Constant False Alarm Rate Detectors in Intensive Noise Environment Conditions

Size: px
Start display at page:

Download "Constant False Alarm Rate Detectors in Intensive Noise Environment Conditions"

Transcription

1 BUGARIA ACADEMY OF SCIECES CYBEREICS AD IFORMAIO ECHOOGIES Voum, o 3 Sofa Contant Fa Aam Rat Dtcto n Intnv o Envonmnt Condton yuba Douova Inttut of Infomaton and Communcaton chnoog, 3 Sofa E-ma: douova@t.ba.bg Abtact: A dffnt tchnqu of CFAR dtcto pocdu fo movng tagt dtcton n no nvonmnt condton wth a Poon dtbutd fow and Ragh amptud dtbuton popod n th pap. h xpon of th dtcton and fa aam pobabty a dvd fo a hghy fuctuatng Swng II tagt. A compaatv anay of th pfomanc of dffnt ada dtcto tuctu png contant fa aam at don. h a a CA CFAR (C Avagng Contant Fa Aam Rat), an EXC CFAR (EXCon Contant Fa Aam Rat), a CFAR BI (Contant Fa Aam Rat wth Bnay Intgaton), an EXC CFAR BI (EXCon Contant Fa Aam Rat wth Bnay Intgaton) and an API CFAR (Adaptv cnong Pot dtcton Intgaton Contant Fa Aam Rat). A mthod fo o tmaton, whch aow choong of optma dtcto paamt, dvopd. h tmat a obtand of th ffctvn of CFAR dtcto n no nvonmnt condton and thy a compad to pattn, nvtgatd by oth autho. h ut achvd can b uccfuy appd fo ada tagt dtcton and n th xtng communcaton ntwo cv, that u pu gna. Kywod: Rada dtcto, CFAR dtcto, no nvonmnt, andomy avng mpu ntfnc, pobabty of dtcton, pobabty of fa aam, dtctabty poft (o).. Intoducton Modn ado-ytm functon n compx ctomagntc nvonmnt, und condton of catd atfca and natua ntfnc wth unnown o vaab paamt. hat uuay mutua ntfnc, fom adacnt ado-ctonc 3

2 dvc, a a u powfu and appang cauay,.., havng no nvonmnt chaacttc wth ag ntnty. h concn pcay gna fom ma ada fo a taffc conto. Randomy Avng Impu Intfnc (RAII), n uch ca, cvd not ony at th bac ada antnna chann, but ao at th dob and th bacob dagam of th antnna, and cvng pob not ony at th bac fquncy chann. Sgna dtcton n noy o cutt nvonmnt a vy mpotant pat of tagt dtcton pocdu. In thoy th no and cutt bacgound w b dcbd by a tattca mod wth.g. Raygh, o xponntay dtbutd andom vaab of nown avag no pow. But n pactca appcaton th avag no o cutt pow abouty unnown and om tattca paamt can addtonay vay ov ang, tm and azmuth. In automatc ada dtcton, th gna cvd ampd n ang and fquncy. Each amp pacd n an aay of ang and Dopp outon c. h cutt bacgound n th c und tt tmatd by avagng th output of th naby outon c (ang and/o Dopp). h tagt dtcton dcad, f th gna vau xcd a pmnay dtmnd thhod. Cunt tmatng of th no v n th fnc wndow fom th thhod. h dtcton thhod obtand by cang th no v tmat wth a contant α to achv a dd pobabty of fa aam P FA. A an tmat of th no v, th tmat popod by F n n and Johnon n [] qut oftn ud. Avagng th output of th fnc c uoundng th tt c fom th tmat. hu a contant fa aam at mantand n th poc of dtcton. h th convntona C Avagng Contant Fa Aam Rat (CA CFAR) dtcto, popod by F n n and Johnon n []. h CA CFAR poco a vy ffctv n ca of tatonay and homognou ntfnc and a ffctv amot a th da yman-paon dtcto, whn th numb of fnc c bcom vy ag. h pnc of tong andomy avng mpu ntfnc n both, th tt outon c and th fnc c, can cau datc dgadaton n th pfomanc of CA CFAR poco. Such typ of ntfnc non-tatonay and non-homognou and oftn caud by adacnt ada o oth ado-ctonc dvc. In a non-homognou nvonmnt, th dtcton pfomanc and th fa aam guaton popt of CA CFAR dtcto may b ouy dgadd. Dung th at fw ya a ot of dffnt appoach hav bn popod to mpov th dtctabty of CFAR dtcto opatng n andom mpu no [-9]. On way fo png contant fa aam at und th condton th ung of th xcon CFAR dtcto pntd n pap [, ], but t not ffctv nough. Mo ffctv fo th tabzaton of fa aam th mpmntaton of Pot-dtcton Intgaton (PI), and Bnay Intgaton (BI) n CFAR gna poco, tudd and anayzd n pap [5, 9]. Mot ffctv th Adaptv Pot-dtcton Intgato CFAR (API CFAR) gna poco wth adaptv cton on mpu no n fnc and n tt wndow and a potdtcton ntgaton pocdu [5, 3]. 3

3 h no n tt c a Raygh nvop dtbutd and tagt tun a fuctuatng accodng to Swng II mod n [-4]. Impu no xt ony n th tt wndow n [5], th avag ptton fquncy of pu ammng n th ca dtmnd by th numb of pu n a wndow. In fnc [7-, ] th autho aum that th amp of th tota ntfnc a dtbutd accodng to th compound xponnta aw, wh th wghtng coffcnt a th pobabt of couptng and non-couptng of th amp. h pobabt fo appang of th mpu no wth avag ngth n th c of ang dpnd on th mutpcaton of th avag ptton fquncy of mpu no and th no ngth. In uch tuaton t woud b dab to now th CFAR o dpndng on th paamt of th mpu no, fo atng th bhavo of th ada. h a two appoach fo cacuaton of CFAR o, offd by Rohng and Kaam n [, 4]. h convntona mthod to comput th addtona SR ndd fo CFAR pocng chm byond that fo th optmum poco, to achv a fxd dtcton pobabty (.g.,.5), ud n [5, 7-, ]. Fo a patcua CFAR chm th o obvouy va wth th dtcton pobabty. Atnatvy, th autho n [, 4] u anoth cton, atd to th on bad on th Avag Dcon hhod (AD), nc th thhod and th dtcton pobabty a coy atd to on anoth. hn th dffnc btwn two CFAR ytm n a homognou cutt tuaton xpd by th ato btwn th two AD maud n db n [, 4]. Such tmaton and o anay a not dcbd n [4, 5, 7]. On th oth hand, n [8, 9, ] th o a tmatd, but fo a dffnt vau fo th pobabty of dtcton.9755 and th ut a compad wth th am CFAR chm n th tuaton wthout mpu no. Sma nvtgaton pntd n [] and th ut, whch a achvd fo CFAR poco, a qua to tho pntd n [] fo th ca wthout mpu no. Ung th AD appoach and th Momnt Gnatng Functon (MGF) fo modng of th mpu no pntd n []. h o of CFAR dtcto a cacuatd fo dffnt vau of fa aam pobabty, fo a dffnt numb of obvaton n th fnc wndow, an avag Intfnc-to-o Rato (IR) and pobabt fo appaanc of mpu no wth avag ngth n th c n ang. h dtcton pfomanc of CFAR poco popod by H o u n [] fo th ca of homognou nvonmnt and ch-qua famy of fuctuatng tagt mod (Swng I, II, III, and IV). In th pap th tudy pntd of th tuaton fo a hghy fuctuatng tagt Swng II typ tagt mod dtcton und ntnv no nvonmnt condton. A compaatv anay of th pfomanc of dffnt typ of CFAR dtcto cad out. h tuctu gv th pobty fo png a contant fa aam at n th pnc of andom avng mpu ntfnc. In th tudy on vy nttng ca condd th mt, whn ncang th pobabty of th appaanc chang th dtbuton aw fom Poon to bnomna. h bnomna mod mo gna than Poon dtbuton mod 33

4 [3]. h chang of th dtbuton aw and th paamt of RAII ad to wond dtcton poc. h ach wo pfomd n MAAB computatona nvonmnt.. Sgna mod Ung th appoach popod n [], nw ut a obtand fo Swng II typ tagt dtcton mod of pfomanc n no nvonmnt (Randomy Avng Impu Intfnc RAII). h gna n th fnc wndow aumd to b wth Poon dtbuton and ha th foowng Pobabty Dnty Functon (PDF) [4]: () f ( x) P ( ) λ xp x xp ( ) ( ) ( ) λ λ λ wh th p pu avag Sgna-to-o Rato (SR), λ th avag pow of th cv no, th avag IR, th pobabty of appaanc of RAII. Und condton of bnoma dtbuton of pu ntfnc, th pobabty of ntfnc-pu-no occunc n th bacgound nvonmnt ( ). h pobabty of appaanc of two ntfnc n a ng c and havng ony no pobabty ( ), wh t F, F th avag ptton fquncy of pu ntfnc and t c th ngth of pu tanmon [4]. h dtbuton bnoma whn th pobabty of pu ntfnc abov. [4]. In th tuaton th output of th fnc wndow a obvaton fom tattcay ndpndnt xponnta andom vaab. Conqunty, th PDF of th fnc wndow output may b dfnd by: c x () λ ( ) f xp B ( x) ( ) x xp λ λ ( ) x xp ( ) ( ) λ λ λ x wh λ th avag pow of th cv no and /λ th p pu avag IR. In th nxt two fgu, accodng to pap [5], compaatv muaton xamp a hown fo Poon and fo bnoma dtbuton of pu ntfnc, wth gna and no paamt vau 7 db, λ, 3 db,.. 34

