Moving Target Hough Detector in Pulse Jamming*

Size: px
Start display at page:

Download "Moving Target Hough Detector in Pulse Jamming*"

Transcription

1 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 Fal Alam Rat (CFAR) poco a Cll Avagng (CA CFAR) poco and an Excon (EXC CFAR) poco n th pnc of pul ammng nvtgatd n th pnt pap. h dtcton pobablty and th avag dtcton thhold of a Hough dtcto wth th two typ of CFAR poco a tudd. h xpmntal ult a obtand by numcal analy. hy val that th u of Hough dtcto allow ducng datcally dtctablty lo n compaon to th convntonal CFAR dtcto and that t ffctv fo mall gnal-to-no ato. h ach wo pfomd n MALAB computatonal nvonmnt. h obtand analytcal ult fo Hough dtcto can b ud n both ada and communcaton cv ntwo. Kywod: Rada Dtcto Hough dtcto ul Jammng obablty of dtcton obablty of fal alam Dtctablty poft (lo).. Intoducton Dung th lat fw ya mathmatcal mthod fo xtacton of uful data about th bhavo of obvd tagt by mathmatcal tanfomaton of cvd gnal a bng wdly ud n th dgn of nw hghly ffctv algothm fo pocng ada nfomaton. Such a mathmatcal appoach th Hough anfom (H). h concpt of ung th H fo mpovng th tagt dtcton n wht Gauan no ntoducd by Calon Evan and Wlon n [ 3]. h appoach ud by Calon n [3] fo a hghly fluctuatng tagt Swlng II typ tagt modl and tatonay homognou ntfnc. In modn ada th tagt dtcton dclad f th gnal valu xcd a plmnay dtmnd adaptv thhold. h cunt tmaton of th no lvl n th fnc wndow fom th thhold. o tmat th no lvl fo ada gnal dtcton n clutt nvonmnt wth unnown avag pow lvl th tchnqu popod by Fnn and Johnon n [4] oftn ud. Avagng th output * h wo uppotd by poct II 89/7 MS Ltd. Gant IF--85/5 and Gant MI-56/5. 6 7

2 of th fnc cll uoundng th tt cll fom th tmat. h dtcton thhold dtmnd a a poduct of th no lvl tmat n th fnc wndow and a cal facto to achv th dd pobablty of fal alam. hu a contant fal alam at mantand n th poc of dtcton. h CA CFAR poco (Cll Avagng Contant Fal Alam Rat oco) a vy ffctv n ca of tatonay and homognou ntfnc. h pnc of pul ammng n both tt oluton cll and th fnc cll can cau datc dgadaton n th pfomanc of th CA CFAR poco [6]. Such typ of ntfnc non-tatonay and non-homognou and oftn caud by adacnt ada o oth ado-lctonc dvc. A tchnqu that may b ud to allvat th poblm th xcon of tong pul bfo a cll-avagng pocdu. h appoach fo an EXC CFAR dtcto pntd by Goldman and Ba-Davd and analyzd fo multpl tagt tuaton n [8 9]. h analytcal xpon fo th pobablty of dtcton and th pobablty of fal alam of EXC CFAR and EXC CFAR BI dtcto n th pnc of oon dtbuton pul ammng and Ralgh ampltud dtbuton n both tt and fnc wndow a pntd n []. h gnal modl bad on th fact that th law of dtbuton of mpul ntfnc chang fom oon to bnomal wth th ncang of th pobablty of appaanc of andomly avng mpul gat than. []. h bnomnal modl mo gnal than oon dtbuton modl. hfo all mathmatcal fomula fo valuaton of both pobablty mau th pobablty of dtcton and th pobablty of fal alam hould b dvd fo bnomnal dtbuton fo a Hough dtcto. In th pnt pap on tuaton fo a hghly fluctuatng tagt Swlng II typ tagt modl dtcton n condton of pul ammng tudd. h ffctvn of Hough dtcto wth CA CFAR o EXC CFAR poco n pul ammng fo valu of pobablty of dtcton D =.5 achd. h ffctvn of Hough dtcto wth th mthod fom [3].. th nblty towad pul ammng tmatd. h tmat allow th compaon of Hough dtcto towad ondmnonal CFAR poco and th compaon towad anoth pattn achd fom oth autho []. h pnt ult how that Hough dtcto ffctv n condton of dcad pul ammng.. Stattcal analy of Hough dtcto Ung Calon appoach [ 3] w obtan a nw ult fo dtcton pfomanc n Hough pac fo tagt modl of th typ Swlng II n condton of pul ammng dcbd wth th pobablty dnty functon (pdf) of th fnc wndow output [5]: () f x xp x xp wh th p pul avag gnal-to-no ato th avag pow of th cv no th avag ntfnc-to-no ato th pobablty fo th appaanc of pul ammng wth avag lngth n th ang cll. x 6 8

