Theory of Low Frequency Instabilities Near Transport Barriers

Size: px
Start display at page:

Download "Theory of Low Frequency Instabilities Near Transport Barriers"

Transcription

1 A. L. Roger Theory of Low Frequecy Ible er Trpor Brrer Iu für Plmphyk Forchugzerum Jülch GmbH EURATOM Aoco Trlerl Eurego Cluer D-545 Jülch Germy fz-juelch.de Abrc: The heory of low frequecy ble xymmerc orodl plm preeed from he po of vew of he wo-flud equo umg he drd drf wve orderg. Aeo focued o he lm whch eghborg rol urfce re uffcely fr pr h mode overlppg o-exe. Owg o feld le bedg polodl de-bd m±1... coex wh he prmry mode m ehcg ocebly he role of he prllel o dymc. The elecro d o brche re veged ccurely uder hoe codo. I foud h he rdl wdh of he egemode cree wh repec o he lb vlue; he her dmpg re of he elecro brch repecvely he growh re of he o brch cree correpodgly. Oher ereg reul re obed cocerg he frequecy he growh re d he polodl vro of he mplude of he o mode flucuo. Thoe expl he org of erl rpor brrer; hey lo ugge wy of erpreg flucuo ymmere oberved okmk d (whe collo re cluded he Rdve Improved cofeme mode. 1. Iroduco We hve derved he frmework of he wo-flud heory wo-dmeol prl dfferel equo whch decrbe he dymc of low frequecy mcro-ble eloged log he mgec feld le; our dervo free of umpo regrdg he blloog chrcer of he mode d he re eor; o collo hve furhermore bee ke yemclly o ccou. The wo-flud heory rcve becue of mmede phycl coe bu fl o clude wve-prcle reo erco d he rpped prcle repoe; hoe c be ke o ccou v kec exeo oce he chrcerc rge bly prmeer hve bee defed by he wo-flud reul. I okmk crucl prmeer he D decrpo of low frequecy ble he ro of he rdl wdh (w of eghborg egemode (wh decl orodl mode umber o he dce ( bewee he rol urfce bou whch hey re repecvely loclzed. Srog overlp occur f w/»1; h ce ew e of egefuco my be bul from ler combo of he oled egemode propoed by Tylor [1]. Polodl couplg whch prmrly occur hrough he mgec feld rdl d polodl grde ply decve role he ler bly propere: mgec her dmpg of elecro drf wve for exmple uppreed for proper phg of he oled egemode. The homogeey of he mgec feld ply lo mpor role he oppoe lm w/ «1 he prllel mode umber of he de-bd (qr lrger h h of he prmry mode; reul he role of he prllel o dymc ocebly ehced d he rdl wdh d complex frequecy re lered gfcly. We cocere here our effor o h lmg ce whch prculrly ppropre o erl rpor brrer oced wh wek mgec her. For he purpoe of he lycl heory he prmeer ε ŝ / q wll be umed mll (ε L /R he ro of he dey legh-cle o he mjor rdu.

2 Our m heorecl reul re follow. The frequecy of he o brch (meured he ExB rog frme ω'ω ω ExB mll compred o he o dmgec frequecy ( ω d h he oppoe g [Eq.(]. The growh re proporol o he bolue vlue of he mgec her ŝ [Eq.(]. The ormlzed dey flucuo mll compred o he ormlzed o emperure flucuo d exhb mpor polodl vro [Eq.(7]. The frequecy d he rdl ocllo d decy legh re lrger he cul orodl geomery h he lb model [Eq.( (1 (1b d (4]; he growh re re decl [Eq.(]. Io collo c blze he o brch epeclly hgh mode umber [Eq.(8] bu hve eglgble effec o he elecro brch. The elecro brch frequecy ω' bou ω e bu dperve effec re ehced by he geomery [Eq.(11]. The rdl ocllo cle of he egemode d her dmpg re (he ler proporol o ŝ re lrger he oru h he lb by frcol power of (1+q [Eq.(1 d (1; he ler reul oppoe o h obed he rog overlp lm [1]; cully he bllog formlm co grp he orodl effec obed here becue of rercve umpo]. The expermel relevce of hoe reul dcued Seco 5.. Mehodology The coveol drf wve orderg defed by ω k ~1 k qr ~1 (1 ~ ω j j / Ω ~ / L ~ µ «1 ω (1b umed ogeher wh c / c e ~ (m e / m ~ µ (1c (j he pece dex c /Ω c d Ω re he o Lrmor rdu herml velocy d gyrofrequecy repecvely. Wh h frmework he bulk ( oppoo o rpped o codered here elecro behve dbclly ( ω<<c e /qr.e. e d e eφ. e Te ( We coder flucuo of he form [] ( χ ϕ χ ˆ ( χ; exp ϕ ν( χ' dχ' ( ( where χ d ϕ re he drd flux polodl d orodl coorde [] ν χ (dϕ / dχ JB / R (4 ( B ϕ he pch gle of he feld le J he Jcob of he rformo r (Ψ χ ϕ re he orodl d referece polodl mode umber [~µ -1 ccordg o (1 d (1b]. The rol mgec urfce re defed by q( ν( χdχ / π m /. (4b The fuco ˆ ( χ; decrbe he rdl rucure of he mode he eghbourhood of he rol urfce d owg o he homogeee of he equlbrum redul polodl d rdl vro; he former ply herefer mpor role. The repreeo ( compble wh he perodcy d he log prllel wvelegh requreme []. The ummo my be dropped here ce ˆ ( χ; ˆ ( ± 1 χ; ± 1 w/ <<1. D equo re he obed for he o dey emperure d prllel flow velocy.

