STOCHASTIC BEHAVIOUR OF COMMUNICATION SUBSYSTEM OF COMMUNICATION SATELLITE
|
|
- Edgar Shepherd
- 5 years ago
- Views:
Transcription
1 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte SOHSI HVIOU O OMMUNIION SUSYSM O OMMUNIION SLLI SK Mttal eepankar Sharma & Neelam Sharma 3 S he author n th paper have dcued the tochatc behavor of communcaton atellte for evaluaton of ome mportant relablty parameter One Standby control unt ha been taken to mprove ytem performance h Standby unt can take place through a perfect wtchng devce Supplementary varable technque ha been ued to convert a Non-Markovan proce n to Markovan one Steady-State behavor of the ytem ha obtaned ll the tranton State probablte n cae repar follow exponental tme dtrbuton have alo computed to mprove practcal utlty of the model Keyword: Supplementary varable erfect Swtchng Standby redundancy valablty and cot functon INOUION he heart of a atellte the communcaton ubytem It cont of multple tranponder whch a explaned earler receve and amplfy up-lnk gnal tranlate them n frequency and amplfy agan for retranmon a down-lnk gnal In the ngle converon tranponder (fg) only ngle frequency tranlaton proce take place from the receved gnal to the tranmtted gnal he author dvded the ytem nto fve ubytem namely (ntenna) (ecever) t (frequency tranlator) (tranmtter) and (two control unt n tandby) Laplace tranform and upplementary varable technque have been ued to olve and formulate of mathematcal model ll falure follow exponental tme dtrbuton where a all repar follow general tme dtrbuton Laplace tranform of varou tate probablte have been obtaned numercal example together wth t graphcal llutraton ha appended n lat to hghlght mportant reult of th tudy SSUMIONS he followng aumpton have been aocated wth th model: Intally the ytem work wth t full effcency epar faclte are alway avalable and after repar unt work lke new one 3 Swtchng devce ued to onlne tandby control unt perfect 4 alure are tattcally ndependent Nothng can fal from a faled tate 5 ll the falure and repar follow exponental and general tme dtrbuton repectvely ommuncaton Subytem ecver requency ranlator ranponder ranmtter ntenna Subytem erfect Swtchng evce ommuncaton ntenna ontrol unt g-: General block dagram of a atellte 8
2 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte (x) (m) ( y (y) ( x ( m (x) ( ) ( ) t ( x t (y) c ( y (z) (r) (z) (r) ( z ( r (x) ( r ( z ( n g-: State-ranton agram State: Good aled NOMNLU ollowng notaton have been ued throughout th tudy: ( ) : he probablty that at tme t the ytem n good tate of full effcency t ( j : he probablty that at tme t the ytem n faled tate due to falure of th ubytem and elaped repar tme le n the nterval j j where and j xy zrm xy zrn repectvely ( j) : he frt order probablty that th ubytem wll be repared n the tme nterval j j condtoned that t wa not repared up to the tme j 83
3 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte / / / / : alure rate of ntenna recever frequency tranlator tranmtter and whole / ytem due to envronmental reaon : alure rate of control unt I and II : Laplace tranform of functon ( M : t d d S = mean tme to repar S : jexp ( j) dj for j μ th unt 3 OMULION O MHMIL MOL: Ung contnuty argument we obtan the followng et of dfference-dfferental equaton whch are dcrete n pace and contnuou n tme governng the behavour of the model under conderaton: t t x x t dx y y t dy z z tdz r r tdr m m t n n t dn t t t t t x y z r m dm x x t y y t z z t r r t m m t () () (3) (4) (5) (6) 84
4 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte t n n n t (7) t t x x t dx y y t dy z z t r r tdr t t x t y t z t r x x t y y t z z t oundary condton are: t t t t t t t t r r t (8) (9) () () () (3) (4) (5) (6) t t t (7) t t t t t t t t t t (8) (9) () () () 85
5 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte Intal condton: and all other tate probablte at t are zero (3) 4 SOLUION O H MOL: akng Laplace tranform of equaton () through () by makng ue of ntal condton (3) and then on olvng them one by one we obtan the followng Laplace tranform of dfferent tate probablte: (4) m (5) (6) (7) (8) (9) (3) (3) (3) (33) (34) 86
6 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte (35) where S S S S (36) S S S S S S S (37) and j S j j for all and j (38) 5 GOI HVIOU O H SYSM: y makng ue of bel Lemma Vz lm lm t ay o t have the followng tme- ndependent tate probablte from equaton (4) through (35): provded the lmt on rght ext we (39) M (4) M (4) M (4) M (43) (ay) (44) M (45) 87