5 Fg.. Examp of Poon dtbuton of pu ntfnc Fg.. Examp of bnomna dtbuton of pu ntfnc 3. CFAR poco tattca anay In th modn ada ytm, png contant fa aam at, th tagt dtctd accodng to th foowng agothm []: (3) H H : Φ : Φ ( q ) ( q ), q, q > αv, < V α 35

6 wh H th hypoth that th tt outon c contan th cho fom th tagt and H th hypoth that th tt outon c contan th andomy avng mpu ntfnc ony, V th no v tmaton. h contant α a ca coffcnt, whch dtmnd n od to mantan a gvn contant fa aam at. h dffnt CFAR tuctu ma u of dffnt agothm fo no v tmaton V [5-4]. In th pap va typ of gna poco a anayzd a CA (C Avagng), an EXC (EXCon), a BI (Bnay Intgaton), an EXC BI (EXCon wth Bnay Intgaton) and an API (Adaptv cnong Pot dtcton Intgaton). On Fg. 3 on xamp pntd of th adaptv thhod pocdu fo on-dmnona CFAR poco n condton of andomy avng mpu ntfnc [5]. h gna tuctu of an adaptv CFAR poco hown on Fg. 4. Fg. 3. Adaptv thhod pocdu fo on-dmnona CFAR poco Input gna Squa ow Dtcto CFAR agothm hhod pocdu C o m p a a t o Output of th CFAR Fg. 4. Gna tuctu of an adaptv CFAR poco 36

7 37 t u aum that pu ht th tagt, whch modd accodng to Swng II ca. h gna cvd ampd n ang by ung outon c utng n a matx wth ow and coumn. Each coumn of th data matx cont of th vau of th gna obtand fo pu ntva n on ang outon c. t u ao aum that th ft / and th at / ow of th data matx a ud a a fnc wndow n od to tmat th no-puntfnc v n th ada tt outon c. In th ca th amp of th fnc c ut n a matx X of z Ν Λ. h tt c o th ada tagt mag ncud th mnt of th / ow of th data matx and a vcto Z of ngth. h pobabty of dtcton fo a CA CFAR poco fo tagt of ca Swng II, accodng to [8] (4) M M C P CA CA CA CA D CA wh CA th thhod contant fo CA CFAR poco. h pobabty of dtcton fo CFAR BI gna poco n th no tuaton [9] (5) { } 3 D BI R R R C C P wh:, BI BI BI R, BI BI BI R R BI BI BI 3, wh BI th thhod contant fo CFAR BI poco.

8 Fo compaon on th nxt two fgu, th output of CA CFAR and CFAR BI dtcto a pntd. Fg. 5. Examp of a CA CFAR output dtcto h pobabty of dtcton fo an EXC CFAR poco fo tagt mod Swng II, accodng to [6] (6) EXC EXC P D EXC C PE PE е MV, еm V, λ λ wh M V(). th Momnt Gnatng Functon (MGF) and EXC a pdtmnd ca facto fo EXC CFAR poco. 38 Fg. 6. Examp of a CFAR BI output dtcto

9 h MGF of th no v tmat V, may b obtand a (7) MV ( U ) PE ( PE ) MV ( U, ) wh U f (,,, λ ) EXC and th pobabty that a amp x uvv at th xcon output cacuatd a B E E (8) E xp xp. ( ) B P λ λ M V, th condtona MGF of th tmat V wh th numb of amp uvvd at th xcon output. h pobabty of pu tan dtcton fo EXC CFAR BI poco vauatd n uch no tuaton a n [7, ] by h functon ( U ) * * (9) PD CP D EXC ( P D EXC ) EXC BI M wh M bnay dcon u, P D EXC th pobabty of pu dtcton, whch may b found ung th xpon fo EXC CFAR poco wth Poon mpu no. In th on vy ffctv CFAR dtcto ca pap condd, whn both th two-dmnona fnc wndow and th tt c a couptd by andomy avng mpu ntfnc, who avag ptton fquncy and magntud a unnown, [3]. h cnong pocdu gvn n [4, 5], n od to mov th unwantd amp fom both th fnc wndow and th tt c bfo fomng th adaptv thhod and th tt tattc, ud. In th ca th numb of th ntgatd amp n th tt c and ao n th fnc wndow a andom vaab wth bnoma dtbuton. Accodng to th cnong agothm a th mnt wth hgh ntnty of gna a movd fom th fnc wndow and th tt outon c. h cnong agothm cont of th foowng tag: Stag. h mnt of th fnc wndow x ( x, x,..., x ) outon c z ( z z,..., ) magntud, (), z and th tt a an-odd accodng to ncang x x... x... x and z z... z... z. Stag. Each of th o and mnt compad wth th adaptv thhod, accodng to th foowng u: x x z z () x,,...,, and z,,...,, wh x x and z z. 39

10 4 Aft th top of th cuv pocdu, t aumd that mot o a of th andomy avng mpu ntfnc a n th cond pat of th fnc wndow and th tt outon c. In th pap popod th mo gna xpon fo th pobabty of tagt dtcton n th pnc of Poon dtbuton no nvonmnt condton may b cacuatd a n [3]: () API API API API API API API API D API P wh API a pdtmnd ca facto fo API CFAR poco that povd a contant fa aam at (P FA ). h pobabty of fa aam fo th CFAR poco wth tagt mod ca Swng II n andomy avng mpu ntfnc obtand fo vau of gna-to-no ato. Fo compaon and cacuaton of CFAR dtcto o th ato a ud btwn two vau of SR fo dffnt CFAR poco, maud n db. h appoach condd n [4]: (3) CFAR CFAR SR SR og Δ, by 5. cont, CFAR D CFAR D D FA P P P P. 4. umca ut It povd n th pap that dffnt CFAR poco ud fo gna dtcton on th homognou bacgound of unnown ntnty and n th pnc of andomy avng mpu ntfnc wth nown paamt, mpov th dtcton pfomanc. In uch CFAR poco t uuay aumd that th no amptud a Raygh dtbutd vaab and th pow, thfo, an xponntay dtbutd vaab. h numca ut pntd a obtand aft dtad muatona anay of CFAR dtcto pfomanc und no nvonmnt condton. h anay of th pfomanc of dffnt tuctu of on-dmnona and two-dmnona CFAR gna poco CA CFAR (c avag), EXC CFAR (xcon), CFAR BI (bnay ntgaton), EXC CFAR BI (xcon and bnay ntgaton) and API CFAR (adaptv pot ntgaton) don.

11 h achvd ut fo CA CFAR dtcto thhod anay wth th vau of th pobabty of fa aam (P FA ), fo two vau of numb of obvaton n th fnc wndow (), fo two vau of avag ntfnc-tono ato (IR) and fo fv dffnt vau fo a pobabty of appaanc of mpu ntfnc wth avag ngth n th c n ang a pntd n ab. ab P FA 6 3 IR, db IR3, db IR, db IR3, db h pobabty of dtcton fo CA CFAR dtcto hown on Fg. 7 fo contant dtcton thhod achvd fo non homognou ntfnc wth paamt avag pow of th cv no λ, avag IR 3 db, pobabty of appaanc of mpu ntfnc wth avag ngth n th ang c.. h ut fo EXC CFAR dtcto thhod anay wth pobabty of 4 fa aam ( P FA ), xcon contant B E, fo two vau of numb of obvaton n th fnc wndow (), an avag ntfnc-to-no ato (IR 3 db) and nn dffnt vau fo pobabty of appaanc of mpu ntfnc wth avag ngth n th c n ang a pntd n ab. h pobabty of dtcton fo EXC CFAR dtcto hown on Fg. 8. h tudy anayzd fo contant dtcton thhod achvd fo non homognou ntfnc wth paamt avag pow of th cv no λ, avag IR 3 db, pobabty of appaanc of mpu ntfnc wth avag ngth n th ang c..9. 4