3 I he followg we coder lrge pec ro okmk wh crculr cro-eco; replcg χ by he uul polodl gle we hve BB (1-ε co where εr/r r he mor rdu of he eed or d correpod o he ouer equorl ple. The o mgec drf frequecy operor c be wre ωb (T / er Bϕ [(m / rco+ r r ] + O( ε m (5 where ν ( χ ν( χ (r r rq(r + O( ε (6 The redul polodl depedece of ˆ û d ˆ decrbed by Fourer ere e.g. [ ˆ (r r ] ˆ p (r r pe (7 P χ + [ ν( χ ν( χ led o he lgebrc (p + ŝ k x where ŝ r d r l q k m/r d x r r ; we oe h o h he prllel dfferel operor ] expreo ŝ k x << 1; he dex p lbel he de-bd. Aumg ε / q << 1 he fe yem of ordry dfferel equo c be ruced o p d p±1. Flly he rge of polodl mode umber for whch orodl d lb erm compee h bee defed order h he mo complee equo re obed (mxmum complexy orderg.. Reul for he elecro drf brch The elecro drf brch chrcerzed by ω ~ ω d «1 where ( x +k he ormlzed Lplc. The rdl egevlue equo [ τe (1 + q τe (1 + τe + η ( ω' ωe / ωe + ( ε x / q ]( o (8 where η L /L T τ e T e /T d τ e. Equo (8 lredy obed [4] dffer from he lb equo [5] by he (eoclcl fcor (1+q. The oluo re ( ˆ H (K 1 / x / exp( K x / (9 wh / K (1 + q ε ŝ / q g ωe (1 d Rω ' [1 (1 + q k (1 + τe + η τe ] ωe ; (11 ' ( 1(1 q I ω γ + + (1 + τe + η τe k ŝ c / q R (1 (The H re Herme polyoml.dmpg of elecro drf wve by rg o hered mgec feld coequece of he wve eergy beg rded wy from he rol urfce; Eq.(1 how her dmpg lrger orodl plm h predced by he lb model. The cle of he rdl ocllo lo lrger: / 4 / w K (1 + q ε ŝ / q. (1 The rge of polodl mode umber over whch boh codo of eglgble overlp d eglgble wve-prcle reo erco re fulflled gve by / τe q ε < k < (1 + q q ε / ŝ ; (14 compbly requre h / ε ŝ / q «τe (1 + q (15 The ro of he mplude of he de-bd ( ˆ d ( ˆ o he p compoe of order (ε ŝ / q f k he rge (14. We oe flly h ( η ( (16

4 4. Reul for he o drf brch The o drf brch chrcerzed by ω «ω d «1. The rdl egevlue 1 ω' ε ŝ ω D + (x / (x / (ˆ (17 ( / η q ω'.ν ω where D (1 + τe [ ε /(1.5η k ] ν / (1.5η ω (17b [We oe h lo he lb (D1 Eq.(17 dffer from he equo obed by Copp e l. [6] who fled o ke fe Lrmor rdu correco o he perpedculr compoe of he flucuo velocy yemclly o ccou; he ler re eel he o eergy equo. The effec of collo wll be egleced fr. The oluo of Eq.(17 re he (ˆ H (K x / exp( K x / (18 where K y roo of D K [ k + (1 + K ] [( / η ] ( ε ŝ / q (19 fyg Re K >; he complex egevlue ω re gve by ω' / ω [( / η ]D [ k + (1 + K ]; ( here D gve by Eq.(17b wh ν. 4.1 The Smll Mgec Sher Lm If ŝ<<1 he codo of eglgble overlp c be fed eher whe k < Κ or whe k > K.Oe c how h uder o crcumce wve-prcle reo erco ( (1 eglgble he former ce. I he ler Eq.(19 yeld K K + K wh ( K ( / ± η ε ŝ / q k D (1 (1 ( K (1 + (K / k. (1b R e K herefore pove correpodg o bouded egemode (η >/ requred for bouded uble oluo. Furher he growh / he dmpg re of he mode re γ ( g (1 ( / # ω + η ŝ c / q R ( where her gulr frequecy Re ω ' ( η / D k ω. ( R e ω' d ω hve oppoe g. The chrcerc rdl ocllory cle of o overlppg orodl egemode ( 4 w K ( / η q k D / ε ŝ (4 g lrger h he correpodg lb model (fcor D. Oe c how h he rge of polodl mode umber over whch boh codo of eglgble overlp d eglgble wve prcle reo erco re fulflled gve by [ ( / ] q D k [ ( / ] η ε < < η ε / q ; (5 compbly requre h ŝ < [ η ( / ]. (6 The orodl egemode re gve by ere mlr o Eq.(7. Of prculr ere he expreo of he dey flucuo: ˆ (x ( τ ω (ŝ k x ( ω / ω' + (5 / [ η ( / ] ω ( ˆ (7 { B} e

5 where ω c /qr d he operor ω B defed (5; he mplude of he dey de-bd ( ˆ re ypclly lrger h he mplude of he m compoe / ( ˆ by ( ε ŝ / q where ( ˆ /(ˆ ~ ( ε ŝ / q ; moreover he ro ( ˆ /(ˆ of order (ε / ŝ / q. 4. The Role of Collo I he lm k > Κ o collo ed o blze he o brch he re Im ω ' γ (4 / k ν ; (8 5. Summry d Expermel Relevce 5.1 Ierl Trpor Brrer The growh re of he o drf mode [Eq.(] proporol o he bolue vlue of he mgec her prmeer. Th reul brg mple explo o he formo of erl rpor brrer wh mmum q profle. The umpo of wek overlp prculrly ppropre here ( corro he oppoe lm codered mo oher work o vld. Sce he growh re furhermore depede of k Ldu dmpg (o codered here expeced o uppre he bly log wvelegh. 5. Rdve Improved Mode A he oher ed of he pecrum.e. for fe k vlue o collo my blze he yem f ν lrge eough Eq.(8 how. Shrkg of he bly rge owg o boh Ldu d collol dmpg my expl he reduco of coducve/covecve omlou rpor he edge of he hgh dey Rdve Improved cofeme mode dchrge (he bove ly requrg boh ŝ «1 d eglgble mode overlp however o drecly pplcble. 5. Aymmery of he flucuo The mplude of he o drf mode dey flucuo re chrcerzed by mpor polodl ymmere cf. Eq.(7. Uder he bove umpo ( K < k d low her wo mxm re er he equorl ple repecvely o he low d o he hgh feld de. Thoe reul re relev o obervo he core of TEXT-U. The o emperure flucuo re lrger h he dey flucuo d oly wekly depede. Referece [1] TAYLOR J.B. Plm Phyc d Corolled ucler Fuo Reerch 1976 (Proc. 6 h I. Cof. Berechgde 1976 IAEA Ve (1977. [] ROGISTER A. Tr. Fuo Tech. 9 ( (Proc. d Crolu Mgu Summer School o Plm Phyc [] MERCIER C. ucl. Fuo 1 ( [4] ROGISTER A. Phy. Plm ( [5] PEARLSTEI L.D. BERK H.L. Phy. Rev. Le. (1969. [6] COPPI B. ROSEBLUTH M.. SAGDEEV R.Z. Phy. Flud 1 (