7 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte M M M M M where (46) (47) (48) (49) (5) (5) M S for all (5) d d (53) 6 SOM IUL SS: (a) when repar follow exponental tme dtrbuton Settng S j for all and j n equaton (4) through (35) one may obtan the followng tranton tate j probablte n th cae: (54) (55) (56) 88
8 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte 89 (57) (58) (59) (6) (6) (6) (63) (64) where (65) (66) and (67)
9 IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte (b) valablty and proft functon for the ytem: We have up or up a b where a b On takng nvere Laplace tranform we obtan up t at at e e a b e a b bt (68) It nteretng to note that up lo t t down (69) gan the proft functon for the ytem gven by up t upt dt t 3 G t Where revenue cot per unt tme repar cot per unt tme and 3 ytem etablhment cot for one perod o here e a a b t 3 G t at e b bt a b (7) where a and b have mentoned earler (c) Numercal omputaton or a numercal computaton let u conder the data / unt tme / unt tme 3 5 / etup and t= y puttng thee value n equaton (68) (69) and (7) we plot varou graph hown n fgure (3) (4) and (5) 9
10 up( > IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte to oberve the change n value of avalablty and proft functon able and 3 how the value of t t up down and G( repectvely 7 SULS N ISUSSION ll the tranton tate probablte n cae repar follow exponental tme dtrbuton have been computed to mprove practcal utlty of the model Steady-tate behavour of the ytem ha alo been obtaned One numercal computaton wth t graphcal llutraton ha mentoned n the end to hghlght mportant reult of tudy n examnaton of table - and fg-3 reveal that the avalablty of the ytem decreae catatrophcally n the begnnng but after t =4 t decreae n a contant manner lo fg-4 the graph roft functon v t and the correpondng value are gven n the table - crtcal examnaton of fg-4 yeld that proft functon negatve n tartng becaue ntally we nvet money to etablh the new ytem but G( become potve and t value tart ncreang up to t=6 and thereafter t agan decreae Maxmum value of G ( and t for t=6 t up t able- up( 8 6 up( t > g- 3 9
11 G( > IJS 4 () July Sharma & al ehavour of Subytem of ommuncaton Satellte G t t able- G( t > G g- 4 8 NS [] Satellte ommuncaton Sytem ngneerng rentce Hall Inc New Jerey 993 G Gordon and WL Morgan: [] rncple of ommuncaton Satellte John Wley & Son Inc NY pp [3] Hyder ; Joorel J S: Stochatc ehavor of a wo Unt old Standby edundant Sytem Subject to andom alure Mcroelectronc elab Vol 36() pp [4] Satellte ommuncaton Sytem John Wlley and Son ourth dton 3 757pp Satellte and atellte ubytem relablty: Stattcal data analy and modelng [5] ape V; akten : n Introducton to ontnuou-tme Stochatc rocee: heory Model and pplcaton" rkhauer ublcaton 4 [6] Sharma eepankar Sharma Jyot; tmaton of relablty parameter for telecommuncaton ytem Journal of combnatorc nformaton and ytem cence Vol9 No-4 pp5-6(5) [7] Sharma eepankar Geol K; Sharma Vnt: elablty and M evaluaton of telecommuncaton ytem ulletn of pure and appled Scence Vol4 () No pp (5) 9
COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
More informationAdditional 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 informationABSTRACT
RELIABILITY AND SENSITIVITY ANALYSIS OF THE K-OUT-OF-N:G WARM STANDBY PARALLEL REPAIRABLE SYSTEM WITH REPLACEMENT AT COMMON-CAUSE FAILURE USING MARKOV MODEL M. A. El-Damcese 1 and N. H. El-Sodany 2 1 Mathematcs
More informationAPPLICATIONS OF RELIABILITY ANALYSIS TO POWER ELECTRONICS SYSTEMS
APPLICATIONS OF RELIABILITY ANALYSIS TO POWER ELECTRONICS SYSTEMS Chanan Sngh, Fellow IEEE Praad Enjet, Fellow IEEE Department o Electrcal Engneerng Texa A&M Unverty College Staton, Texa USA Joydeep Mtra,
More informationSpecification -- Assumptions of the Simple Classical Linear Regression Model (CLRM) 1. Introduction
ECONOMICS 35* -- NOTE ECON 35* -- NOTE Specfcaton -- Aumpton of the Smple Clacal Lnear Regreon Model (CLRM). Introducton CLRM tand for the Clacal Lnear Regreon Model. The CLRM alo known a the tandard lnear
More informationHarmonic oscillator approximation
armonc ocllator approxmaton armonc ocllator approxmaton Euaton to be olved We are fndng a mnmum of the functon under the retrcton where W P, P,..., P, Q, Q,..., Q P, P,..., P, Q, Q,..., Q lnwgner functon
More informationThe optimal delay of the second test is therefore approximately 210 hours earlier than =2.