12 Fg. 7. Pobabty of dtcton fo CA CFAR dtcto ab Fg. 8. Pobabty of dtcton fo EXC CFAR dtcto 4

13 ab 3 pnt th obtand thhod contant und qua xpmnta condton fo th dffnt CFAR dtcton tuctu wth two-dmnona bnay ntgaton pocdu. h ut a achvd fo a vau of pobabty of fa 4 aam ( P FA ), fo two vau of bnay u /6 and 6/6, fo nn vau of pobabty of appaanc of mpu ntfnc and an avag ntfnc-tono ato (IR3 db). ab 3 M//6 M/6/ h pobabt of dtcton fo CFAR BI dtcto wth two dffnt vau of bnay u on nxt two fgu Fg. 9 ( M / / 6) and Fg. ( M / 6/ 6) a pntd. h ut a achvd fo th foowng paamt - pobabty of fa aam P FA 4, avag pow of th cv no λ, avag IR 3 db, pobabty of appaanc of mpu ntfnc wth avag ngth n th ang c..9. Fg. 9. Pobabty of dtcton fo CFAR BI dtcto 43

14 Fg.. Pobabty of dtcton fo CFAR BI dtcto ab 4 pnt th obtand thhod contant vau und qua xpmnta condton fo th two-dmnona EXC CFAR BI dtcto. h 4 ut a achvd fo vau of pobabty of fa aam ( P FA ), fo two vau of bnay u /6 and 6/6, fo nn vau of pobabty of appaanc of mpu ntfnc and an avag ntfnc-to-no ato (IR3 db). 44 ab 4 M//6 M/6/ h pobabt of dtcton fo EXC CFAR BI dtcto wth two dffnt vau of bnay u on nxt two fgu Fg. ( M / / 6) and Fg. ( M / 6/ 6) a pntd. h ut a achvd fo th foowng paamt pobabty of fa aam P FA 4, xcon contant B E, avag pow of th cv no λ, avag IR 3 db, pobabty of appaanc of mpu ntfnc wth avag ngth n th ang c..9. h numca ut fo th obtand thhod contant vau n qua xpmnta condton fo th two-dmnona API CFAR dtcto a ncudd

15 n ab 5. h ut a achvd fo th vau of pobabty of fa aam (P FA ), fo two vau of numb of obvaton n th fnc wndow (, ), fo two vau of avag IR and fo fv dffnt vau fo a pobabty of appaanc of mpu ntfnc wth avag ngth n th c n ang. Fg.. Pobabty of dtcton fo EXC CFAR BI dtcto Fg.. Pobabty of dtcton fo EXC CFAR BI dtcto 45

16 ab 5 P FA 6 and 6 6 and 3 IR db and IR db and IR 3 db IR 3 db h pobabt chaacttc of dtcton fo API CFAR dtcto a hown on Fg. 3 fo contant dtcton thhod achvd fo non homognou ntfnc wth paamt pobabty of fa aam ( P FA 4 ), fo vau of numb of obvaton n th fnc wndow ( 6, 6), an avag ntfnc-to-no ato (IR3 db) and fv dffnt vau fo pobabty of appaanc of mpu ntfnc wth avag ngth n th c n th ang.. 46 Fg. 3. Pobabty of dtcton fo API CFAR dtcto

17 5. Concuon h xpmnta ut va th nfunc of th ntfnc on th dtcton poc, whn havng contant fa aam at n no nvonmnt condton. h pap pntdcond th ut obtand by th popod adaptv thhod dtmnaton pocdu and th anay of dffnt CFAR dtcto tuctu n ntnv andomy avng mpu ntfnc nvonmnt. h nd fo an adquat thhod anay pocdu, nabng btt dtcton ut fo ow vau of SR, condd. h vau of th tt outon c and th pobabty of fa aam ov th avag dtcton thhod a tudd. h appcaton of cnong tchnqu n th dtcton agothm mpov th CFAR dtcto ffctvn. h ut obtand may hav gnfcant pactca appcaton fo CFAR dtcto wong und no nvonmnt condton. h obtand ut how, that th API CFAR (Adaptv cnong Pot dtcton Intgaton CFAR) poco th mot ffctv n th condton. A a fna concuon th ut achvd n th pntd pap confm onc agan th ncty fo ynth of nw agothm fo movng tagt dtcton, aung obutn and hgh ffcncy of th ada ytm. h ut obtand n th pap coud pactcay b ud n ada and communcaton ntwo. R f n c. F n n, H., R. J o h n o n. Adaptv Dtcton Mod wth hhod Conto a a Functon of Spatay Sampd Cutt Etmaton. RCA Rvw, Vo. 9, 968, o 3, H o u, X.,. M o n a g a,. a m a w a, Dct Evauaton of Rada Dtcton Pobabt. IEEE an., Vo. AES-3, 987, o 4, G o d m a n, H., I. B a -D a v d. Anay and Appcaton of th Excon CFAR Dtcto. In: IEE Poc., Vo. 35, Pt.F, 988, o 6, K a b a c h v, C.,. D o u o v a, I. G a v a n o v. Hough Rada Dtcto n Condton of Intnv Pu Jammng. Sno & anduc Magazn, Spca Iu Mutno Data and Infomaton Pocng, 5, Kabachv, C., I. Gavanov,. Douova. Adaptv Cnong CFAR PI Dtcto wth Hough anfom n Randomy Avng Impu Intfnc. Cybntc and Infomaton chnoog, Vo. 5, 5, o, Kabachv, C., I. Gavanov,. Douova. Excon CFAR BI Dtcto wth Hough anfom n Pnc of Randomy Avng Impu Intfnc. In: Poc. of th Intnatona Rada Sympoum IRS 5, Bn, Gmany, 5, D o u o v a,., C. K a b a c h v. Pfomanc of Hough Dtcto n Pnc of Randomy Avng Impu Intfnc. In: Poc. of th Intnatona Rada Sympoum IRS 6, Kaow, Poand, 6, Kabachv, C.,. Douova, I. Gavanov. C Avagng Contant Fa Aam Rat Dtcto wth Hough anfom n Randomy Avng Impu Intfnc. Cybntc and Infomaton chnoog, Vo. 6, 6, o, D o u o v a,. Hough Dtcto wth Bnay Intgaton Sgna Poco. Compt. Rnd. Acad. Bug. Sc., Vo. 6, 7, o 5, D o u o v a,., V. B h a, C. K a b a c h v. Hough Dtcto Anay by man of Mont Cao Smuaton Appoach. In: Poc. of th Intnatona Rada Sympoum IRS 8, Wocaw, Poand, 8,

18 . D o u o v a,. Movng agt Hough Dtcto n Pu Jammng. Cybntc and Infomaton chnoog, Vo. 7, 7, o, D o u o v a,. Hough Dtcto wth On-dmnona CFAR Poco n Randomy Avng Impu Intfnc. In: Poc. of Dtbutd Comput and Communcaton two, Intnatona Wohop, Sofa, Bugaa, 6, Bha, V., C. Kabachv,. Douova. Adaptv CA CFAR Poco fo Rada agt Dtcton n Pu Jammng. Jouna of VSI Sgna Pocng, Vo. 6,, R o h n g, H. Rada CFAR hhodng n Cutt and Mutp agt Stuaton. IEEE anacton, Vo. AES-9, 983, o 4, D o u o v a,., I. G a v a n o v. Hough Dtcto hhod Anay n Pnc of Randomy Avng Impu Intfnc. Cybntc and Infomaton chnoog, Vo.,, o,

Moving Target Hough Detector in Pulse Jamming*

Moving Target Hough Detector in Pulse Jamming* BULGARIA ACADEMY OF SCIECES CYBEREICS AD IFORMAIO ECHOLOGIES Volum 7 o Sofa 7 Movng agt Hough Dtcto n ul Jammng* Lyuba Douova Inttut of Infomaton chnolog 3 Sofa Abtact: h Hough dtcto wth two typ of a Contant

More information

CFAR BI DETECTOR IN BINOMIAL DISTRIBUTION PULSE JAMMING 1. I. Garvanov. (Submitted by Academician Ivan Popchev on June 23, 2003)

CFAR BI DETECTOR IN BINOMIAL DISTRIBUTION PULSE JAMMING 1. I. Garvanov. (Submitted by Academician Ivan Popchev on June 23, 2003) FA BI EEO I BIOMIAL ISIBUIO PULSE JAMMIG I. Gavanov (Submtted by Academcan Ivan Popchev on June 3, 3) Abtact: In many pactcal tuaton, howeve, the envonment peence of tong pule ammng (PJ) wth hgh ntenty;

More information

PROPERTIES OF PROBABILITY PRODUCTIVE DEPENDENCIES IN THE DATA ANALYSIS OF LARGE DATA VOLUMES

PROPERTIES OF PROBABILITY PRODUCTIVE DEPENDENCIES IN THE DATA ANALYSIS OF LARGE DATA VOLUMES Vo., No., 0 COMPUTATIONAL PROBLEMS OF ELECTRICAL ENGINEERING PROPERTIES OF PROBABILITY PRODUCTIVE DEPENDENCIES IN THE DATA ANALYSIS OF LARGE DATA VOLUMES O Pnycny Lvv Poytcnc Natona Unvty aa.pnycny@gma.com

More information

Lecture 7 Diffusion. Our fluid equations that we developed before are: v t v mn t

Lecture 7 Diffusion. Our fluid equations that we developed before are: v t v mn t Cla ot fo EE6318/Phy 6383 Spg 001 Th doumt fo tutoal u oly ad may ot b opd o dtbutd outd of EE6318/Phy 6383 tu 7 Dffuo Ou flud quato that w dvlopd bfo a: f ( )+ v v m + v v M m v f P+ q E+ v B 13 1 4 34