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as.

Laplace Transform. Definition of Laplace Transform: f(t) that satisfies The Laplace transform of f(t) is defined as. Lplce Trfor The Lplce Trfor oe of he hecl ool for olvg ordry ler dfferel equo. - The hoogeeou equo d he prculr Iegrl re olved oe opero. - The Lplce rfor cover he ODE o lgerc eq. σ j ple do. I he pole o

More information

Isotropic Non-Heisenberg Magnet for Spin S=1

Isotropic Non-Heisenberg Magnet for Spin S=1 Ierol Jourl of Physcs d Applcos. IN 974- Volume, Number (, pp. 7-4 Ierol Reserch Publco House hp://www.rphouse.com Isoropc No-Heseberg Mge for p = Y. Yousef d Kh. Kh. Mumov.U. Umrov Physcl-Techcl Isue

More information

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X ECON 37: Ecoomercs Hypohess Tesg Iervl Esmo Wh we hve doe so fr s o udersd how we c ob esmors of ecoomcs reloshp we wsh o sudy. The queso s how comforble re we wh our esmors? We frs exme how o produce

More information

BEST PATTERN OF MULTIPLE LINEAR REGRESSION

BEST PATTERN OF MULTIPLE LINEAR REGRESSION ERI COADA GERMAY GEERAL M.R. SEFAIK AIR FORCE ACADEMY ARMED FORCES ACADEMY ROMAIA SLOVAK REPUBLIC IERAIOAL COFERECE of SCIEIFIC PAPER AFASES Brov 6-8 M BES PAER OF MULIPLE LIEAR REGRESSIO Corel GABER PEROLEUM-GAS

More information

Modification of raised cosine weighting functions family

Modification of raised cosine weighting functions family Compuol Mehod d Expermel Meureme XIV 9 Modfco of red coe eghg fuco fmly C. Lek,. Klec & J. Perk Deprme of Elecroc, Mlry Uvery of echology, Pold brc Modfco of he ko fmly of red coe eghg fuco h he poer of

More information

Calculation of Effective Resonance Integrals

Calculation of Effective Resonance Integrals Clculo of ffecve Resoce egrls S.B. Borzkov FLNP JNR Du Russ Clculo of e effecve oce egrl wc cludes e rel eerg deedece of euro flux des d correco o e euro cure e smle s eeded for ccure flux deermo d euro

More information

STOCHASTIC CALCULUS I STOCHASTIC DIFFERENTIAL EQUATION

STOCHASTIC CALCULUS I STOCHASTIC DIFFERENTIAL EQUATION The Bk of Thld Fcl Isuos Polcy Group Que Models & Fcl Egeerg Tem Fcl Mhemcs Foudo Noe 8 STOCHASTIC CALCULUS I STOCHASTIC DIFFERENTIAL EQUATION. ก Through he use of ordry d/or prl deres, ODE/PDE c rele

More information

The Signal, Variable System, and Transformation: A Personal Perspective

The Signal, Variable System, and Transformation: A Personal Perspective The Sgal Varable Syem ad Traformao: A Peroal Perpecve Sherv Erfa 35 Eex Hall Faculy of Egeerg Oule Of he Talk Iroduco Mahemacal Repreeao of yem Operaor Calculu Traformao Obervao O Laplace Traform SSB A

More information

4. Runge-Kutta Formula For Differential Equations

4. Runge-Kutta Formula For Differential Equations NCTU Deprme o Elecrcl d Compuer Egeerg 5 Sprg Course by Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos To solve e derel equos umerclly e mos useul ormul s clled Ruge-Ku ormul

More information

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula NCTU Deprme o Elecrcl d Compuer Egeerg Seor Course By Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos A. Euler Formul B. Ruge-Ku Formul C. A Emple or Four-Order Ruge-Ku Formul

More information

Chapter3 Pattern Association & Associative Memory

Chapter3 Pattern Association & Associative Memory Cher3 Per Aoco & Aocve Memor Aocg er hch re mlr, corr, cloe roxm l, cloe ucceo emorl Aocve recll evoe oced er recll er b r of evoe/recll h comlee/ o er To e of oco. For o er d heero-oco! : relg o dffere

More information

The Lucas congruence for Stirling numbers of the second kind

The Lucas congruence for Stirling numbers of the second kind ACTA ARITHMETICA XCIV 2 The Luc cogruece for Srlg umber of he ecod kd by Robero Sáchez-Peregro Pdov Iroduco The umber roduced by Srlg 7 h Mehodu dfferel [], ubequely clled Srlg umber of he fr d ecod kd,

More information

Numerical Methods using the Successive Approximations for the Solution of a Fredholm Integral Equation

Numerical Methods using the Successive Approximations for the Solution of a Fredholm Integral Equation ece Advce Appled d eorecl ec uercl eod u e Succeve Approo or e Soluo o Fredol Ierl Equo AIA OBIŢOIU epre o ec d opuer Scece Uvery o Peroş Uvery Sree 6 Peroş OAIA rdorou@yoo.co Arc: pper pree wo eod or

More information

Midterm Exam. Tuesday, September hour, 15 minutes

Midterm Exam. Tuesday, September hour, 15 minutes Ecoomcs of Growh, ECON560 Sa Fracsco Sae Uvers Mchael Bar Fall 203 Mderm Exam Tuesda, Sepember 24 hour, 5 mues Name: Isrucos. Ths s closed boo, closed oes exam. 2. No calculaors of a d are allowed. 3.