THE IEC 61508 FORMULAS 223 The optmal delay of the second test s therefore approxmately 210 hours earler than =2. 8.4 The IEC 61508 Formulas IEC 61508-6 provdes approxmaton formulas for the PF for smple
More informationThe multivariate Gaussian probability density function for random vector X (X 1,,X ) T. diagonal term of, denoted
Appendx Proof of heorem he multvarate Gauan probablty denty functon for random vector X (X,,X ) px exp / / x x mean and varance equal to the th dagonal term of, denoted he margnal dtrbuton of X Gauan wth
More informationCS-433: Simulation and Modeling Modeling and Probability Review
CS-433: Smulaton and Modelng Modelng and Probablty Revew Exercse 1. (Probablty of Smple Events) Exercse 1.1 The owner of a camera shop receves a shpment of fve cameras from a camera manufacturer. Unknown
More informationA new Approach for Solving Linear Ordinary Differential Equations
, ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of
More informationOn the SO 2 Problem in Thermal Power Plants. 2.Two-steps chemical absorption modeling
Internatonal Journal of Engneerng Reearch ISSN:39-689)(onlne),347-53(prnt) Volume No4, Iue No, pp : 557-56 Oct 5 On the SO Problem n Thermal Power Plant Two-tep chemcal aborpton modelng hr Boyadjev, P
More informationConfidence intervals for the difference and the ratio of Lognormal means with bounded parameters
Songklanakarn J. Sc. Technol. 37 () 3-40 Mar.-Apr. 05 http://www.jt.pu.ac.th Orgnal Artcle Confdence nterval for the dfference and the rato of Lognormal mean wth bounded parameter Sa-aat Nwtpong* Department
More informationTwo-Layered Model of Blood Flow through Composite Stenosed Artery
Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 93-9466 Vol. 4, Iue (December 9), pp. 343 354 (Prevouly, Vol. 4, No.) Applcaton Appled Mathematc: An Internatonal Journal (AAM) Two-ayered Model
More informationStart Point and Trajectory Analysis for the Minimal Time System Design Algorithm
Start Pont and Trajectory Analy for the Mnmal Tme Sytem Degn Algorthm ALEXANDER ZEMLIAK, PEDRO MIRANDA Department of Phyc and Mathematc Puebla Autonomou Unverty Av San Claudo /n, Puebla, 757 MEXICO Abtract:
More informationChapter 6 The Effect of the GPS Systematic Errors on Deformation Parameters
Chapter 6 The Effect of the GPS Sytematc Error on Deformaton Parameter 6.. General Beutler et al., (988) dd the frt comprehenve tudy on the GPS ytematc error. Baed on a geometrc approach and aumng a unform
More informationIntroduction to Interfacial Segregation. Xiaozhe Zhang 10/02/2015
Introducton to Interfacal Segregaton Xaozhe Zhang 10/02/2015 Interfacal egregaton Segregaton n materal refer to the enrchment of a materal conttuent at a free urface or an nternal nterface of a materal.