3 6 9 In condton of bnomal dtbuton of pul ntfnc th bacgound nvonmnt nclud th ntfnc-plu-no tuaton []. Conquntly th pobablty dnty functon (pdf) of th fnc wndow output may b dfnd by () x x x x f xp xp xp wh λ th avag pow of th cv no and /λ th p pul avag ntfnc-to-no ato (IR). h pobablty of dtcton fo CA CFAR poco fo tagt of ca Swlng II n pul ammng [7] (3) CA CA CA CA SW d C wh th gnal-to-no ato CA th thhold contant and th avag ntfnc-to-no ato (IR). h pobablty of fal alam fo a CA CFAR dtcto fo ca Swlng II n pul ammng [5] obtand fo valu of th pobablty of dtcton d =. h pobablty of tagt dtcton of an EXC CFAR dtcto valuatd by: (4) EXC V EXC V EXC V E E SW M M M C d wh M V (.) th momnt gnatng functon accodng to [] and EXC a pdtmnd cal facto that povd a contant fal alam at ( fa ) dsw th pobablty of pul dtcton of an EXC CFAR dtcto n th pnc of bnomnal dtbuton mpul ntfnc. h pobablty of fal alam of an EXC CFAR poco valuatd by (4) ttng =. All ndcaton fo gnal dtcton obtand fom ang oluton cll and can a aangd n a matx of z n t pac. In th pac tatonay o contant ada vlocty tagt pa a a taght ln whch cont of nonzo lmnt of. Lt u aum that nm a t of uch nonzo lmnt of that conttut a taght ln n t pac that ( ) nm. h ln may b pntd n Hough paamt pac a a pont (n m). Dnotng nm a th maxmal z of th cumulatv fal alam pobablty fo a cll wttn accodng to [3]: (5) nm nm K l l l nm nm l fa fa fa wh K a lna tactoy dtcton thhold.

4 h total fal alam pobablty n Hough paamt pac qual to on mnu th pobablty that no fal alam occud n any of th Hough cll. Fo ndpndnt Hough cll th pobablty max( nm ) nm W (6) fa fa nm K ( nm ) wh max nm th accbl Hough pac maxmum and nm of cll fom Hough paamt pac who valu a qual to W th numb nm. h cumulatv pobablty of tagt dtcton n Hough paamt pac D cannot b wttn n th fom of a mpl Bnoull um. A th tagt mov wth pct to th ada th SR of th cvd gnal chang dpndng on th dtanc to th tagt and th pobablty of a pul D () chang a wll. hn th pobablty D can by calculatd by Bunn mthod. By man of Bunn mthod [3] a matx of z th lmnt of whch a th pmtv pobablty of dtcton fom th -th tm lc fomd. Ung (3) (4) t pobl all th ( ) ndd to calculat D to b obtand. Fo can of ada th followng vald: (7) d ( S ) SW S D. M h a not many ca n pactc whn ada quppd wth a Hough dtcto wong n pul ammng. In uch tuaton t would b dabl to now th Hough lo dpndng on th paamt of th pul ammng fo atng th bhavo of th ada. Fo th calculaton of Hough dtcto lo ud th ato btwn th two valu of gnal-to-no-ato (SR) maud n db. h compaon a mad and towad Hough dtcto wth CA CFAR poco and Hough dtcto wth EXC CFAR poco n pul ammng. 3. umcal ult In od to analyz th qualty of th Hough dtcto w cond ada wth paamt mla to tho n []: th ach can tm 6 ; th ang oluton R = 3 n. m ( n. m = 85 m); th bam ang-tm pac ha 8 ang cll and tm lc. In th analy condd taght ln ncomng tagt wth a pd of Mach 3 and m ada co cton. In th analy th SR avag valu calculatd a S=K/R 4 wh K=.6 th gnalzd ngy paamt of th ada and R th dtanc to th tagt maud n nautcal ml. Calon appoach ung Bunn mthod fo calculatng th pobablty of dtcton n Hough paamt pac futh dvlopd n od to mantan contant fal alam pobablty at th output of th Hough dtcto. h utabl cal facto chon tatvly. h nflunc of th thhold contant on th qud gnalto-no ato tudd. h nvtgaton pfomd fo pobablty of dtcton ( D =.5) and dffnt valu of th pobablty fo th appaanc of pul ammng wth avag lngth n th cll n ang. 7