More information

Multi-linear Systems and Invariant Theory. in the Context of Computer Vision and Graphics. Class 4: Mutli-View 3D-from-2D. CS329 Stanford University

Multi-linear Systems and Invariant Theory. in the Context of Computer Vision and Graphics. Class 4: Mutli-View 3D-from-2D. CS329 Stanford University Mult-lna Sytm and Invaant hoy n th Contxt of Comut Von and Gahc Cla 4: Mutl-Vw 3D-fom-D CS39 Stanfod Unvty Amnon Shahua Cla 4 Matal W Wll Cov oday Eola Gomty and Fundamntal Matx h lan+aallax modl and latv

More information

Differential Kinematics

Differential Kinematics Lctu Diffntia Kinmatic Acknowgmnt : Pof. Ouama Khatib, Robotic Laboato, tanfo Univit, UA Pof. Ha Aaa, AI Laboato, MIT, UA Guiing Qution In obotic appication, not on th poition an ointation, but th vocit

More information

Rectification and Depth Computation

Rectification and Depth Computation Dpatmnt of Comput Engnng Unvst of Cafona at Santa Cuz Rctfcaton an Dpth Computaton CMPE 64: mag Anass an Comput Vson Spng 0 Ha ao 4/6/0 mag cosponncs Dpatmnt of Comput Engnng Unvst of Cafona at Santa Cuz

More information

Nonlinear vibration of a cantilever beam

Nonlinear vibration of a cantilever beam Roct Inttut of Tcnoogy RIT Scoa Wok T T/Dtaton Cocton 7 Nonna vbaton of a cantv bam Iván Dgado-Vázquz Foow t and addtona wok at: ttp://coawok.t.du/t Rcommd Ctaton Dgado-Vázquz, Iván, "Nonna vbaton of a

More information

Speed Control of Direct Torque Controlled Induction Motor By using PI, Anti-Windup PI and Fuzzy Logic Controller

Speed Control of Direct Torque Controlled Induction Motor By using PI, Anti-Windup PI and Fuzzy Logic Controller Intnatonal Jounal of Intllgnt Sytm and Applcaton n Engnng Advancd Tchnology and Scnc ISSN:7-7997-799 www.atcnc.og/ijisae Ognal Rach Pap Spd Contol of Dct Toqu Contolld Inducton Moto By ung, Ant-Wndup and

More information

Loss Minimization Control for Doubly-Fed Induction Generators in Variable Speed Wind Turbines

Loss Minimization Control for Doubly-Fed Induction Generators in Variable Speed Wind Turbines Th 33d Annual Confnc of th IEEE Indutal Elctonc Soct (IECON) Nov. 5-8, 7, Tap, Tawan o Mnmzaton Contol fo Doubl-Fd Inducton Gnato n Vaabl Spd Wnd Tubn Ahmd G. Abo- Khall, Hong-Guk Pak, Dong-Choon Dpt.

More information

Time to Recruitment for a Single Grade Manpower System with Two Thresholds, Different Epochs for Inter-Decisions and Exits Having Correlated Wastages

Time to Recruitment for a Single Grade Manpower System with Two Thresholds, Different Epochs for Inter-Decisions and Exits Having Correlated Wastages IOR Jouna of Mahmac IOR-JM -IN: 78-578 -IN: 39-765X. Voum 3 Iu 4 V. III Ju. u. 7 PP 38-4 www.oouna.o m o Rcumn fo a n ad Manow m wh wo hhod Dffn och fo In-Dcon x Havn Coad Waa. Ravchan ;. nvaan an Pofo

More information

School of Aeronautic Science and Engineering, Beihang Universty, Beijing, China

School of Aeronautic Science and Engineering, Beihang Universty, Beijing, China Snd Ods fo pnts to pnts@bnthamscnc.nt 5 Th Opn Ectca & Ectonc Engnng Jouna, 214, 8, 5-55 Opn Accss Study on Infunc of Thcknss and Ectomagntc Paamt of Pfcty Matchd Lay (PML) Jnzu J * and Fang Lu Schoo of

More information

SUNWAY UNIVERSITY BUSINESS SCHOOL SAMPLE FINAL EXAMINATION FOR FIN 3024 INVESTMENT MANAGEMENT

SUNWAY UNIVERSITY BUSINESS SCHOOL SAMPLE FINAL EXAMINATION FOR FIN 3024 INVESTMENT MANAGEMENT UNWA UNIVRIT BUIN HOOL AMPL FINAL AMINATION FOR FIN 34 INVTMNT MANAGMNT TION A A ALL qto th cto. Qto tha kg facg fo a ca. Th local bak ha ag to gv hm a loa fo 9% of th cot of th ca h ll pay th t cah a

More information

CERTAIN RESULTS ON TIGHTENED-NORMAL-TIGHTENED REPETITIVE DEFERRED SAMPLING SCHEME (TNTRDSS) INDEXED THROUGH BASIC QUALITY LEVELS

CERTAIN RESULTS ON TIGHTENED-NORMAL-TIGHTENED REPETITIVE DEFERRED SAMPLING SCHEME (TNTRDSS) INDEXED THROUGH BASIC QUALITY LEVELS Intnatonal Rsach Jounal of Engnng and Tchnology (IRJET) -ISSN: 2395-0056 Volum: 03 Issu: 02 Fb-2016 www.jt.nt p-issn: 2395-0072 CERTAIN RESULTS ON TIGHTENED-NORMAL-TIGHTENED REPETITIVE DEFERRED SAMPLING

More information

Control Systems. Lecture 8 Root Locus. Root Locus. Plant. Controller. Sensor

Control Systems. Lecture 8 Root Locus. Root Locus. Plant. Controller. Sensor Cotol Syt ctu 8 Root ocu Clacal Cotol Pof. Eugo Schut hgh Uvty Root ocu Cotoll Plat R E C U Y - H C D So Y C C R C H Wtg th loo ga a w a ttd tackg th clod-loo ol a ga va Clacal Cotol Pof. Eugo Schut hgh

More information

5- Scattering Stationary States

5- Scattering Stationary States Lctu 19 Pyscs Dpatmnt Yamou Unvsty 1163 Ibd Jodan Pys. 441: Nucla Pyscs 1 Pobablty Cunts D. Ndal Esadat ttp://ctaps.yu.du.jo/pyscs/couss/pys641/lc5-3 5- Scattng Statonay Stats Rfnc: Paagaps B and C Quantum

More information

EE243 Advanced Electromagnetic Theory Lec # 22 Scattering and Diffraction. Reading: Jackson Chapter 10.1, 10.3, lite on both 10.2 and 10.

EE243 Advanced Electromagnetic Theory Lec # 22 Scattering and Diffraction. Reading: Jackson Chapter 10.1, 10.3, lite on both 10.2 and 10. Appid M Fa 6, Nuuth Lctu # V //6 43 Advancd ctomagntic Thoy Lc # Scatting and Diffaction Scatting Fom Sma Obcts Scatting by Sma Dictic and Mtaic Sphs Coction of Scatts Sphica Wav xpansions Scaa Vcto Rading:

More information

Applications of Lagrange Equations

Applications of Lagrange Equations Applcaton of agang Euaton Ca Stuy : Elctc Ccut ng th agang uaton of oton, vlop th athatcal ol fo th ccut hown n Fgu.Sulat th ult by SIMI. Th ccuty paat a: 0.0 H, 0.00 H, 0.00 H, C 0.0 F, C 0. F, 0 Ω, Ω

More information

4.8 Huffman Codes. Wordle. Encoding Text. Encoding Text. Prefix Codes. Encoding Text

4.8 Huffman Codes. Wordle. Encoding Text. Encoding Text. Prefix Codes. Encoding Text 2/26/2 Word A word a word coag. A word contrctd ot of on of th ntrctor ar: 4.8 Hffan Cod word contrctd ng th java at at word.nt word a randozd grdy agorth to ov th ackng rob Encodng Txt Q. Gvn a txt that

More information

Neural Networks The ADALINE

Neural Networks The ADALINE Lat Lctu Summay Intouction to ua to Bioogica uon Atificia uon McCuoch an itt LU Ronbatt cton Aan Bnaino, a@i.it.ut.t Machin Laning, 9/ ua to h ADALI M A C H I L A R I G 9 / cton Limitation cton aning u

More information

EE 584 MACHINE VISION

EE 584 MACHINE VISION MTU 584 Lctu Not by A.AydnALATAN 584 MACHIN VISION Photomtc Sto Radomty BRDF Rflctanc Ma Rcovng Sufac Ontaton MTU 584 Lctu Not by A.AydnALATAN Photomtc Sto It obl to cov th ontaton of ufac atch fom a numb

More information

Extinction Ratio and Power Penalty

Extinction Ratio and Power Penalty Application Not: HFAN-.. Rv.; 4/8 Extinction Ratio and ow nalty AVALABLE Backgound Extinction atio is an impotant paamt includd in th spcifications of most fib-optic tanscivs. h pupos of this application