More information

Partial Molar Properties of solutions

Partial Molar Properties of solutions Paral Molar Properes of soluos A soluo s a homogeeous mxure; ha s, a soluo s a oephase sysem wh more ha oe compoe. A homogeeous mxures of wo or more compoes he gas, lqud or sold phase The properes of a

More information

Unscented Transformation Unscented Kalman Filter

Unscented Transformation Unscented Kalman Filter Usceed rsformo Usceed Klm Fler Usceed rcle Fler Flerg roblem Geerl roblem Seme where s he se d s he observo Flerg s he problem of sequell esmg he ses (prmeers or hdde vrbles) of ssem s se of observos become

More information

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall 8. Queueg sysems lec8. S-38.45 - Iroduco o Teleraffc Theory - Fall 8. Queueg sysems Coes Refresher: Smle eleraffc model M/M/ server wag laces M/M/ servers wag laces 8. Queueg sysems Smle eleraffc model

More information

Integral Equations and their Relationship to Differential Equations with Initial Conditions

Integral Equations and their Relationship to Differential Equations with Initial Conditions Scece Refleco SR Vol 6 wwwscecereflecocom Geerl Leers Mhemcs GLM 6 3-3 Geerl Leers Mhemcs GLM Wese: hp://wwwscecereflecocom/geerl-leers--mhemcs/ Geerl Leers Mhemcs Scece Refleco Iegrl Equos d her Reloshp

More information

The Poisson Process Properties of the Poisson Process

The Poisson Process Properties of the Poisson Process Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad

More information

Efficient Estimators for Population Variance using Auxiliary Information

Efficient Estimators for Population Variance using Auxiliary Information Global Joural of Mahemacal cece: Theor ad Praccal. IN 97-3 Volume 3, Number (), pp. 39-37 Ieraoal Reearch Publcao Houe hp://www.rphoue.com Effce Emaor for Populao Varace ug Aular Iformao ubhah Kumar Yadav

More information

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1 Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch

More information

Decompression diagram sampler_src (source files and makefiles) bin (binary files) --- sh (sample shells) --- input (sample input files)

Decompression diagram sampler_src (source files and makefiles) bin (binary files) --- sh (sample shells) --- input (sample input files) . Iroduco Probblsc oe-moh forecs gudce s mde b 50 esemble members mproved b Model Oupu scs (MO). scl equo s mde b usg hdcs d d observo d. We selec some prmeers for modfg forecs o use mulple regresso formul.

More information

Analysis of the Preference Shift of. Customer Brand Selection. and Its Matrix Structure. -Expansion to the second order lag

Analysis of the Preference Shift of. Customer Brand Selection. and Its Matrix Structure. -Expansion to the second order lag Jourl of Compuo & Modellg vol. o. 6-9 ISS: 79-76 (pr) 79-88 (ole) Scepre Ld l of he Preferece Shf of Cuomer Brd Seleco d I Mr Srucure -Epo o he ecod order lg Kuhro Teu rc I ofe oerved h coumer elec he

More information

I I M O I S K J H G. b gb g. Chapter 8. Problem Solutions. Semiconductor Physics and Devices: Basic Principles, 3 rd edition Chapter 8

I I M O I S K J H G. b gb g. Chapter 8. Problem Solutions. Semiconductor Physics and Devices: Basic Principles, 3 rd edition Chapter 8 emcouc hyscs evces: Bsc rcles, r eo Cher 8 oluos ul rolem oluos Cher 8 rolem oluos 8. he fwr s e ex f The e ex f e e f ex () () f f f f l G e f f ex f 59.9 m 60 m 0 9. m m 8. e ex we c wre hs s e ex h

More information

Competitive Facility Location Problem with Demands Depending on the Facilities

Competitive Facility Location Problem with Demands Depending on the Facilities Aa Pacc Maageme Revew 4) 009) 5-5 Compeve Facl Locao Problem wh Demad Depedg o he Facle Shogo Shode a* Kuag-Yh Yeh b Hao-Chg Ha c a Facul of Bue Admrao Kobe Gau Uver Japa bc Urba Plag Deparme Naoal Cheg

More information

Chapter Simpson s 1/3 Rule of Integration. ( x)

Chapter Simpson s 1/3 Rule of Integration. ( x) Cper 7. Smpso s / Rule o Iegro Aer redg s per, you sould e le o. derve e ormul or Smpso s / rule o egro,. use Smpso s / rule o solve egrls,. develop e ormul or mulple-segme Smpso s / rule o egro,. use

More information

Analysis of a Stochastic Lotka-Volterra Competitive System with Distributed Delays

Analysis of a Stochastic Lotka-Volterra Competitive System with Distributed Delays Ieraoal Coferece o Appled Maheac Sulao ad Modellg (AMSM 6) Aaly of a Sochac Loa-Volerra Copeve Sye wh Drbued Delay Xagu Da ad Xaou L School of Maheacal Scece of Togre Uvery Togre 5543 PR Cha Correpodg

More information

Novel Bose-Einstein Interference in the Passage of a Jet in a Dense Medium. Oak Ridge National Laboratory

Novel Bose-Einstein Interference in the Passage of a Jet in a Dense Medium. Oak Ridge National Laboratory Rdge Worksho, INT, My 7-, 0 Novel Bose-Ese Ierferece he Pssge of Je Dese Medu Cheuk-Y Wog Ok Rdge Nol Lborory Our focus: recols of edu ros fer je collso Poel odel versus Fey lude roch Bose-Ese erferece

More information

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body.