5 In od to achv a contant valu of th pobablty of fal alam ( fa ) th valu of th thhold contant whch guaant that a dtmnd fo dffnt numb of obvaton n th fnc wndow an avag ntfnc-to-no ato (IR) and a pobablty fo th appaanc of pul ammng wth avag lngth n th cll n ang. h poft (lo) of th CA Hough dtcto n pul ammng a dtmnd towad th CA CFAR dtcto followng th algothm popod n [3] fo pobablty of dtcton 5. In tabl a pntd ult fo avag dtcton thhold fo CA Hough 4 CFAR dtcto wth th pobablty of fal alam ( fa ) fo numb of obvaton n th fnc wndow ( 6 ) avag ntfnc-to-no ato (IR=3 db) and two dfnt valu fo a pobablty fo th appaanc of pul ammng wth avag lngth n th cll n ang. abl M CA fo = CA fo =. AD fo = AD fo = h autho n [3] u appoach popod by Baton to dtmn th thhold n Hough paamt pac. hy aum M =7 a optmal thhold n th bnay ntgaton and apply t n Hough paamt pac. In th pap aft tatv analy th optmal thhold n Hough paamt pac alo dtmnd to b M =7 fo th valu of th pobablty of appaanc of pul ammng wth avag lngth n th ang cll =. Dffnt valu of th dtcton thhold n Hough paamt pac M a hown on Fg.. h optmal valu fo th thhold M =7 of can ( M =7/) fo valu of th pobablty fo th appaanc of pul ammng wth avag lngth n th ang cll ε =. Fo ε =. th optmal valu fo dtcton thhold n Hough paamt pac M = 8 of can ( M =8/). h pobablt of dtcton of Hough dtcto wth a CA CFAR poco a hown on Fg. and Fg. 3 fo valu of th dtcton thhold M = and fo optmal valu of th dtcton thhold M = 7 fo = and fo M = 8 fo =.. h poft of ung a Hough dtcto wth CA CFAR poco calculatd fo th thhold valu M = and fo optmal valu of th dtcton thhold M =7 fo 7

6 = and M =8 fo =. compad to a CA CFAR poco fo th numb of tt oluton cll =6 and th valu fo pobablty of fal alam fa 4 a hown on Fg. 4. h CA Hough dtcto wth th optmal Hough ul M -out-of- qual to 7 of btt n ca of low valu of th pobablty fo appaanc of mpul ntfnc up to.6. Fo hgh valu of th pobablty fo appaanc of mpul ntfnc abov.6 th uag of th optmal Hough ul M -out-of- =8 of can ult n low lo. Fg.. Avag dtcton thhold of a CA Hough CFAR dtcto Fg.. obablty of dtcton of a Hough dtcto wth CA CFAR poco n pul ammng fo can M = M =7 and = Fg. 3. obablty of dtcton of a Hough dtcto wth CA CFAR poco n pul ammng fo can M = M =8 and =. Fg. 4. oft of a Hough dtcto (dahd ln) wth CA CFAR poco fo can M = and two optmal valu of th dtcton thhold M =7 fo = and M =8 fo =. compad to a CA CFAR dtcto (old ln) fo =6 A dtald pfomanc analy of Hough dtcto wth an EXC CFAR poco pntd n th pap. It bhavo ha bn tudd fo dffnt valu of th thhold contant and fo dffnt valu of th pobablty fo th appaanc of mpul ntfnc n Hough paamt pac. h xpmntal ult a obtand fo th followng nput paamt: avag pow of th cv no λ = avag 7

7 ntfnc-to-no ato (IR=3 db) pobablty fo appaanc of mpul ntfnc wth avag lngth n th ang cll fom. to.9 numb of fnc cll =6 (o 3) numb of tt cll L=6 pobablty of fal alam fa = 4 xcon thhold B E = numb of can = optmal valu of Hough dtcton thhold M =7 M =3 and bnay ul M-out-of-L=/6 M-out-of-L=6/6. In abl a pntd ult fo avag dtcton thhold fo EXC Hough CFAR dtcto wth pobablty of fal alam ( fa = 4 ) xcon contant B E = fo numb of obvaton n th fnc wndow ( 6 ) an avag ntfncto-no ato (IR=3 db) and two dfnt valu fo pobablty of appaanc of pul ammng wth avag lngth n th cll n ang. h avag dtcton thhold fo EXC Hough CFAR dtcto n condton of pul ammng and fo dffnt valu of th dtcton thhold n Hough paamt pac M hown on Fg. 5. h avag dtcton thhold fo Hough dtcto wth an EXC CFAR poco fo two dffnt valu of th numb of fnc wndow (=6 and =3) and fo th valu M = of th Hough dtcton thhold a hown on Fg. 6. h ncang of th fnc wndow numb lad to lo dmnhng. h pobablty of dtcton of th EXC Hough CFAR dtcto hown on Fg. 7 fo optmal valu of th dtcton thhold M =3 by valu fo pobablty of appaanc =.. On Fg. 8 hown th pobablty of dtcton of th EXC Hough CFAR dtcto fo two valu of th dtcton thhold M = and M =7 fo valu of pobablty of appaanc =.9. h AD of Hough dtcto wth an EXC CFAR poco fo th optmal valu of th dtcton thhold M =7 fo =.9 M =3 fo =. and fo th thhold valu M = a hown on Fg. 9. Fo compaon on Fg. th ult obtand fo th Hough dtcto wth th two typ of on-dmnonal CFAR poco a hown CA CFAR and EXC CFAR. abl M EXC fo =. EXC fo =.9 AD fo =. AD fo =