More information

FI 3103 Quantum Physics

FI 3103 Quantum Physics 7//7 FI 33 Quantum Physics Axan A. Iskana Physics of Magntism an Photonics sach oup Institut Tknoogi Banung Schoing Equation in 3D Th Cnta Potntia Hyognic Atom 7//7 Schöing quation in 3D Fo a 3D pobm,

More information

SENSORLESS DIRECT FIELD ORIENTED CONTROL OF INDUCTION MACHINE BY FLUX AND SPEED ESTIMATION USING MODEL REFERENCE ADAPTIVE SYSTEM

SENSORLESS DIRECT FIELD ORIENTED CONTROL OF INDUCTION MACHINE BY FLUX AND SPEED ESTIMATION USING MODEL REFERENCE ADAPTIVE SYSTEM SENSORESS DIRECT FIED ORIENTED CONTRO OF INDUCTION MACHINE BY FUX AND SPEED ESTIMATION USING MODE REFERENCE ADAPTIVE SYSTEM A THESIS SUBMITTED TO THE GRADUATE SCHOO OF NATURA AND APPIED SCIENCES OF THE

More information

CIVL 7/ D Boundary Value Problems - Axisymmetric Elements 1/8

CIVL 7/ D Boundary Value Problems - Axisymmetric Elements 1/8 CIVL 7/8 -D Bounday Valu Poblms - xsymmtc Elmnts /8 xsymmtc poblms a somtms fd to as adally symmtc poblms. hy a gomtcally th-dmnsonal but mathmatcally only two-dmnsonal n th physcs of th poblm. In oth

More information

Existence of Nonoscillatory Solutions for a Class of N-order Neutral Differential Systems

Existence of Nonoscillatory Solutions for a Class of N-order Neutral Differential Systems Vo 3 No Mod Appd Scc Exsc of Nooscaoy Souos fo a Cass of N-od Nua Dffa Sysms Zhb Ch & Apg Zhag Dpam of Ifomao Egg Hua Uvsy of Tchoogy Hua 4 Cha E-ma: chzhbb@63com Th sach s facd by Hua Povc aua sccs fud

More information

CBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane.

CBSE , ˆj. cos CBSE_2015_SET-1. SECTION A 1. Given that a 2iˆ ˆj. We need to find. 3. Consider the vector equation of the plane. CBSE CBSE SET- SECTION. Gv tht d W d to fd 7 7 Hc, 7 7 7. Lt,. W ow tht.. Thus,. Cosd th vcto quto of th pl.. z. - + z = - + z = Thus th Cts quto of th pl s - + z = Lt d th dstc tw th pot,, - to th pl.

More information

How to Use. The Bears Beat the Sharks!

How to Use. The Bears Beat the Sharks! Hw t U Th uc vd 24 -wd dng ctn bd n wht kd ncunt vy dy, uch mv tng, y, n Intnt ch cn. Ech ctn ccmnd by tw w-u ctc g ng tudnt cmhnn th ctn. Th dng ctn cn b ud wth ndvdu, m gu, th wh c. Th B cnd bmn, Dn

More information

Optimum PSK Signal Mapping for Multi-Phase Binary-CDMA Systems

Optimum PSK Signal Mapping for Multi-Phase Binary-CDMA Systems Omum Sgnal Mappng fo Mult-Pha Bnay-CDMA Sytm Yong-Jn So and Yong-Hwan L Shool of Eltal Engnng and INMC Soul Natonal Unvty Kwanak P O Box 34 Soul 5-744 Koa -mal: yl@nuak Atat - Although th CDMA ytm an ffntly

More information

Mid Year Examination F.4 Mathematics Module 1 (Calculus & Statistics) Suggested Solutions

Mid Year Examination F.4 Mathematics Module 1 (Calculus & Statistics) Suggested Solutions Mid Ya Eamination 3 F. Matmatics Modul (Calculus & Statistics) Suggstd Solutions Ma pp-: 3 maks - Ma pp- fo ac qustion: mak. - Sam typ of pp- would not b countd twic fom wol pap. - In any cas, no pp maks

More information

Load Equations. So let s look at a single machine connected to an infinite bus, as illustrated in Fig. 1 below.

Load Equations. So let s look at a single machine connected to an infinite bus, as illustrated in Fig. 1 below. oa Euatons Thoughout all of chapt 4, ou focus s on th machn tslf, thfo w wll only pfom a y smpl tatmnt of th ntwok n o to s a complt mol. W o that h, but alz that w wll tun to ths ssu n Chapt 9. So lt

More information

The Random Phase Approximation:

The Random Phase Approximation: Th Random Phas Appoxmaton: Elctolyts, Polym Solutons and Polylctolyts I. Why chagd systms a so mpotant: thy a wat solubl. A. bology B. nvonmntally-fndly polym pocssng II. Elctolyt solutons standad dvaton

More information

Cluster Optimization for Takagi & Sugeno Fuzzy Models and Its Application to a Combined Cycle Power Plant Boiler

Cluster Optimization for Takagi & Sugeno Fuzzy Models and Its Application to a Combined Cycle Power Plant Boiler Clut Optmzaton o Takag & Sugno Fuzzy Modl It Applcaton to a Combnd Cycl Pow Plant Bol Do Sáz, Mmb IEEE, Robto Zuñga, Studnt Mmb IEEE Abtact- In th pap, a nw mthod o clut numb optmzaton o Takag & Sugno

More information

Prespacetime-Premomentumenergy Model II: Genesis of Self-Referential Matrix Law & Mathematics of Ether. Huping Hu * & Maoxin Wu ABSTRACT

Prespacetime-Premomentumenergy Model II: Genesis of Self-Referential Matrix Law & Mathematics of Ether. Huping Hu * & Maoxin Wu ABSTRACT cnfc GOD Jouna Novb 24 ou 5 Iu. 965-5 Hu H. &Wu. Pac-Ponungy od II: Gn of f-rfna a aw & ahac of h 965 Pac-Ponungy od II: Gn of f-rfna a aw & ahac of h c Hung Hu * & aon Wu BTRCT Th wok a connuaon of ac-onungy

More information

Excellent web site with information on various methods and numerical codes for scattering by nonspherical particles:

Excellent web site with information on various methods and numerical codes for scattering by nonspherical particles: Lectue 5. Lght catteng and abopton by atmophec patcuate. at 3: Scatteng and abopton by nonpheca patce: Ray-tacng, T- Matx, and FDTD method. Objectve:. Type of nonpheca patce n the atmophee.. Ray-tacng

More information

High-Resolution Impulse Radio Ultra Wideband Ranging

High-Resolution Impulse Radio Ultra Wideband Ranging Hh-Routon Imu Rado Uta Wdand Rann Ha Zhan,, Jaouha Aad, John aotu and Jan-Y Boudc {hazhan, jaouhaaad, johnfaotu}@cmch, {jan-oudc}@fch Cnt Su d'ectonu t d Mcotchnu SA (CSEM, W Communcaton Scton, uchat,

More information

School of Electrical Engineering. Lecture 2: Wire Antennas

School of Electrical Engineering. Lecture 2: Wire Antennas School of lctical ngining Lctu : Wi Antnnas Wi antnna It is an antnna which mak us of mtallic wis to poduc a adiation. KT School of lctical ngining www..kth.s Dipol λ/ Th most common adiato: λ Dipol 3λ/

More information

Average Decision Threshold of CA CFAR and excision CFAR Detectors in the Presence of Strong Pulse Jamming 1

Average Decision Threshold of CA CFAR and excision CFAR Detectors in the Presence of Strong Pulse Jamming 1 Average Decson hreshold of CA CFAR and excson CFAR Detectors n the Presence of Strong Pulse Jammng Ivan G. Garvanov and Chrsto A. Kabachev Insttute of Informaton echnologes Bulgaran Academy of Scences

More information

If we cannot accept your contribution in your preferred presentation mode, would you still be prepared to present in the alternative mode (tick one):

If we cannot accept your contribution in your preferred presentation mode, would you still be prepared to present in the alternative mode (tick one): Pap Submon Fom Nam of Pntng Autho Ahmt Bd Öz Add )ÕUDW hqlyhuvlwhvl 0 KHQGLVOLN )DN OWHVL %LOJLVD\DU 0 KHQGLVOL L (OD]Õ 7 UNL\H Phon (+904242370000 (5292) cp: 05333303642) Fax (+90424 2383787) Oth autho:

More information

PLANAR KNOTTING MECHANISMS FOR TURKISH HAND WOVEN CARPET

PLANAR KNOTTING MECHANISMS FOR TURKISH HAND WOVEN CARPET PLANAR KNOTTIN ECHANISS OR TURKISH HAND WOVEN CARPET E THEORY O ACHINES INSTRUCTOR:POR.DR.TECH.SCI.RASI ALIZADE ASISTANT:RES.ASST.OZUN SELVI :ROUUP EBER NAES: AHET APAK 7 SERKAN CİLARA DENİZ ÖZÜN 6 LEVENT

More information

CBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find

CBSE SAMPLE PAPER SOLUTIONS CLASS-XII MATHS SET-2 CBSE , ˆj. cos. SECTION A 1. Given that a 2iˆ ˆj. We need to find BSE SMLE ER SOLUTONS LSS-X MTHS SET- BSE SETON Gv tht d W d to fd 7 7 Hc, 7 7 7 Lt, W ow tht Thus, osd th vcto quto of th pl z - + z = - + z = Thus th ts quto of th pl s - + z = Lt d th dstc tw th pot,,

More information

An Improved Programme for Deformation Analysis of Vertical Networks

An Improved Programme for Deformation Analysis of Vertical Networks An Improvd Programm for Dformaton Anay of Vrtca Ntwor Cma Ozr YIGIT and Cvat INAL, TURKEY Ky word: Qua-Statc dformaton anay, vrtca ntwor, programmng, S tranformaton SUMMARY Dformaton maurmnt and dformaton

More information

First looking at the scalar potential term, suppose that the displacement is given by u = φ. If one can find a scalar φ such that u = φ. u x.