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body. The kecs of rgd bodes reas he relaoshps bewee he exeral forces acg o a body ad he correspodg raslaoal ad roaoal moos of he body. he kecs of he parcle, we foud ha wo force equaos of moo were requred o defe

More information

A Class of Lobatto Methods of Order 2s

A Class of Lobatto Methods of Order 2s IAENG Ierol Jourl of Appled hem, :, IJA A Cl of oo ehod of Order Wg Fgog d o Xog Ar he fmle of oo RugeKu mehod h o of oo IIIA mehod, oo IIIB mehod, d oo IIIC mehod re ll of order d Ale. Ug V rformo d he

More information

Introduction to Laplace Transforms October 25, 2017

Introduction to Laplace Transforms October 25, 2017 Iroduco o Lplc Trform Ocobr 5, 7 Iroduco o Lplc Trform Lrr ro Mchcl Egrg 5 Smr Egrg l Ocobr 5, 7 Oul Rvw l cl Wh Lplc rform fo of Lplc rform Gg rform b gro Fdg rform d vr rform from bl d horm pplco o dffrl

More information

ESTIMATION AND TESTING

ESTIMATION AND TESTING CHAPTER ESTIMATION AND TESTING. Iroduco Modfcao o he maxmum lkelhood (ML mehod of emao cera drbuo o overcome erave oluo of ML equao for he parameer were uggeed by may auhor (for example Tku (967; Mehrora

More information

CS344: Introduction to Artificial Intelligence

CS344: Introduction to Artificial Intelligence C344: Iroduco o Arfcal Iellgece Puhpa Bhaacharyya CE Dep. IIT Bombay Lecure 3 3 32 33: Forward ad bacward; Baum elch 9 h ad 2 March ad 2 d Aprl 203 Lecure 27 28 29 were o EM; dae 2 h March o 8 h March

More information

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

More information

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead)

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead) Week 8 Lecure 3: Problems 49, 5 Fourier lysis Coursewre pp 6-7 (do look Frech very cofusig look i he Coursewre ised) Fourier lysis ivolves ddig wves d heir hrmoics, so i would hve urlly followed fer he

More information

Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination

Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination Lecure 3 Topc : Drbuo, hypohe eg, ad ample ze deermao The Sude - drbuo Coder a repeaed drawg of ample of ze from a ormal drbuo of mea. For each ample, compue,,, ad aoher ac,, where: The ac he devao of

More information

Monte Carlo Simulation in Thermal Radiative Transfer: Method Review, Validation and Parameter Sensitivity

Monte Carlo Simulation in Thermal Radiative Transfer: Method Review, Validation and Parameter Sensitivity Ierol Jourl of Mechcl & Mechroc Egeerg IJMME Vol: 9 o: 9 - - Moe Crlo Smulo herml Rdve rfer: Mehod Revew, Vldo d Prmeer Sevy Zfr U. Koreh, Sdf Sdd, eem M. Shh Arc Moe Crlo () mulo exevely ued for olvg

More information

Modeling and Predicting Sequences: HMM and (may be) CRF. Amr Ahmed Feb 25

Modeling and Predicting Sequences: HMM and (may be) CRF. Amr Ahmed Feb 25 Modelg d redcg Sequeces: HMM d m be CRF Amr Ahmed 070 Feb 25 Bg cure redcg Sgle Lbel Ipu : A se of feures: - Bg of words docume - Oupu : Clss lbel - Topc of he docume - redcg Sequece of Lbels Noo Noe:

More information

X-Ray Notes, Part III

X-Ray Notes, Part III oll 6 X-y oe 3: Pe X-Ry oe, P III oe Deeo Coe oupu o x-y ye h look lke h: We efe ue of que lhly ffee efo h ue y ovk: Co: C ΔS S Sl o oe Ro: SR S Co o oe Ro: CR ΔS C SR Pevouly, we ee he SR fo ye hv pxel

More information

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.

More information

(1) Cov(, ) E[( E( ))( E( ))]

(1) Cov(, ) E[( E( ))( E( ))] Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )

More information

Reliability Equivalence of a Parallel System with Non-Identical Components

Reliability Equivalence of a Parallel System with Non-Identical Components Ieraoa Mahemaca Forum 3 8 o. 34 693-7 Reaby Equvaece of a Parae Syem wh No-Ideca ompoe M. Moaer ad mmar M. Sarha Deparme of Sac & O.R. oege of Scece Kg Saud Uvery P.O.ox 455 Ryadh 45 Saud raba aarha@yahoo.com

More information

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n 0. Sere I th ecto, we wll troduce ere tht wll be dcug for the ret of th chpter. Wht ere? If we dd ll term of equece, we get whch clled fte ere ( or jut ere) d deoted, for hort, by the ymbol or Doe t mke

More information

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral

More information

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits.