More informationRoot 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 informationCHAPTER X PHASE-CHANGE PROBLEMS
Chapter X Phae-Change Problem December 3, 18 917 CHAPER X PHASE-CHANGE PROBLEMS X.1 Introducton Clacal Stefan Problem Geometry of Phae Change Problem Interface Condton X. Analytcal Soluton for Soldfcaton
More informationSmall signal analysis
Small gnal analy. ntroducton Let u conder the crcut hown n Fg., where the nonlnear retor decrbed by the equaton g v havng graphcal repreentaton hown n Fg.. ( G (t G v(t v Fg. Fg. a D current ource wherea
More informationElectric and magnetic field sensor and integrator equations
Techncal Note - TN12 Electrc and magnetc feld enor and ntegrator uaton Bertrand Da, montena technology, 1728 oen, Swtzerland Table of content 1. Equaton of the derate electrc feld enor... 1 2. Integraton
More informationElectrical Circuits II (ECE233b)
Electrcal Crcut II (ECE33b) Applcaton of Laplace Tranform to Crcut Analy Anet Dounav The Unverty of Wetern Ontaro Faculty of Engneerng Scence Crcut Element Retance Tme Doman (t) v(t) R v(t) = R(t) Frequency
More informationThe Study of Teaching-learning-based Optimization Algorithm
Advanced Scence and Technology Letters Vol. (AST 06), pp.05- http://dx.do.org/0.57/astl.06. The Study of Teachng-learnng-based Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute
More informationImprovements on Waring s Problem
Improvement on Warng Problem L An-Png Bejng, PR Chna apl@nacom Abtract By a new recurve algorthm for the auxlary equaton, n th paper, we wll gve ome mprovement for Warng problem Keyword: Warng Problem,
More informationThis appendix presents the derivations and proofs omitted from the main text.
Onlne Appendx A Appendx: Omtted Dervaton and Proof Th appendx preent the dervaton and proof omtted from the man text A Omtted dervaton n Secton Mot of the analy provded n the man text Here, we formally
More informationWeek3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity
Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle
More informationInformation Acquisition in Global Games of Regime Change (Online Appendix)
Informaton Acquton n Global Game of Regme Change (Onlne Appendx) Mchal Szkup and Iabel Trevno Augut 4, 05 Introducton Th appendx contan the proof of all the ntermedate reult that have been omtted from
More informationDynamic Programming. Lecture 13 (5/31/2017)
Dynamc Programmng Lecture 13 (5/31/2017) - A Forest Thnnng Example - Projected yeld (m3/ha) at age 20 as functon of acton taken at age 10 Age 10 Begnnng Volume Resdual Ten-year Volume volume thnned volume
More informationModelli Clamfim Equazione del Calore Lezione ottobre 2014
CLAMFIM Bologna Modell 1 @ Clamfm Equazone del Calore Lezone 17 15 ottobre 2014 professor Danele Rtell danele.rtell@unbo.t 1/24? Convoluton The convoluton of two functons g(t) and f(t) s the functon (g
More informationMethod Of Fundamental Solutions For Modeling Electromagnetic Wave Scattering Problems
Internatonal Workhop on MehFree Method 003 1 Method Of Fundamental Soluton For Modelng lectromagnetc Wave Scatterng Problem Der-Lang Young (1) and Jhh-We Ruan (1) Abtract: In th paper we attempt to contruct
More informationComparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method
Appled Mathematcal Scences, Vol. 7, 0, no. 47, 07-0 HIARI Ltd, www.m-hkar.com Comparson of the Populaton Varance Estmators of -Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method
More informationSystem in Weibull Distribution
Internatonal Matheatcal Foru 4 9 no. 9 94-95 Relablty Equvalence Factors of a Seres-Parallel Syste n Webull Dstrbuton M. A. El-Dacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co
More informationDistributed Control for the Parallel DC Linked Modular Shunt Active Power Filters under Distorted Utility Voltage Condition
Dtrbted Control for the Parallel DC Lnked Modlar Shnt Actve Power Flter nder Dtorted Utlty Voltage Condton Reearch Stdent: Adl Salman Spervor: Dr. Malabka Ba School of Electrcal and Electronc Engneerng
More informationMODELLING OF TRANSIENT HEAT TRANSPORT IN TWO-LAYERED CRYSTALLINE SOLID FILMS USING THE INTERVAL LATTICE BOLTZMANN METHOD