First looking at the scalar potential term, suppose that the displacement is given by u = φ. If one can find a scalar φ such that u = φ. u x. 7.4 Eastodynams 7.4. Propagaton of Wavs n East Sods Whn a strss wav travs throgh a matra, t ass matra parts to dspa by. It an b shown that any vtor an b wrttn n th form φ + ra (7.4. whr φ s a saar potnta

More information

Studying the Steady State Performance Characteristics of Induction Motor with Field Oriented Control Comparing to Scalar Control

Studying the Steady State Performance Characteristics of Induction Motor with Field Oriented Control Comparing to Scalar Control EJERS, Euopan Jounal of Engining Rach and Scinc Studying th Stady Stat fomanc Chaactitic of nduction Moto with Fild Ointd Contol Compaing to Scala Contol Hamdy Mohamd Soliman Abtact Fild ointd contol i

More information

COMPSCI 230 Discrete Math Trees March 21, / 22

COMPSCI 230 Discrete Math Trees March 21, / 22 COMPSCI 230 Dict Math Mach 21, 2017 COMPSCI 230 Dict Math Mach 21, 2017 1 / 22 Ovviw 1 A Simpl Splling Chck Nomnclatu 2 aval Od Dpth-it aval Od Badth-it aval Od COMPSCI 230 Dict Math Mach 21, 2017 2 /

More information

TRANSIENT PROCESSES AND DYNAMIC OF VARIABLE SPEED PUMP STORAGE UNIT

TRANSIENT PROCESSES AND DYNAMIC OF VARIABLE SPEED PUMP STORAGE UNIT Ol Shal, 203, Vol. 30, No. 2S, pp. 244 256 ISSN 020889X do: 0.376/ol.203.2S.05 203 Etonan Acadmy ublh TRANSIENT ROCESSES AND DYNAMIC OF VARIABLE SEED UM STORAGE UNIT RIMANTAS RANAS DEKSNYS *, DARIUS ALIŠAUSKAS

More information

Cycle Slip Detection and Fixing by MEMS-IMU/GPS Integration for Mobile Environment RTK-GPS

Cycle Slip Detection and Fixing by MEMS-IMU/GPS Integration for Mobile Environment RTK-GPS Cycl Slp tcton and Fxng y MEMS-MU/GS ntgaton fo Mol Envonmnt RK-GS omoj aasu, Ao Yasuda oyo Unvsty of Man Scnc and chnology, Japan BOGRAHY omoj aasu s a sach n Funa Laoatoy of Satllt Navgaton at oyo Unvsty

More information

Grand Canonical Ensemble

Grand Canonical Ensemble Th nsmbl of systms mmrsd n a partcl-hat rsrvor at constant tmpratur T, prssur P, and chmcal potntal. Consdr an nsmbl of M dntcal systms (M =,, 3,...M).. Thy ar mutually sharng th total numbr of partcls

More information

STRIPLINES. A stripline is a planar type transmission line which is well suited for microwave integrated circuitry and photolithographic fabrication.

STRIPLINES. A stripline is a planar type transmission line which is well suited for microwave integrated circuitry and photolithographic fabrication. STIPLINES A tiplin i a plana typ tanmiion lin hih i ll uitd fo mioav intgatd iuity and photolithogaphi faiation. It i uually ontutd y thing th nt onduto of idth, on a utat of thikn and thn oving ith anoth

More information

Hu, H. &Wu, M. Prespacetime-Premomentumenergy Model II: Genesis of Self-Referential Matrix Law & Mathematics of Ether

Hu, H. &Wu, M. Prespacetime-Premomentumenergy Model II: Genesis of Self-Referential Matrix Law & Mathematics of Ether Hu H. &Wu. Pac-Ponungy od II: Gn of f-rfna a aw & ahac of h Pac-Ponungy od II: Gn of f-rfna a aw & ahac of h c Hung Hu * & aon Wu BTRCT Th wok a connuaon of ac-onungy od dcbd cny. H w how how n h od ac-onungy

More information

Shor s Algorithm. Motivation. Why build a classical computer? Why build a quantum computer? Quantum Algorithms. Overview. Shor s factoring algorithm

Shor s Algorithm. Motivation. Why build a classical computer? Why build a quantum computer? Quantum Algorithms. Overview. Shor s factoring algorithm Motivation Sho s Algoith It appas that th univs in which w liv is govnd by quantu chanics Quantu infoation thoy givs us a nw avnu to study & tst quantu chanics Why do w want to build a quantu coput? Pt

More information

Prespacetime-Premomentumenergy Model II: Generation. of Self-Referential Matrix Law &Mathematics of Ether. Huping Hu * & Maoxin Wu ABSTRACT

Prespacetime-Premomentumenergy Model II: Generation. of Self-Referential Matrix Law &Mathematics of Ether. Huping Hu * & Maoxin Wu ABSTRACT Jouna of Concoun oaon & Rach Novb 24 ou 5 Iu. 97-2 Hu H. &Wu. Pac-Ponungy od II: Gnaon of f-rfna a aw & ahac of h 97 Pac-Ponungy od II: Gnaon of f-rfna a aw &ahac of h c Hung Hu * & aon Wu BTRCT Th wok

More information

ROTOR RESISTANCE IDENTIFICATION USING NEURAL NETWORKS FOR INDUCTION MOTOR DRIVES IN THE CASE OF INSENSITIVITY TO LOAD VARIATIONS *

ROTOR RESISTANCE IDENTIFICATION USING NEURAL NETWORKS FOR INDUCTION MOTOR DRIVES IN THE CASE OF INSENSITIVITY TO LOAD VARIATIONS * Ianian Jounal of Scinc & Tchnology, Tanaction B, Engining, Vol. 30, No. B2 Pintd in Th Ilamic Rpublic of Ian, 2006 Shiaz Univity ROTOR RESISTANCE IDENTIFICATION USING NEURA NETWORKS FOR INDUCTION MOTOR

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

Lecture 2: Frequency domain analysis, Phasors. Announcements

Lecture 2: Frequency domain analysis, Phasors. Announcements EECS 5 SPRING 24, ctu ctu 2: Fquncy domain analyi, Phao EECS 5 Fall 24, ctu 2 Announcmnt Th cou wb it i http://int.c.bkly.du/~5 Today dicuion ction will mt Th Wdnday dicuion ction will mo to Tuday, 5:-6:,

More information

ESCI 341 Atmospheric Thermodynamics Lesson 14 Curved Droplets and Solutions Dr. DeCaria

ESCI 341 Atmospheric Thermodynamics Lesson 14 Curved Droplets and Solutions Dr. DeCaria ESCI 41 Atmophric hrmodynamic Lon 14 Curd Dropt and Soution Dr. DCaria Rfrnc: hrmodynamic and an Introduction to hrmotatitic, Can Phyica Chmitry, Lin A hort Cour in Coud Phyic, Rogr and Yau hrmodynamic

More information

J. Milli Monfared K. Abbaszadeh E. Fallah Assistant Professor P.H.D Student P.H.D Student

J. Milli Monfared K. Abbaszadeh E. Fallah Assistant Professor P.H.D Student P.H.D Student olng an Smulaton of Dual h Pha Inucton achn n Fault conton wo Pha cut off) an Popo A Nw Vcto Contol Appoach fo oqu Ocllaton Ructon J. ll onfa K. Abbazah E. Fallah Atant Pofo P.H.D Stunt P.H.D Stunt Amkab

More information

Estimation of a proportion under a certain two-stage sampling design

Estimation of a proportion under a certain two-stage sampling design Etmaton of a roorton under a certan two-tage amng degn Danutė Kraavcatė nttute of athematc and nformatc Lthuana Stattc Lthuana Lthuana e-ma: raav@tmt Abtract The am of th aer to demontrate wth exame that

More information

Course 10 Shading. 1. Basic Concepts: Radiance: the light energy. Light Source:

Course 10 Shading. 1. Basic Concepts: Radiance: the light energy. Light Source: Cour 0 Shadg Cour 0 Shadg. Bac Coct: Lght Sourc: adac: th lght rg radatd from a ut ara of lght ourc or urfac a ut old agl. Sold agl: $ # r f lght ourc a ot ourc th ut ara omttd abov dfto. llumato: lght

More information

AI BASED VECTOR CONTROL OF INDUCTION MOTOR

AI BASED VECTOR CONTROL OF INDUCTION MOTOR AI BASED VECTOR CONTROL OF INDUCTION MOTOR K.Padukola Elctcal and lctonc ngnng S Vdya collg of Engnng and Tchnology, Inda padukola@gmal.com Abtact- In modn hgh pfomanc ac dv uually th dct vcto contol chm

More information

D. Bertsekas and R. Gallager, "Data networks." Q: What are the labels for the x-axis and y-axis of Fig. 4.2?

D. Bertsekas and R. Gallager, Data networks. Q: What are the labels for the x-axis and y-axis of Fig. 4.2? pd by J. Succ ECE 543 Octob 22 2002 Outl Slottd Aloh Dft Stblzd Slottd Aloh Uslottd Aloh Splttg Algoths Rfc D. Btsks d R. llg "Dt twoks." Rvw (Slottd Aloh): : Wht th lbls fo th x-xs d y-xs of Fg. 4.2?

