe

More information

The Backpropagation Algorithm

The Backpropagation Algorithm The Backpopagaton Algothm Achtectue of Feedfowad Netwok Sgmodal Thehold Functon Contuctng an Obectve Functon Tanng a one-laye netwok by teepet decent Tanng a two-laye netwok by teepet decent Copyght Robet

More information

A NOVEL DWELLING TIME DESIGN METHOD FOR LOW PROBABILITY OF INTERCEPT IN A COMPLEX RADAR NETWORK

A NOVEL DWELLING TIME DESIGN METHOD FOR LOW PROBABILITY OF INTERCEPT IN A COMPLEX RADAR NETWORK Z. Zhang et al., Int. J. of Desgn & Natue and Ecodynamcs. Vol. 0, No. 4 (205) 30 39 A NOVEL DWELLING TIME DESIGN METHOD FOR LOW PROBABILITY OF INTERCEPT IN A COMPLEX RADAR NETWORK Z. ZHANG,2,3, J. ZHU

More information

Physics 1501 Lecture 19

Physics 1501 Lecture 19 Physcs 1501 ectue 19 Physcs 1501: ectue 19 Today s Agenda Announceents HW#7: due Oct. 1 Mdte 1: aveage 45 % Topcs otatonal Kneatcs otatonal Enegy Moents of Ineta Physcs 1501: ectue 19, Pg 1 Suay (wth copason

More information

an application to HRQoL

an application to HRQoL AlmaMate Studoum Unvesty of Bologna A flexle IRT Model fo health questonnae: an applcaton to HRQoL Seena Boccol Gula Cavn Depatment of Statstcal Scence, Unvesty of Bologna 9 th Intenatonal Confeence on

More information

Density Functional Theory I

Density Functional Theory I Densty Functonal Theoy I cholas M. Hason Depatment of Chemsty Impeal College Lonon & Computatonal Mateals Scence Daesbuy Laboatoy ncholas.hason@c.ac.uk Densty Functonal Theoy I The Many Electon Schönge

More information

GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS

GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS #A39 INTEGERS 9 (009), 497-513 GENERALIZATION OF AN IDENTITY INVOLVING THE GENERALIZED FIBONACCI NUMBERS AND ITS APPLICATIONS Mohaad Faokh D. G. Depatent of Matheatcs, Fedows Unvesty of Mashhad, Mashhad,

More information

1. A body will remain in a state of rest, or of uniform motion in a straight line unless it

1. A body will remain in a state of rest, or of uniform motion in a straight line unless it Pncples of Dnamcs: Newton's Laws of moton. : Foce Analss 1. A bod wll eman n a state of est, o of unfom moton n a staght lne unless t s acted b etenal foces to change ts state.. The ate of change of momentum

More information

Chapter 3 Optical Systems with Annular Pupils

Chapter 3 Optical Systems with Annular Pupils Chapte 3 Optical Systems with Annula Pupils 3 INTRODUCTION In this chapte, we discuss the imaging popeties of a system with an annula pupil in a manne simila to those fo a system with a cicula pupil The

More information

3.1 Electrostatic Potential Energy and Potential Difference

3.1 Electrostatic Potential Energy and Potential Difference 3. lectostatc Potental negy and Potental Dffeence RMMR fom mechancs: - The potental enegy can be defned fo a system only f consevatve foces act between ts consttuents. - Consevatve foces may depend only

More information

Impact of Polarimetric Dimensionality of Forest Parameter Estimation by Means of Polarimetric SAR interferometry

Impact of Polarimetric Dimensionality of Forest Parameter Estimation by Means of Polarimetric SAR interferometry Impact of Polametc Dmensonalty of Foest Paamete Estmaton by Means of Polametc SAR ntefeomety Jun Su Km, Seung-Kuk Lee, Konstantnos Papathanassou, and Iena Hajnsek Geman Aeospace Cente Mcowaves and Rada

More information

Pearson s Chi-Square Test Modifications for Comparison of Unweighted and Weighted Histograms and Two Weighted Histograms

Pearson s Chi-Square Test Modifications for Comparison of Unweighted and Weighted Histograms and Two Weighted Histograms Peason s Chi-Squae Test Modifications fo Compaison of Unweighted and Weighted Histogams and Two Weighted Histogams Univesity of Akueyi, Bogi, v/noduslód, IS-6 Akueyi, Iceland E-mail: nikolai@unak.is Two

More information

Exact Simplification of Support Vector Solutions

Exact Simplification of Support Vector Solutions Jounal of Machne Leanng Reseach 2 (200) 293-297 Submtted 3/0; Publshed 2/0 Exact Smplfcaton of Suppot Vecto Solutons Tom Downs TD@ITEE.UQ.EDU.AU School of Infomaton Technology and Electcal Engneeng Unvesty