Journal o Appled Mathematc and Computatonal Mechanc 7, 6(4), 57-65 www.amcm.pcz.pl p-issn 99-9965 DOI:.75/jamcm.7.4.6 e-issn 353-588 MODELLING OF TRANSIENT HEAT TRANSPORT IN TWO-LAYERED CRYSTALLINE SOLID
More informationResource Allocation with a Budget Constraint for Computing Independent Tasks in the Cloud
Resource Allocaton wth a Budget Constrant for Computng Independent Tasks n the Cloud Wemng Sh and Bo Hong School of Electrcal and Computer Engneerng Georga Insttute of Technology, USA 2nd IEEE Internatonal
More informationQueueing Networks II Network Performance
Queueng Networks II Network Performance Davd Tpper Assocate Professor Graduate Telecommuncatons and Networkng Program Unversty of Pttsburgh Sldes 6 Networks of Queues Many communcaton systems must be modeled
More informationChapter 11. Supplemental Text Material. The method of steepest ascent can be derived as follows. Suppose that we have fit a firstorder
S-. The Method of Steepet cent Chapter. Supplemental Text Materal The method of teepet acent can be derved a follow. Suppoe that we have ft a frtorder model y = β + β x and we wh to ue th model to determne
More informationMAE140 - Linear Circuits - Winter 16 Final, March 16, 2016
ME140 - Lnear rcuts - Wnter 16 Fnal, March 16, 2016 Instructons () The exam s open book. You may use your class notes and textbook. You may use a hand calculator wth no communcaton capabltes. () You have
More informationENTROPY BOUNDS USING ARITHMETIC- GEOMETRIC-HARMONIC MEAN INEQUALITY. Guru Nanak Dev University Amritsar, , INDIA
Internatonal Journal of Pure and Appled Mathematc Volume 89 No. 5 2013, 719-730 ISSN: 1311-8080 prnted veron; ISSN: 1314-3395 on-lne veron url: http://.jpam.eu do: http://dx.do.org/10.12732/jpam.v895.8
More informationVariable Structure Control ~ Basics
Varable Structure Control ~ Bac Harry G. Kwatny Department of Mechancal Engneerng & Mechanc Drexel Unverty Outlne A prelmnary example VS ytem, ldng mode, reachng Bac of dcontnuou ytem Example: underea
More informationCHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS
CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS 103 Phy 1 9.1 Lnear Momentum The prncple o energy conervaton can be ued to olve problem that are harder to olve jut ung Newton law. It ued to decrbe moton
More information8 Waves in Uniform Magnetized Media
8 Wave n Unform Magnetzed Meda 81 Suceptblte The frt order current can be wrtten j = j = q d 3 p v f 1 ( r, p, t) = ɛ 0 χ E For Maxwellan dtrbuton Y n (λ) = f 0 (v, v ) = 1 πvth exp (v V ) v th 1 πv th
More informationLecture 3: Probability Distributions
Lecture 3: Probablty Dstrbutons Random Varables Let us begn by defnng a sample space as a set of outcomes from an experment. We denote ths by S. A random varable s a functon whch maps outcomes nto the
More informationPulse Coded Modulation
Pulse Coded Modulaton PCM (Pulse Coded Modulaton) s a voce codng technque defned by the ITU-T G.711 standard and t s used n dgtal telephony to encode the voce sgnal. The frst step n the analog to dgtal
More informationEstimation of Finite Population Total under PPS Sampling in Presence of Extra Auxiliary Information
Internatonal Journal of Stattc and Analy. ISSN 2248-9959 Volume 6, Number 1 (2016), pp. 9-16 Reearch Inda Publcaton http://www.rpublcaton.com Etmaton of Fnte Populaton Total under PPS Samplng n Preence
More informationPolynomial Regression Models
LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance
More informationComputer Control Systems
Computer Control ytem In th chapter we preent the element and the bac concept of computercontrolled ytem. The dcretaton and choce of amplng frequency wll be frt examned, followed by a tudy of dcrete-tme
More information/ n ) are compared. The logic is: if the two
STAT C141, Sprng 2005 Lecture 13 Two sample tests One sample tests: examples of goodness of ft tests, where we are testng whether our data supports predctons. Two sample tests: called as tests of ndependence
More informationELG3336: 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 informationModule 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:
More informationMULTIPLE REGRESSION ANALYSIS For the Case of Two Regressors