More information

Induction Motor Speed Control using Fuzzy Logic Controller

Induction Motor Speed Control using Fuzzy Logic Controller Wold cadmy of Scnc, Engnng and Tchnology Intnatonal Jounal of Elctcal and Comput Engnng Vol:, No:, 008 Inducton Moto Spd Contol ung Fuzzy Logc Contoll V. Chta, and R. S. Pabhaka Intnatonal Scnc Indx, Elctcal

More information

Article Premomentumenergy Model II: Genesis of Self-Referential Matrix Law & Mathematics of Ether

Article Premomentumenergy Model II: Genesis of Self-Referential Matrix Law & Mathematics of Ether cnfc GOD Jouna Novmb 4 Voum 5 Iu 9. 83-863 Hu H. & Wu. Pmomnumngy od II: Gn of f-rfna a aw & ahmac of h 83 c Pmomnumngy od II: Gn of f-rfna a aw & ahmac of h Hung Hu * & aon Wu BTRCT Th wok a connuaon

More information

(( ) ( ) ( ) ( ) ( 1 2 ( ) ( ) ( ) ( ) Two Stage Cluster Sampling and Random Effects Ed Stanek

(( ) ( ) ( ) ( ) ( 1 2 ( ) ( ) ( ) ( ) Two Stage Cluster Sampling and Random Effects Ed Stanek Two ag ampling and andom ffct 8- Two Stag Clu Sampling and Random Effct Ed Stank FTE POPULATO Fam Labl Expctd Rpon Rpon otation and tminology Expctd Rpon: y = and fo ach ; t = Rpon: k = y + Wk k = indx

More information

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9 OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at

More information

Chapter 3 Basic Crystallography and Electron Diffraction from Crystals. Lecture 12. CHEM 793, 2008 Fall

Chapter 3 Basic Crystallography and Electron Diffraction from Crystals. Lecture 12. CHEM 793, 2008 Fall Chapt 3 Bac Cytalloaphy and Elcton Dacton om Cytal Lctu 1 CHEM 793, 008 all Announcmnt Mdtm Exam: Oct., Wdnday, :30 4:30 CHEM 793, 008 all Th xctaton o, Ba' Law and th Lau quaton pdct dacton at only pc

More information

STATISTICAL MECHANICS OF DIATOMIC GASES

STATISTICAL MECHANICS OF DIATOMIC GASES Pof. D. I. ass Phys54 7 -Ma-8 Diatomic_Gas (Ashly H. Cat chapt 5) SAISICAL MECHAICS OF DIAOMIC GASES - Fo monatomic gas whos molculs hav th dgs of fdom of tanslatoy motion th intnal u 3 ngy and th spcific

More information

Theoretical Electron Impact Ionization, Recombination, and Photon Emissivity Coefficient for Tungsten Ions

Theoretical Electron Impact Ionization, Recombination, and Photon Emissivity Coefficient for Tungsten Ions TM on Unctanty ssssmnt and Bnchmak Expmnts fo &M Data fo Fuson pplcatons Thotcal Elcton Impact Ionzaton, Rcombnaton, and Photon Emssvty Coffcnt fo Tungstn Ions D.-H. Kwon, Koa tomc Engy Rsach Insttut 2016.

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Premomentumenergy Model II: Creation of Self-Referential Matrix Law & Mathematics of Ether in Consciousness. Huping Hu * & Maoxin Wu ABSTRACT

Premomentumenergy Model II: Creation of Self-Referential Matrix Law & Mathematics of Ether in Consciousness. Huping Hu * & Maoxin Wu ABSTRACT Jouna of Concoun oaon & Rach Novmb 4 Voum 5 Iu 9. 835-866 Hu H. & Wu. Pmomnumngy od II: Caon of f-rfna a aw & ahmac of h n Concoun 835 c Pmomnumngy od II: Caon of f-rfna a aw & ahmac of h n Concoun Hung

More information

International Journal of Advanced Scientific Research and Management, Volume 3 Issue 11, Nov

International Journal of Advanced Scientific Research and Management, Volume 3 Issue 11, Nov 199 Algothm ad Matlab Pogam fo Softwa Rlablty Gowth Modl Basd o Wbull Od Statstcs Dstbuto Akladswa Svasa Vswaatha 1 ad Saavth Rama 2 1 Mathmatcs, Saaatha Collg of Egg, Tchy, Taml Nadu, Ida Abstact I ths

More information

Analysis of a M/G/1/K Queue with Vacations Systems with Exhaustive Service, Multiple or Single Vacations

Analysis of a M/G/1/K Queue with Vacations Systems with Exhaustive Service, Multiple or Single Vacations Analyss of a M/G// uu wth aatons Systms wth Ehaustv Sv, Multpl o Sngl aatons W onsd h th fnt apaty M/G// uu wth th vaaton that th sv gos fo vaatons whn t s dl. Ths sv modl s fd to as on povdng haustv sv,

More information

MECH321 Dynamics of Engineering System Week 4 (Chapter 6)

MECH321 Dynamics of Engineering System Week 4 (Chapter 6) MH3 Dynamc of ngnrng Sytm Wk 4 (haptr 6). Bac lctrc crcut thor. Mathmatcal Modlng of Pav rcut 3. ompl mpdanc Approach 4. Mchancal lctrcal analogy 5. Modllng of Actv rcut: Opratonal Amplfr rcut Bac lctrc

More information

}, the unrestricted process will see a transition to

}, the unrestricted process will see a transition to A u an Mod wt Rvs Inoaton Excang: ot Andx t : Dnng t Rstctd Pocss W gn wt ocusng on a stctd vson o t cot M dscd aov stctd vson osvs t ocss on ov stats o wc N W not tat wnv t stctd ocss s n stats { } t

More information

Homework: Due

Homework: Due hw-.nb: //::9:5: omwok: Du -- Ths st (#7) s du on Wdnsday, //. Th soluton fom Poblm fom th xam s found n th mdtm solutons. ü Sakua Chap : 7,,,, 5. Mbach.. BJ 6. ü Mbach. Th bass stats of angula momntum

More information

Period vs. Length of a Pendulum

Period vs. Length of a Pendulum Gaphcal Mtho n Phc Gaph Intptaton an Lnazaton Pat 1: Gaphng Tchnqu In Phc w u a vat of tool nclung wo, quaton, an gaph to mak mol of th moton of objct an th ntacton btwn objct n a tm. Gaph a on of th bt

More information

Who is this Great Team? Nickname. Strangest Gift/Friend. Hometown. Best Teacher. Hobby. Travel Destination. 8 G People, Places & Possibilities

Who is this Great Team? Nickname. Strangest Gift/Friend. Hometown. Best Teacher. Hobby. Travel Destination. 8 G People, Places & Possibilities Who i thi Gt Tm? Exi Sh th foowing i of infomtion bot of with o tb o tm mt. Yo o not hv to wit n of it own. Yo wi b givn on 5 mint to omih thi tk. Stngt Gift/Fin Niknm Homtown Bt Th Hobb Tv Dtintion Robt

More information

Bethe-Salpeter Equation Green s Function and the Bethe-Salpeter Equation for Effective Interaction in the Ladder Approximation

Bethe-Salpeter Equation Green s Function and the Bethe-Salpeter Equation for Effective Interaction in the Ladder Approximation Bh-Salp Equaon n s Funcon and h Bh-Salp Equaon fo Effcv Inacon n h Ladd Appoxmaon Csa A. Z. Vasconcllos Insuo d Físca-UFRS - upo: Físca d Hadons Sngl-Pacl Popagao. Dagam xpanson of popagao. W consd as