More information

MULTIPOLE FIELDS. Multipoles, 2 l poles. Monopoles, dipoles, quadrupoles, octupoles... Electric Dipole R 1 R 2. P(r,θ,φ) e r

MULTIPOLE FIELDS. Multipoles, 2 l poles. Monopoles, dipoles, quadrupoles, octupoles... Electric Dipole R 1 R 2. P(r,θ,φ) e r MULTIPOLE FIELDS Mutpoes poes. Monopoes dpoes quadupoes octupoes... 4 8 6 Eectc Dpoe +q O θ e R R P(θφ) -q e The potenta at the fed pont P(θφ) s ( θϕ )= q R R Bo E. Seneus : Now R = ( e) = + cosθ R = (

More information

Dynamics of Rigid Bodies

Dynamics of Rigid Bodies Dynamcs of Rgd Bodes A gd body s one n whch the dstances between consttuent patcles s constant thoughout the moton of the body,.e. t keeps ts shape. Thee ae two knds of gd body moton: 1. Tanslatonal Rectlnea

More information

The Forming Theory and the NC Machining for The Rotary Burs with the Spectral Edge Distribution

The Forming Theory and the NC Machining for The Rotary Burs with the Spectral Edge Distribution oden Appled Scence The Fomn Theoy and the NC achnn fo The Rotay us wth the Spectal Ede Dstbuton Huan Lu Depatment of echancal Enneen, Zhejan Unvesty of Scence and Technoloy Hanzhou, c.y. chan, 310023,

More information

A Queuing Model for an Automated Workstation Receiving Jobs from an Automated Workstation

A Queuing Model for an Automated Workstation Receiving Jobs from an Automated Workstation Intenatonal Jounal of Opeatons Reseach Intenatonal Jounal of Opeatons Reseach Vol. 7, o. 4, 918 (1 A Queung Model fo an Automated Wokstaton Recevng Jobs fom an Automated Wokstaton Davd S. Km School of

More information

Physical & Interfacial Electrochemistry 2013

Physical & Interfacial Electrochemistry 2013 Physcal & Intefacal Electochemsty 013 Lectue 3. Ion-on nteactons n electolyte solutons. Module JS CH3304 MoleculaThemodynamcs and Knetcs Ion-Ion Inteactons The themodynamc popetes of electolyte solutons

More information

Chapter I Matrices, Vectors, & Vector Calculus 1-1, 1-9, 1-10, 1-11, 1-17, 1-18, 1-25, 1-27, 1-36, 1-37, 1-41.

Chapter I Matrices, Vectors, & Vector Calculus 1-1, 1-9, 1-10, 1-11, 1-17, 1-18, 1-25, 1-27, 1-36, 1-37, 1-41. Chapte I Matces, Vectos, & Vecto Calculus -, -9, -0, -, -7, -8, -5, -7, -36, -37, -4. . Concept of a Scala Consde the aa of patcles shown n the fgue. he mass of the patcle at (,) can be epessed as. M (,

More information

gravity r2,1 r2 r1 by m 2,1

gravity r2,1 r2 r1 by m 2,1 Gavtaton Many of the foundatons of classcal echancs wee fst dscoveed when phlosophes (ealy scentsts and atheatcans) ted to explan the oton of planets and stas. Newton s ost faous fo unfyng the oton of

More information

Ranks of quotients, remainders and p-adic digits of matrices

Ranks of quotients, remainders and p-adic digits of matrices axv:1401.6667v2 [math.nt] 31 Jan 2014 Ranks of quotents, emandes and p-adc dgts of matces Mustafa Elshekh Andy Novocn Mak Gesbecht Abstact Fo a pme p and a matx A Z n n, wte A as A = p(a quo p)+ (A em

More information

Supersymmetry in Disorder and Chaos (Random matrices, physics of compound nuclei, mathematics of random processes)

Supersymmetry in Disorder and Chaos (Random matrices, physics of compound nuclei, mathematics of random processes) Supesymmety n Dsoe an Chaos Ranom matces physcs of compoun nucle mathematcs of anom pocesses Lteatue: K.B. Efetov Supesymmety n Dsoe an Chaos Cambge Unvesty Pess 997999 Supesymmety an Tace Fomulae I.V.

More information

(8) Gain Stage and Simple Output Stage

(8) Gain Stage and Simple Output Stage EEEB23 Electoncs Analyss & Desgn (8) Gan Stage and Smple Output Stage Leanng Outcome Able to: Analyze an example of a gan stage and output stage of a multstage amplfe. efeence: Neamen, Chapte 11 8.0) ntoducton

More information