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits. ose ad Varably Homewor # (8), aswers Q: Power spera of some smple oses A Posso ose A Posso ose () s a sequee of dela-fuo pulses, eah ourrg depedely, a some rae r (More formally, s a sum of pulses of wdh

More information

A NEW FIVE-POINT BINARY SUBDIVISION SCHEME WITH A PARAMETER

A NEW FIVE-POINT BINARY SUBDIVISION SCHEME WITH A PARAMETER Jourl of ure d Appled Mhemcs: Advces d Applcos Volume 9 Numer ges -9 Avlle hp://scefcdvcesco DOI: hp://dxdoorg/6/ms_9 A NEW FIVE-OINT BINARY UBDIVIION CHEME WITH A ARAMETER YAN WANG * d HIMING LI chool

More information

Reinforcement Learning

Reinforcement Learning Reiforceme Corol lerig Corol polices h choose opiml cios Q lerig Covergece Chper 13 Reiforceme 1 Corol Cosider lerig o choose cios, e.g., Robo lerig o dock o bery chrger o choose cios o opimize fcory oupu

More information

Policy optimization. Stochastic approach

Policy optimization. Stochastic approach Polcy opmzo Sochc pproch Dcree-me Mrkov Proce Sory Mrkov ch Sochc proce over fe e e S S {.. 2 S} Oe ep ro probbly: Prob j - p j Se ro me: geomerc drbuo Prob j T p j p - 2 Dcree-me Mrkov Proce Sory corollble

More information

A Remark on Generalized Free Subgroups. of Generalized HNN Groups

A Remark on Generalized Free Subgroups. of Generalized HNN Groups Ieraoal Mahemacal Forum 5 200 o 503-509 A Remar o Geeralzed Free Subroup o Geeralzed HNN Group R M S Mahmood Al Ho Uvery Abu Dhab POBo 526 UAE raheedmm@yahoocom Abrac A roup ermed eeralzed ree roup a ree

More information

graph of unit step function t

graph of unit step function t .5 Piecewie coninuou forcing funcion...e.g. urning he forcing on nd off. The following Lplce rnform meril i ueful in yem where we urn forcing funcion on nd off, nd when we hve righ hnd ide "forcing funcion"

More information

Continuous Time Markov Chains

Continuous Time Markov Chains Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,

More information

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state) Pro. O. B. Wrgh, Auum Quaum Mechacs II Lecure Tme-depede perurbao heory Tme-depede perurbao heory (degeerae or o-degeerae sarg sae) Cosder a sgle parcle whch, s uperurbed codo wh Hamloa H, ca exs a superposo

More information

Second Quantization for Fermions

Second Quantization for Fermions 9 Chaper Secod Quazao for Fermo Maro Pr Iuo Superor de Ceca y Tecología Nucleare, Ave Salvador Allede y Luace, Qua de lo Molo, La Habaa 6, Cuba. The objec of quaum chemry co of eracg may parcle yem of

More information

An improved Bennett s inequality

An improved Bennett s inequality COMMUNICATIONS IN STATISTICS THEORY AND METHODS 017,VOL.0,NO.0,1 8 hps://do.org/10.1080/0361096.017.1367818 A mproved Bee s equly Sogfeg Zheg Deprme of Mhemcs, Mssour Se Uversy, Sprgfeld, MO, USA ABSTRACT

More information

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002 Mmm lkelhood eme of phylogey BIO 9S/ S 90B/ MH 90B/ S 90B Iodco o Bofomc pl 00 Ovevew of he pobblc ppoch o phylogey o k ee ccodg o he lkelhood d ee whee d e e of eqece d ee by ee wh leve fo he eqece. he

More information

Introduction to Neural Networks Computing. CMSC491N/691N, Spring 2001

Introduction to Neural Networks Computing. CMSC491N/691N, Spring 2001 Iroduco o Neurl Neorks Compug CMSC49N/69N, Sprg 00 us: cvo/oupu: f eghs: X, Y j X Noos, j s pu u, for oher us, j pu sgl here f. s he cvo fuco for j from u o u j oher books use Y f _ j j j Y j X j Y j bs:

More information

Conquering kings their titles take ANTHEM FOR CONGREGATION AND CHOIR

Conquering kings their titles take ANTHEM FOR CONGREGATION AND CHOIR Coquerg gs her es e NTHEM FOR CONGREGTION ND CHOIR I oucg hs hm-hem, whch m be cuded Servce eher s Hm or s hem, he Cogrego m be referred o he No. of he Hm whch he words pper, d ved o o sgg he 1 s, 4 h,

More information

NONLINEAR SYSTEM OF SINGULAR PARTIAL DIFFERENTIAL EQUATIONS

NONLINEAR SYSTEM OF SINGULAR PARTIAL DIFFERENTIAL EQUATIONS Jourl of Mhemcl Sceces: dvces d pplcos Volume 43, 27, Pges 3-53 vlble hp://scefcdvces.co. DOI: hp://d.do.org/.8642/ms_72748 OLIER SYSTEM OF SIGULR PRTIL DIFFERETIL EQUTIOS PTRICE POGÉRRD Mhemcs Lborory

More information

Collapsing to Sample and Remainder Means. Ed Stanek. In order to collapse the expanded random variables to weighted sample and remainder

Collapsing to Sample and Remainder Means. Ed Stanek. In order to collapse the expanded random variables to weighted sample and remainder Collapg to Saple ad Reader Mea Ed Staek Collapg to Saple ad Reader Average order to collape the expaded rado varable to weghted aple ad reader average, we pre-ultpled by ( M C C ( ( M C ( M M M ( M M M,

More information

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity Ieraoal Joural of Mahemacs esearch. IN 0976-50 Volume 6, Number (0), pp. 6-7 Ieraoal esearch Publcao House hp://www.rphouse.com Bach ype II ff Flud led Cosmologcal Model Geeral elay B. L. Meea Deparme

More information

SLOW INCREASING FUNCTIONS AND THEIR APPLICATIONS TO SOME PROBLEMS IN NUMBER THEORY

SLOW INCREASING FUNCTIONS AND THEIR APPLICATIONS TO SOME PROBLEMS IN NUMBER THEORY VOL. 8, NO. 7, JULY 03 ISSN 89-6608 ARPN Jourl of Egieerig d Applied Sciece 006-03 Ai Reerch Publihig Nework (ARPN). All righ reerved. www.rpjourl.com SLOW INCREASING FUNCTIONS AND THEIR APPLICATIONS TO

More information

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS . REVIEW OF PROPERTIES OF EIGENVLUES ND EIGENVECTORS. EIGENVLUES ND EIGENVECTORS We hll ow revew ome bc fct from mtr theory. Let be mtr. clr clled egevlue of f there et ozero vector uch tht Emle: Let 9

More information

Chapter Trapezoidal Rule of Integration

Chapter Trapezoidal Rule of Integration Cper 7 Trpezodl Rule o Iegro Aer redg s per, you sould e le o: derve e rpezodl rule o egro, use e rpezodl rule o egro o solve prolems, derve e mulple-segme rpezodl rule o egro, 4 use e mulple-segme rpezodl

More information

Stat 6863-Handout 5 Fundamentals of Interest July 2010, Maurice A. Geraghty

Stat 6863-Handout 5 Fundamentals of Interest July 2010, Maurice A. Geraghty S 6863-Hou 5 Fuels of Ieres July 00, Murce A. Gerghy The pror hous resse beef cl occurreces, ous, ol cls e-ulero s ro rbles. The fl copoe of he curl oel oles he ecooc ssupos such s re of reur o sses flo.