8 Fg. 5. Avag dtcton thhold of an EXC Hough CFAR dtcto fo two valu of th pobablty of appaanc Fg. 6. Avag dtcton thhold of an EXC Hough CFAR dtcto fo two valu of th numb of tt oluton cll Fg. 7. obablty of dtcton of a Hough Fg. 8. obablty of dtcton of a Hough dtcto wth EXC CFAR poco n pul dtcto wth EXC CFAR poco n pul ammng fo can M = M =3 and =. ammng fo can M = M =7 and =.9 Fg. 9. Avag dtcton thhold of an EXC Hough CFAR dtcto fo two optmal valu of dtcton thhold M =7 fo =.9 M =3 fo =. and fo thhold valu M = 7 4 Fg.. obablty of dtcton fo Hough dtcto wth two on-dmnonal CFAR poco

9 4. Concluon h xpmntal ult val th nflunc of th ntfnc on th dtcton poc whn havng contant fal alam at n pul ammng. A mthod fo lo tmaton whch allow choong optmal dtcto paamt dvlopd. h tmat of th ffctvn of a Hough dtcto (CA Hough CFAR o EXC Hough CFAR) n pul ammng a cvd fo dffnt tam chaacttc. Ung Matlab th avag dtcton thhold fo th two typ of Hough dtcto fo a hghly fluctuatng tagt Swlng II typ tagt modl dtcton n condton of pul ammng calculatd n accodanc wth th appoach pntd n [3]. Ung th appoach t vy ay to pcly dtmn th ngy bnft whn ung a gvn dtcto. h ult achvd how that Hough dtcto wth on-dmnonal poco ffctv n condton of dcang pul ammng. h pfomanc of a Hough dtcto dgnd fo non-homognou ntfnc tudd. h optmal thhold valu fo dffnt nput condton a tmatd. h valu of th tt oluton cll and th pobablty of fal alam ov th avag dtcton thhold a tudd. h ult how lo n th gnal to no ato of about 37 db fo th Hough dtcto wth EXC CFAR poco and 4 db fo th Hough dtcto wth CA CFAR poco wth pct to th Hough dtcto wth a fxd thhold []. Applcaton of cnong tchnqu n th dtcton algothm mpov th Hough dtcto ffctvn. h ult obtand n th pap could pactcally b ud n ada and communcaton ntwo. R f n c. C a l o n B. E. E v a n S. W l o n. Sach Rada Dtcton and ac wth th Hough anfom. at I. IEEE an. Vol. AES o -8.. C a l o n B. E. E v a n. S. W l o n. Sach Rada Dtcton and ac wth th Hough anfom. at II. IEEE an. Vol. AES o C a l o n B. E. E v a n S. W l o n. Sach Rada Dtcton and ac wth th Hough anfom. at III. IEEE an. Vol. AES o F n n H. M. R. S. J o h n o n. Adaptv Dtcton Mod wth hhold Contol a a Functon of Spatally Sampld Clutt Etmaton. RCA Rvw B h a V. CA CFAR ada gnal dtcton n pul ammng. Compt. Rnd. Acad. Bulg. Sc. Vol o K a b a c h v C h. L. D o u o v a I. G a v a n o v. Compaatv Analy of Lo of CA CFAR oco n ul Jammng Cybntc and Infomaton chnolog Vol K a b a c h v C h. L. D o u o v a I. G a v a n o v. Cll Avagng Contant Fal Alam Rat Dtcto wth Hough anfom n Randomly Avng Impul Intfnc. Cybntc and Infomaton chnolog Vol. 6 6 o G o l d m a n H. I. B a -D a v d. Analy and Applcaton of th Excon CFAR Dtcto. In: IEE oc. Vol. 35 t.f. (6) G o l d m a n H. fomanc of th Excon CFAR dtcto n th pnc of ntf. In: IEE oc. Vol. 37 t.f. (3) B h a V. C h. K a b a c h v. Excon CFAR Bnay Intgaton oco. Compt. Rnd. Acad. Bulg. Sc. Vol o /