More information

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9 C C A 55NED n R 5 0 9 b c c \ { s AS EC 2 5? 9 Con 0 \ 0265 o + s ^! 4 y!! {! w Y n < R > s s = ~ C c [ + * c n j R c C / e A / = + j ) d /! Y 6 ] s v * ^ / ) v } > { ± n S = S w c s y c C { ~! > R = n

More information

GRAVITATION. (d) If a spring balance having frequency f is taken on moon (having g = g / 6) it will have a frequency of (a) 6f (b) f / 6

GRAVITATION. (d) If a spring balance having frequency f is taken on moon (having g = g / 6) it will have a frequency of (a) 6f (b) f / 6 GVITTION 1. Two satllits and o ound a plant P in cicula obits havin adii 4 and spctivly. If th spd of th satllit is V, th spd of th satllit will b 1 V 6 V 4V V. Th scap vlocity on th sufac of th ath is

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

Mechanical Property Analysis with Ultrasonic Phased Array

Mechanical Property Analysis with Ultrasonic Phased Array 7th Word onference on Nondetructve Tetng, 25-28 Oct 28, Shangha, hna Mechanca Property Anay wth Utraonc Phaed Array Wen-A SONG, Ke-Y YUAN, Y-Fang HEN, Hu-Mng YAN 2 Department of Mechanca Engneerng, Tnghua

More information

The angle between L and the z-axis is found from

The angle between L and the z-axis is found from Poblm 6 This is not a ifficult poblm but it is a al pain to tansf it fom pap into Mathca I won't giv it to you on th quiz, but know how to o it fo th xam Poblm 6 S Figu 6 Th magnitu of L is L an th z-componnt

More information

Exam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms

Exam 2 Solutions. Jonathan Turner 4/2/2012. CS 542 Advanced Data Structures and Algorithms CS 542 Avn Dt Stutu n Alotm Exm 2 Soluton Jontn Tun 4/2/202. (5 ont) Con n oton on t tton t tutu n w t n t 2 no. Wt t mllt num o no tt t tton t tutu oul ontn. Exln you nw. Sn n mut n you o u t n t, t n

More information

Massachusetts Institute of Technology Introduction to Plasma Physics

Massachusetts Institute of Technology Introduction to Plasma Physics Massachustts Insttut of Tchnology Intoducton to Plasma Physcs NAME 6.65J,8.63J,.6J R. Pak Dcmb 5 Fnal Eam :3-4:3 PM NOTES: Th a 8 pags to th am, plus on fomula sht. Mak su that you copy s complt. Each

More information

α-particles, β-particles and γ-rays upon Atomic Nuclei.

α-particles, β-particles and γ-rays upon Atomic Nuclei. Etoant thod fo bokn th aton of uton, α-pat, β-pat and γ-ay upon Ato u. Fan D Aquno Copyht 01 by Fan D Aquno. A Rht Rvd. H w how an toant thod fo bokn th aton of xtna nuton, α- pat, β-pat and γ-ay upon

More information

Environmental Engineering / Fundamentals of Fluid Mechanics and Heat Transfer 2017/2018

Environmental Engineering / Fundamentals of Fluid Mechanics and Heat Transfer 2017/2018 H H Envonmntal Engnng / Fundamntal o Flud Mcanc and Hat an 07/08. Dtmn t tack pu n a buldng wc m g, t ndoo a tmpatu = +0 C and outdoo a tmpatu = C. Wat t nutal lvl gt, t a two opnng n t buldng nvlop, on

More information

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19)

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19) TOTAL INTRNAL RFLTION Kmacs pops Sc h vcos a coplaa, l s cosd h cd pla cocds wh h X pla; hc 0. y y y osd h cas whch h lgh s cd fom h mdum of hgh dx of faco >. Fo cd agls ga ha h ccal agl s 1 ( /, h hooal

More information

Noise in electronic components.

Noise in electronic components. No lto opot5098, JDS No lto opot Th PN juto Th ut thouh a PN juto ha fou opot t: two ffuo ut (hol fo th paa to th aa a lto th oppot to) a thal at oty ha a (hol fo th aa to th paa a lto th oppot to, laka

More information

Modeling and implementation of vector control for Induction motor Drive

Modeling and implementation of vector control for Induction motor Drive Intnatonal Jounal of Engnng Rach and Gnal Scnc Volum 3, Iu 2, Mach-Apl, 215 Modlng and mplmntaton of cto contol fo Inducton moto D K.Ramh 1,Ch.Ra Kuma 2,P.Bala Mual 3 1 P.G.Studnt,Dpt of EEE,AITAM Engnng

More information

The Log-Gamma-Pareto Distribution

The Log-Gamma-Pareto Distribution aoa Joa of Scc: Bac ad Appd Rach JSBAR SSN 37-453 P & O hp:odphp?oajoaofbacadappd ---------------------------------------------------------------------------------------------------------------------------

More information

and decompose in cycles of length two

and decompose in cycles of length two Permutaton of Proceedng of the Natona Conference On Undergraduate Reearch (NCUR) 006 Domncan Unverty of Caforna San Rafae, Caforna Apr - 4, 007 that are gven by bnoma and decompoe n cyce of ength two Yeena

More information

8-node quadrilateral element. Numerical integration

8-node quadrilateral element. Numerical integration Fnt Elmnt Mthod lctur nots _nod quadrlatral lmnt Pag of 0 -nod quadrlatral lmnt. Numrcal ntgraton h tchnqu usd for th formulaton of th lnar trangl can b formall tndd to construct quadrlatral lmnts as wll

More information

A study on Ricci soliton in S -manifolds.

A study on Ricci soliton in S -manifolds. IO Joual of Mathmatc IO-JM -IN: 78-578 p-in: 9-765 olum Iu I Ja - Fb 07 PP - wwwojoualo K dyavath ad Bawad Dpatmt of Mathmatc Kuvmpu vtyhaaahatta - 577 5 hmoa Kaataa Ida Abtact: I th pap w tudy m ymmtc

More information

ORBITAL TO GEOCENTRIC EQUATORIAL COORDINATE SYSTEM TRANSFORMATION. x y z. x y z GEOCENTRIC EQUTORIAL TO ROTATING COORDINATE SYSTEM TRANSFORMATION

ORBITAL TO GEOCENTRIC EQUATORIAL COORDINATE SYSTEM TRANSFORMATION. x y z. x y z GEOCENTRIC EQUTORIAL TO ROTATING COORDINATE SYSTEM TRANSFORMATION ORITL TO GEOCENTRIC EQUTORIL COORDINTE SYSTEM TRNSFORMTION z i i i = (coωcoω in Ωcoiinω) (in Ωcoω + coωcoiinω) iniinω ( coωinω in Ωcoi coω) ( in Ωinω + coωcoicoω) in icoω in Ωini coωini coi z o o o GEOCENTRIC

More information

Aakash. For Class XII Studying / Passed Students. Physics, Chemistry & Mathematics

Aakash. For Class XII Studying / Passed Students. Physics, Chemistry & Mathematics Aakash A UNIQUE PPRTUNITY T HELP YU FULFIL YUR DREAMS Fo Class XII Studying / Passd Studnts Physics, Chmisty & Mathmatics Rgistd ffic: Aakash Tow, 8, Pusa Road, Nw Dlhi-0005. Ph.: (0) 4763456 Fax: (0)

More information

Plasma Sheaths and Langmuir probes

Plasma Sheaths and Langmuir probes Cass nots fo EE5383/Phys 5383 Spng Ths documnt s fo nstuctona us ony and may not b copd o dstbutd outsd of EE5383/Phys 5383 Last wk w ookd at msson of ght fom a pasma. In ffct ght msson s th smpst dagnostc

More information

Electric Machines. Leila Parsa Rensselaer Polytechnic Institute

Electric Machines. Leila Parsa Rensselaer Polytechnic Institute Elctc Machn la Paa Rnla Polytchnc Inttut 1 Hybd Vhcl Elctc Shp Applcaton 4 Elctc Shp Pow Sytm http://www.nay.ml/naydata/cno/n87/uw/u_9/pow_ytm.html 5 6 Populon Moto 19MW http://nay-matt.bdall.com/mag/mw.gf

More information

Joint Effect Analysis of Phase Noise, Carrier Frequency Offset, Doppler Spread and Nonlinear Amplifier on the Performance of OFDM System

Joint Effect Analysis of Phase Noise, Carrier Frequency Offset, Doppler Spread and Nonlinear Amplifier on the Performance of OFDM System 7th WSEAS Intnational Confnc on Application of Elctical Engining (AEE 8, ondhim, Noway, July -, 8 Joint Effct Analyi of Pha Noi, Cai Fquncy Offt, oppl Spad and Nonlina Amplifi on th Pfomanc of OFM Sytm

More information

Exercises for lectures 7 Steady state, tracking and disturbance rejection

Exercises for lectures 7 Steady state, tracking and disturbance rejection Exrc for lctur 7 Stady tat, tracng and dturbanc rjcton Martn Hromčí Automatc control 06-3-7 Frquncy rpon drvaton Automatcé řízní - Kybrnta a robota W lad a nuodal nput gnal to th nput of th ytm, gvn by

More information