More information

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p

The MacWilliams Identity of the Linear Codes over the Ring F p +uf p +vf p +uvf p Reearch Joural of Aled Scece Eeer ad Techoloy (6): 28-282 22 ISSN: 2-6 Maxwell Scefc Orazao 22 Submed: March 26 22 Acceed: Arl 22 Publhed: Auu 5 22 The MacWllam Idey of he Lear ode over he R F +uf +vf

More information

A note on Turán number Tk ( 1, kn, )

A note on Turán number Tk ( 1, kn, ) A oe o Turá umber T (,, ) L A-Pg Beg 00085, P.R. Cha apl000@sa.com Absrac: Turá umber s oe of prmary opcs he combaorcs of fe ses, hs paper, we wll prese a ew upper boud for Turá umber T (,, ). . Iroduco

More information

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type J N Sce & Mh Res Vol 3 No (7) -7 Alble ole h://orlwlsogocd/deh/sr P-Coey Proery Msel-Orlcz Fco Sce o Boher ye Yl Rodsr Mhecs Edco Deree Fcly o Ss d echology Uerss sl Neger Wlsogo Cerl Jdoes Absrcs Corresodg

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Application of Multiple Exp-Function Method to Obtain Multi-Soliton Solutions of (2 + 1)- and (3 + 1)-Dimensional Breaking Soliton Equations

Application of Multiple Exp-Function Method to Obtain Multi-Soliton Solutions of (2 + 1)- and (3 + 1)-Dimensional Breaking Soliton Equations Amerc Jourl of Compuol Appled Mhemcs: ; (: 4-47 DOI:.593/j.jcm..8 Applco of Mulple Exp-Fuco Mehod o Ob Mul-Solo Soluos of ( + - (3 + -Dmesol Breg Solo Equos M. T. Drvsh,*, Mlheh Njf, Mohmmd Njf Deprme

More information

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3.

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3. C. Trael me cures for mulple reflecors The ray pahs ad rael mes for mulple layers ca be compued usg ray-racg, as demosraed Lab. MATLAB scrp reflec_layers_.m performs smple ray racg. (m) ref(ms) ref(ms)

More information

Mathematical Formulation

Mathematical Formulation Mahemacal Formulao The purpose of a fe fferece equao s o appromae he paral ffereal equao (PE) whle maag he physcal meag. Eample PE: p c k FEs are usually formulae by Taylor Seres Epaso abou a po a eglecg

More information

U1. Transient circuits response

U1. Transient circuits response U. Tr crcu rpo rcu ly, Grdo Irí d omucco uro 6-7 Phlp Sm phlp.m@uh. Dprmo d Torí d l Sñl y omucco Idx Rcll Gol d movo r dffrl quo Rcll Th homoou oluo d d ordr lr dffrl quo Exmpl of d ordr crcu Il codo

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model Joura of Saca Theory ad Appcao Vo. No. (Sepember ) - Parameer Emao a Geera Faure Rae Sem-Marov Reaby Mode M. Fahzadeh ad K. Khorhda Deparme of Sac Facuy of Mahemaca Scece Va-e-Ar Uvery of Rafaja Rafaja

More information

-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for

-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for Assgme Sepha Brumme Ocober 8h, 003 9 h semeser, 70544 PREFACE I 004, I ed o sped wo semesers o a sudy abroad as a posgraduae exchage sude a he Uversy of Techology Sydey, Ausrala. Each opporuy o ehace my

More information

Nonsynchronous covariation process and limit theorems

Nonsynchronous covariation process and limit theorems Sochac Procee ad her Applcao 121 (211) 2416 2454 www.elever.com/locae/pa Noychroou covarao proce ad lm heorem Takak Hayah a,, Nakahro Yohda b a Keo Uvery, Graduae School of Bue Admrao, 4-1-1 Hyoh, Yokohama

More information

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae

More information

Spherical refracting surface. Here, the outgoing rays are on the opposite side of the surface from the Incoming rays.

Spherical refracting surface. Here, the outgoing rays are on the opposite side of the surface from the Incoming rays. Sphericl refrctig urfce Here, the outgoig ry re o the oppoite ide of the urfce from the Icomig ry. The oject i t P. Icomig ry PB d PV form imge t P. All prxil ry from P which trike the phericl urfce will

More information

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY

INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY [Mjuh, : Jury, 0] ISSN: -96 Scefc Jourl Impc Fcr: 9 ISRA, Impc Fcr: IJESRT INTERNATIONAL JOURNAL OF ENINEERIN SCIENCES & RESEARCH TECHNOLOY HAMILTONIAN LACEABILITY IN MIDDLE RAPHS Mjuh*, MurlR, B Shmukh

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

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

LAPLACE TRANSFORMS. 1. Basic transforms

LAPLACE TRANSFORMS. 1. Basic transforms LAPLACE TRANSFORMS. Bic rnform In hi coure, Lplce Trnform will be inroduced nd heir properie exmined; ble of common rnform will be buil up; nd rnform will be ued o olve ome dierenil equion by rnforming