10 . K a b a c h v C h. I. G a v a n o v L. D o u o v a. Excon CFAR BI Dtcto wth Hough anfom n nc of Randomly Avng Impul Intfnc. In: oc. of Intnatonal Rada Sympoum IRS 5 Bln Gmany D o u o v a L. Hough Dtcto wth On-dmnonal CFAR oco n Randomly Avng Impul Intfnc. In: oc. of Dtbutd Comput and Communcaton two Intnatonal Wohop Sofa Bulgaa R o h l n g H. Rada CFAR hholdng n Clutt and Multpl agt Stuaton. IEEE an. Vol. AES o

Constant False Alarm Rate Detectors in Intensive Noise Environment Conditions

Constant False Alarm Rate Detectors in Intensive Noise Environment Conditions 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

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

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

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

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

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

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

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

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

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

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

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

Diffraction. Diffraction: general Fresnel vs. Fraunhofer diffraction Several coherent oscillators Single-slit diffraction. Phys 322 Lecture 28

Diffraction. Diffraction: general Fresnel vs. Fraunhofer diffraction Several coherent oscillators Single-slit diffraction. Phys 322 Lecture 28 Chapt 10 Phys 3 Lctu 8 Dffacton Dffacton: gnal Fsnl vs. Faunhof dffacton Sval cohnt oscllatos Sngl-slt dffacton Dffacton Gmald, 1600s: dffacto, dvaton of lght fom lna popagaton Dffacton s a consqunc of

More information

Diffraction. Diffraction: general Fresnel vs. Fraunhofer diffraction Several coherent oscillators Single-slit diffraction. Phys 322 Lecture 28

Diffraction. Diffraction: general Fresnel vs. Fraunhofer diffraction Several coherent oscillators Single-slit diffraction. Phys 322 Lecture 28 Chapt 10 Phys 3 Lctu 8 Dffacton Dffacton: gnal Fsnl vs. Faunhof dffacton Sval cohnt oscllatos Sngl-slt dffacton Dffacton Gmald, 1600s: dffacto, dvaton of lght fom lna popagaton Dffacton s a consqunc of

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

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

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

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

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

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

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

(( ) ( ) ( ) ( ) ( 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

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

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

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

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

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

Chapter-10. Ab initio methods I (Hartree-Fock Methods)

Chapter-10. Ab initio methods I (Hartree-Fock Methods) Chapt- Ab nto mthods I (Hat-Fock Mthods) Ky wods: Ab nto mthods, quantum chmsty, Schodng quaton, atomc obtals, wll bhavd functons, poduct wavfunctons, dtmnantal wavfunctons, Hat mthod, Hat Fock Mthod,

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

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

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

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

Solutions to Supplementary Problems

Solutions to Supplementary Problems Solution to Supplmntay Poblm Chapt Solution. Fomula (.4): g d G + g : E ping th void atio: G d 2.7 9.8 0.56 (56%) 7 mg Fomula (.6): S Fomula (.40): g d E ping at contnt: S m G 0.56 0.5 0. (%) 2.7 + m E

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

Evaluation of Back-EMF Estimators for Sensorless Control of Permanent Magnet Synchronous Motors

Evaluation of Back-EMF Estimators for Sensorless Control of Permanent Magnet Synchronous Motors Ealuaton of Back-EMF Etmato fo Snol Contol of JPE -4- http://x.o.og/.63/jpe...4. Ealuaton of Back-EMF Etmato fo Snol Contol of Pmannt Magnt Synchonou Moto Kwang-Woon an Jung-Ik Ha Dpt. of Elctonc Eng.,

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

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

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

The Fourier Transform

The Fourier Transform /9/ Th ourr Transform Jan Baptst Josph ourr 768-83 Effcnt Data Rprsntaton Data can b rprsntd n many ways. Advantag usng an approprat rprsntaton. Eampls: osy ponts along a ln Color spac rd/grn/blu v.s.

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

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

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

Signal Circuit and Transistor Small-Signal Model

Signal Circuit and Transistor Small-Signal Model Snal cut an anto Sall-Snal Mol Lctu not: Sc. 5 Sa & Sth 6 th E: Sc. 5.5 & 6.7 Sa & Sth 5 th E: Sc. 4.6 & 5.6 F. Najaba EE65 Wnt 0 anto pl lopnt Ba & Snal Ba Snal only Ba Snal - Ba? MOS... : : S... MOS...

More information

Additional File 1 - Detailed explanation of the expression level CPD

Additional File 1 - Detailed explanation of the expression level CPD Addtonal Fle - Detaled explanaton of the expreon level CPD A mentoned n the man text, the man CPD for the uterng model cont of two ndvdual factor: P( level gen P( level gen P ( level gen 2 (.).. CPD factor

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

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

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

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

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

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

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

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

Algorithmic Superactivation of Asymptotic Quantum Capacity of Zero-Capacity Quantum Channels

Algorithmic Superactivation of Asymptotic Quantum Capacity of Zero-Capacity Quantum Channels Algothmc Supactvaton of Asymptotc Quantum Capacty of Zo-Capacty Quantum Channls Laszlo Gyongyos, Sando Im Dpatmnt of Tlcommuncatons Budapst Unvsty of Tchnology and Economcs - Budapst, Magya tudoso t, ungay

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

Partial Fraction Expansion

Partial Fraction Expansion Paial Facion Expanion Whn ying o find h inv Laplac anfom o inv z anfom i i hlpfl o b abl o bak a complicad aio of wo polynomial ino fom ha a on h Laplac Tanfom o z anfom abl. W will illa h ing Laplac anfom.

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

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

ESCI 341 Atmospheric Thermodynamics Lesson 16 Pseudoadiabatic Processes Dr. DeCaria

ESCI 341 Atmospheric Thermodynamics Lesson 16 Pseudoadiabatic Processes Dr. DeCaria ESCI 34 Atmohi hmoynami on 6 Puoaiabati Po D DCaia fn: Man, A an FE obitaill, 97: A omaion of th uialnt otntial tmatu an th tati ngy, J Atmo Si, 7, 37-39 Btt, AK, 974: Futh ommnt on A omaion of th uialnt

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

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

Q Q N, V, e, Quantum Statistics for Ideal Gas and Black Body Radiation. The Canonical Ensemble

Q Q N, V, e, Quantum Statistics for Ideal Gas and Black Body Radiation. The Canonical Ensemble Quantum Statistics fo Idal Gas and Black Body Radiation Physics 436 Lctu #0 Th Canonical Ensmbl Ei Q Q N V p i 1 Q E i i Bos-Einstin Statistics Paticls with intg valu of spin... qi... q j...... q j...

More information

GUIDE FOR SUPERVISORS 1. This event runs most efficiently with two to four extra volunteers to help proctor students and grade the student

GUIDE FOR SUPERVISORS 1. This event runs most efficiently with two to four extra volunteers to help proctor students and grade the student GUIDE FOR SUPERVISORS 1. This vn uns mos fficinly wih wo o fou xa voluns o hlp poco sudns and gad h sudn scoshs. 2. EVENT PARAMETERS: Th vn supviso will povid scoshs. You will nd o bing a im, pns and pncils

More information

Study on the Classification and Stability of Industry-University- Research Symbiosis Phenomenon: Based on the Logistic Model

Study on the Classification and Stability of Industry-University- Research Symbiosis Phenomenon: Based on the Logistic Model Jounal of Emging Tnds in Economics and Managmnt Scincs (JETEMS 3 (1: 116-1 Scholalink sach Institut Jounals, 1 (ISS: 141-74 Jounal jtms.scholalinksach.og of Emging Tnds Economics and Managmnt Scincs (JETEMS

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

Chapter 3 Binary Image Analysis. Comunicação Visual Interactiva

Chapter 3 Binary Image Analysis. Comunicação Visual Interactiva Chapt 3 Bnay Iag Analyss Counação Vsual Intatva Most oon nghbohoods Pxls and Nghbohoods Nghbohood Vznhança N 4 Nghbohood N 8 Us of ass Exapl: ogn nput output CVI - Bnay Iag Analyss Exapl 0 0 0 0 0 output

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

Fourier transforms (Chapter 15) Fourier integrals are generalizations of Fourier series. The series representation

Fourier transforms (Chapter 15) Fourier integrals are generalizations of Fourier series. The series representation Pof. D. I. Nass Phys57 (T-3) Sptmb 8, 03 Foui_Tansf_phys57_T3 Foui tansfoms (Chapt 5) Foui intgals a gnalizations of Foui sis. Th sis psntation a0 nπx nπx f ( x) = + [ an cos + bn sin ] n = of a function

More information

Analysis and control of dual stator winding induction motor

Analysis and control of dual stator winding induction motor ARCHIVES OF EECRICA ENGINEERING VO. 61(3), pp. 41-438 (01) DOI 10.478/v10171-01-0033-z Analy and contol of dual tato wndng nducton oto KRZYSZOF PIEŃKOWSKI Inttut of Elctcal Machn, Dv and Maunt Woclaw Unvty

More information

Queuing Network Approximation Technique for Evaluating Performance of Computer Systems with Input to Terminals

Queuing Network Approximation Technique for Evaluating Performance of Computer Systems with Input to Terminals 6th Intenatonal Confeence on Chemcal Agcultual Envonmental and Bologcal cence CAEB-7 Dec. 7-8 07 Pa Fance ueung Netwo Appoxmaton Technque fo Evaluatng Pefomance of Compute ytem wth Input to Temnal Ha Yoh

More information

A Velocity Extraction Method in Molecular Dynamic Simulation of Low Speed Nanoscale Flows

A Velocity Extraction Method in Molecular Dynamic Simulation of Low Speed Nanoscale Flows Int. J. Mol. Sc. 006, 7, 405-416 Intnatonal Jounal of Molcula Scncs ISSN 14-0067 006 by MDPI www.mdp.og/ms/ A Vlocty Extacton Mthod n Molcula Dynamc Smulaton of Low Spd Nanoscal Flows Wnf Zhang School

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

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

SYMMETRICAL COMPONENTS

SYMMETRICAL COMPONENTS SYMMETRCA COMPONENTS Syl oponn llow ph un of volg n un o pl y h p ln yl oponn Con h ph ln oponn wh Engy Convon o 4 o o wh o, 4 o, 6 o Engy Convon SYMMETRCA COMPONENTS Dfn h opo wh o Th o of pho : pov ph

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

What Makes Production System Design Hard?