More information

ONE APPROACH FOR THE OPTIMIZATION OF ESTIMATES CALCULATING ALGORITHMS A.A. Dokukin

ONE APPROACH FOR THE OPTIMIZATION OF ESTIMATES CALCULATING ALGORITHMS A.A. Dokukin Iero Jor "Iforo Theore & co" Vo 463 ONE PPROH FOR THE OPTIIZTION OF ETITE UTING GORITH Do rc: I h rce he ew roch for ozo of eo ccg gorh ggeed I c e ed for fdg he correc gorh of coexy he coex of gerc roch

More information

Linear Open Loop Systems

Linear Open Loop Systems Colordo School of Me CHEN43 Trfer Fucto Ler Ope Loop Sytem Ler Ope Loop Sytem... Trfer Fucto for Smple Proce... Exmple Trfer Fucto Mercury Thermometer... 2 Derblty of Devto Vrble... 3 Trfer Fucto for Proce

More information

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

4. THE DENSITY MATRIX

4. THE DENSITY MATRIX 4. THE DENSTY MATRX The desy marx or desy operaor s a alerae represeao of he sae of a quaum sysem for whch we have prevously used he wavefuco. Alhough descrbg a quaum sysem wh he desy marx s equvale o

More information

KINEMATICS OF RIGID BODIES RELATIVE VELOCITY RELATIVE ACCELERATION PROBLEMS

KINEMATICS OF RIGID BODIES RELATIVE VELOCITY RELATIVE ACCELERATION PROBLEMS KINEMTICS OF RIGID ODIES RELTIVE VELOCITY RELTIVE CCELERTION PROLEMS 1. The crculr dsk rolls o he lef whou slppg. If.7 m s deerme he eloc d ccelero of he ceer O of he dsk. (516) .7 m s O? O? . The ed rollers

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

Some Improved Estimators for Population Variance Using Two Auxiliary Variables in Double Sampling

Some Improved Estimators for Population Variance Using Two Auxiliary Variables in Double Sampling Vplav Kumar gh Rajeh gh Deparme of ac Baara Hdu Uver Varaa-00 Ida Flore maradache Uver of ew Meco Gallup UA ome Improved Emaor for Populao Varace Ug Two Aular Varable Double amplg Publhed : Rajeh gh Flore

More information

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

New approach for numerical solution of Fredholm integral equations system of the second kind by using an expansion method

New approach for numerical solution of Fredholm integral equations system of the second kind by using an expansion method Ieraoal Reearch Joural o Appled ad Bac Scece Avalable ole a wwwrabcom ISSN 5-88X / Vol : 8- Scece xplorer Publcao New approach or umercal oluo o Fredholm eral equao yem o he ecod d by u a expao mehod Nare

More information

Science & Technologies GENERAL BIRTH-DEATH PROCESS AND SOME OF THEIR EM (EXPETATION- MAXIMATION) ALGORITHM

Science & Technologies GENERAL BIRTH-DEATH PROCESS AND SOME OF THEIR EM (EXPETATION- MAXIMATION) ALGORITHM GEERAL BIRH-EAH ROCESS A SOME OF HEIR EM EXEAIO- MAXIMAIO) ALGORIHM Il Hl, Lz Ker, Ylldr Seer Se ery o eoo,, eoo Mcedo l.hl@e.ed.; lz.er@e.ed.; ylldr_@hol.co ABSRAC Brh d deh roce coo-e Mrco ch, h odel

More information

Solution set Stat 471/Spring 06. Homework 2

Solution set Stat 471/Spring 06. Homework 2 oluo se a 47/prg 06 Homework a Whe he upper ragular elemes are suppressed due o smmer b Le Y Y Y Y A weep o he frs colum o oba: A ˆ b chagg he oao eg ad ec YY weep o he secod colum o oba: Aˆ YY weep o

More information

KINEMATICS OF RIGID BODIES RELATIVE VELOCITY RELATIVE ACCELERATION PROBLEMS

KINEMATICS OF RIGID BODIES RELATIVE VELOCITY RELATIVE ACCELERATION PROBLEMS KINEMTICS F RIGID DIES RELTIVE VELCITY RELTIVE CCELERTIN PRLEMS 1. The crculr dsk rolls o he lef whou slppg. If.7 m s deerme he eloc d ccelero of he ceer of he dsk. (516) .7 m s?? . The eloc of roller

More information

Chapter 5 Transient Analysis

Chapter 5 Transient Analysis hpr 5 rs Alyss Jsug Jg ompl rspos rs rspos y-s rspos m os rs orr co orr Dffrl Equo. rs Alyss h ffrc of lyss of crcus wh rgy sorg lms (ucors or cpcors) & m-ryg sgls wh rss crcus s h h quos rsulg from r

More information

Multivariate Time Series Analysis

Multivariate Time Series Analysis Mulvre me Sere Anl Le { : } be Mulvre me ere. Denon: () = men vlue uncon o { : } = E[ ] or. (,) = Lgged covrnce mr o { : } = E{[ - ()][ - ()]'} or, Denon: e me ere { : } onr e jon drbuon o,,, e me e jon

More information

EGN 3321 Final Exam Review Spring 2017

EGN 3321 Final Exam Review Spring 2017 EN 33 l Em Reew Spg 7 *T fshg ech poblem 5 mues o less o pcce es-lke me coss. The opcs o he pcce em e wh feel he bee sessed clss, bu hee m be poblems o he es o lke oes hs pcce es. Use ohe esouces lke he

More information

Review - Week 10. There are two types of errors one can make when performing significance tests:

Review - Week 10. There are two types of errors one can make when performing significance tests: Review - Week Read: Chaper -3 Review: There are wo ype of error oe ca make whe performig igificace e: Type I error The ull hypohei i rue, bu we miakely rejec i (Fale poiive) Type II error The ull hypohei

More information

Let s treat the problem of the response of a system to an applied external force. Again,

Let s treat the problem of the response of a system to an applied external force. Again, Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information