What Makes Production System Design Hard? What Maks Poduction Systm Dsign Had? 1. Things not always wh you want thm whn you want thm wh tanspot and location logistics whn invntoy schduling and poduction planning 2. Rsoucs a lumpy minimum ffctiv

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

University of Toledo REU Program Summer 2002

University of Toledo REU Program Summer 2002 Univiy of Toldo REU Pogam Summ 2002 Th Effc of Shadowing in 2-D Polycyallin Gowh Jff Du Advio: D. Jacqu Ama Dpamn of Phyic, Univiy of Toldo, Toldo, Ohio Abac Th ffc of hadowing in 2-D hin film gowh w udid

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

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

Network Connectivity Probability of Linear Vehicular Ad-Hoc Networks on Two-Way Street

Network Connectivity Probability of Linear Vehicular Ad-Hoc Networks on Two-Way Street Communcatons and Ntwok,, 4, 33-34 http://dx.do.og/.436/cn..4438 ublshd Onln Novmb (http://www.scr.og/jounal/cn) Ntwok Connctvty obablty of Lna Vhcula Ad-Hoc Ntwoks on Two-Way Stt. C. Nlakantan, A. V. Babu

More information

MOS transistors (in subthreshold)

MOS transistors (in subthreshold) MOS tanito (in ubthhold) Hitoy o th Tanito Th tm tanito i a gnic nam o a olid-tat dvic with 3 o mo tminal. Th ild-ct tanito tuctu wa it dcibd in a patnt by J. Lilinld in th 193! t took about 4 ya bo MOS

More information

Auctions for Infrastructure Concessions with Demand Uncertainty and Unknown Costs

Auctions for Infrastructure Concessions with Demand Uncertainty and Unknown Costs MRA Munch sonal REc Achv Auctons fo nfastuctu oncssons wth Dmand Unctanty and Unknown osts Gustavo ombla and Gns d Rus Economcs of nfastuctu and anspot, Unvsty of Las almas 00 Onln at http://mpa.ub.un-munchn.d/03/

More information

multipath channel Li Wei, Youyun Xu, Yueming Cai and Xin Xu

multipath channel Li Wei, Youyun Xu, Yueming Cai and Xin Xu Robust quncy ost stmato o OFDM ov ast vayng multpath channl L W, Youyun Xu, Yumng Ca and Xn Xu Ths pap psnts a obust ca quncy ost(cfo stmaton algothm sutabl o ast vayng multpath channls. Th poposd algothm

More information

CHAPTER 4 TWO-COMMODITY CONTINUOUS REVIEW INVENTORY SYSTEM WITH BULK DEMAND FOR ONE COMMODITY

CHAPTER 4 TWO-COMMODITY CONTINUOUS REVIEW INVENTORY SYSTEM WITH BULK DEMAND FOR ONE COMMODITY Unvety of Petoa etd Van choo C de Wet 6 CHAPTER 4 TWO-COMMODITY CONTINUOU REVIEW INVENTORY YTEM WITH BULK DEMAND FOR ONE COMMODITY A modfed veon of th chapte ha been accepted n Aa-Pacfc Jounal of Opeatonal

More information

Integration of Predictive Display and Aircraft Flight Control System

Integration of Predictive Display and Aircraft Flight Control System ATE Wb of onfrnc 99, 03005 (07 DOI: 005/ matcconf/079903005 TAI06 Intgraton of Prdctv Dplay and Arcraft Flght ontrol Sytm AV Efrmov, *, S Tjaglk, IH Irgalv and VG Tpnko ocow Avaton Inttut, Aronautcal chool,

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

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

ELG3336: Op Amp-based Active Filters

ELG3336: Op Amp-based Active Filters ELG6: Op Amp-baed Actve Flter Advantage: educed ze and weght, and thereore paratc. Increaed relablty and mproved perormance. Smpler degn than or pave lter and can realze a wder range o uncton a well a

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

Root Locus Techniques

Root Locus Techniques Root Locu Technque ELEC 32 Cloed-Loop Control The control nput u t ynthezed baed on the a pror knowledge of the ytem plant, the reference nput r t, and the error gnal, e t The control ytem meaure the output,

More information

ON A GENERALIZED PROBABILITY DISTRIBUTION IN ASSOCIATION WITH ALEPH ( ) - FUNCTION

ON A GENERALIZED PROBABILITY DISTRIBUTION IN ASSOCIATION WITH ALEPH ( ) - FUNCTION Intnational Jounal of Engining, Scinc and athmatic Vol. 8, Iu, Januay 8, ISSN: 3-94 Impact Facto: 6.765 Jounal Hompag: http://www.ijm.co.in, Email: ijmj@gmail.com Doubl-Blind P Riwd Rfd Opn Acc Intnational

More information

MODELING AND CONTROL OF DOUBLY FED INDUCTION GENERATOR FOR WIND POWER

MODELING AND CONTROL OF DOUBLY FED INDUCTION GENERATOR FOR WIND POWER MODEING AND CONTRO O DOUBY ED INDUCTION GENERATOR OR WIND POWER Tak Mdall Maaud 1, Studnt M, IEEE and P.K. Sn, llow IEEE Coloado School of Mn, Don of Engnng, Goldn, Coloado 841 Atact- Wth ncad pntaton

More information

Elasticity 1. 10th April c 2003, Michael Marder

Elasticity 1. 10th April c 2003, Michael Marder Elasticity 0th Apil 003 c 003, Michal Mad Gnal Thoy of Lina Elasticity Bfo dfomation Aft dfomation Many ways to div lasticity. Cold div fom thoy of atoms and thi intactions. Howv, this appoach is not histoically

More information

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari snbrg Modl Sad Mohammad Mahd Sadrnhaad Survsor: Prof. bdollah Langar bstract: n ths rsarch w tr to calculat analtcall gnvalus and gnvctors of fnt chan wth ½-sn artcls snbrg modl. W drov gnfuctons for closd

More information

Solving the Dirac Equation: Using Fourier Transform

Solving the Dirac Equation: Using Fourier Transform McNa Schola Reeach Jounal Volume Atcle Solvng the ac quaton: Ung oue Tanfom Vncent P. Bell mby-rddle Aeonautcal Unvety, Vncent.Bell@my.eau.edu ollow th and addtonal wok at: http://common.eau.edu/na Recommended

More information

PF nce. Conferen. is, FRANC. ectronics Pari. ber 6-10, 2. ustrial Ele. Novemb. EEE Indu

PF nce. Conferen. is, FRANC. ectronics Pari. ber 6-10, 2. ustrial Ele. Novemb. EEE Indu Confn nc s, FRANC CE ctoncs 006 Pa ustal El b 6-0, EEE Indu Nomb 3 nd I Spd and Poston Estmaton fo PM Synchonous Moto usng Slf-Compnsatd t d Back-EMF k Obss Maco TURSINI, Robto PETRELLA, Alssa SCAFATI

More information

(( )( )) = = S p S p = S p p m ( )

(( )( )) = = S p S p = S p p m ( ) 36 Chapt 3. Rnoalization Toolit Poof of th oiginal Wad idntity o w nd O p Σ i β = idβ γ is p γ d p p π π π p p S p = id i d = id i S p S p d π β γ γ γ i β i β β γ γ β γ γ γ p = id is p is p d = Λ p, p.

More information

Robust Observer-based Controller Design for T-S Systems with Nonlinear Consequent Parts

Robust Observer-based Controller Design for T-S Systems with Nonlinear Consequent Parts Robu Obv-bad Conoll Dgn fo -S Sym wh Nonlna Conqun Pa Hoda Mood, Mohammad Faokh Dpamn of Elccal Engnng, Ian Unvy of Scnc and chnology, han 686-3, Ian, -mal: {mood, faokh} @ u.ac. Abac: h pap cond h dgn

More information

A Note on Estimability in Linear Models

A Note on Estimability in Linear Models Intrnatonal Journal of Statstcs and Applcatons 2014, 4(4): 212-216 DOI: 10.5923/j.statstcs.20140404.06 A Not on Estmablty n Lnar Modls S. O. Adymo 1,*, F. N. Nwob 2 1 Dpartmnt of Mathmatcs and Statstcs,

More information

Unsupervised Image Segmentation Method based on Finite Generalized Gaussian Distribution with EM & K-Means Algorithm

Unsupervised Image Segmentation Method based on Finite Generalized Gaussian Distribution with EM & K-Means Algorithm IJCSS Intrnatonal Journal of Computr Scnc and twork Scurty, VOL.7 o.4, Aprl 2007 37 Unuprvd Imag Sgmntaton bad on Fnt Gnralzd Gauan Dtrbuton wth EM & -Man Algorthm raad Rddy.V.G.D, Srnva Rao. 2, Srnva

More information