MULTIPLE REGRESSION ANALYSIS For the Cae of Two Regreor In the followng note, leat-quare etmaton developed for multple regreon problem wth two eplanator varable, here called regreor (uch a n the Fat Food
More informationRandomness and Computation
Randomness and Computaton or, Randomzed Algorthms Mary Cryan School of Informatcs Unversty of Ednburgh RC 208/9) Lecture 0 slde Balls n Bns m balls, n bns, and balls thrown unformly at random nto bns usually
More informationChapter 13: Multiple Regression
Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to
More informationPerformance Analysis for a Network having Standby Redundant Unit with Waiting in Repair
TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen
More informationChapter 7 Channel Capacity and Coding
Wreless Informaton Transmsson System Lab. Chapter 7 Channel Capacty and Codng Insttute of Communcatons Engneerng atonal Sun Yat-sen Unversty Contents 7. Channel models and channel capacty 7.. Channel models
More informationScattering of two identical particles in the center-of. of-mass frame. (b)
Lecture # November 5 Scatterng of two dentcal partcle Relatvtc Quantum Mechanc: The Klen-Gordon equaton Interpretaton of the Klen-Gordon equaton The Drac equaton Drac repreentaton for the matrce α and
More informationStatistical Properties of the OLS Coefficient Estimators. 1. Introduction
ECOOMICS 35* -- OTE 4 ECO 35* -- OTE 4 Stattcal Properte of the OLS Coeffcent Etmator Introducton We derved n ote the OLS (Ordnary Leat Square etmator ˆβ j (j, of the regreon coeffcent βj (j, n the mple
More informationDEADLOCK INDEX ANALYSIS OF MULTI-LEVEL QUEUE SCHEDULING IN OPERATING SYSTEM USING DATA MODEL APPROACH
GESJ: Computer Scence and Telecommuncaton 2 No.(29 ISSN 2-232 DEADLOCK INDEX ANALYSIS OF MULTI-LEVEL QUEUE SCHEDULING IN OPERATING SYSTEM USING DATA MODEL APPROACH D. Shukla, Shweta Ojha 2 Deptt. of Mathematc
More informationRao IIT Academy/ SSC - Board Exam 2018 / Mathematics Code-A / QP + Solutions JEE MEDICAL-UG BOARDS KVPY NTSE OLYMPIADS SSC - BOARD
Rao IIT Academy/ SSC - Board Exam 08 / Mathematcs Code-A / QP + Solutons JEE MEDICAL-UG BOARDS KVPY NTSE OLYMPIADS SSC - BOARD - 08 Date: 0.03.08 MATHEMATICS - PAPER- - SOLUTIONS Q. Attempt any FIVE of
More informationEGR 544 Communication Theory
EGR 544 Communcaton Theory. Informaton Sources Z. Alyazcoglu Electrcal and Computer Engneerng Department Cal Poly Pomona Introducton Informaton Source x n Informaton sources Analog sources Dscrete sources
More informationA Hybrid Variational Iteration Method for Blasius Equation
Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method
More informationChapter 11: Simple Linear Regression and Correlation
Chapter 11: Smple Lnear Regresson and Correlaton 11-1 Emprcal Models 11-2 Smple Lnear Regresson 11-3 Propertes of the Least Squares Estmators 11-4 Hypothess Test n Smple Lnear Regresson 11-4.1 Use of t-tests
More informationCopyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor
Taylor Enterprses, Inc. Control Lmts for P Charts Copyrght 2017 by Taylor Enterprses, Inc., All Rghts Reserved. Control Lmts for P Charts Dr. Wayne A. Taylor Abstract: P charts are used for count data
More information6.3.4 Modified Euler s method of integration
6.3.4 Modfed Euler s method of ntegraton Before dscussng the applcaton of Euler s method for solvng the swng equatons, let us frst revew the basc Euler s method of numercal ntegraton. Let the general from
More information6. Stochastic processes (2)
Contents Markov processes Brth-death processes Lect6.ppt S-38.45 - Introducton to Teletraffc Theory Sprng 5 Markov process Consder a contnuous-tme and dscrete-state stochastc process X(t) wth state space
More informationTwo Approaches to Proving. Goldbach s Conjecture
Two Approache to Provng Goldbach Conecture By Bernard Farley Adved By Charle Parry May 3 rd 5 A Bref Introducton to Goldbach Conecture In 74 Goldbach made h mot famou contrbuton n mathematc wth the conecture
More informationPractice Problems - Week #7 Laplace - Step Functions, DE Solutions Solutions
For Quetion -6, rewrite the piecewie function uing tep function, ketch their graph, and find F () = Lf(t). 0 0 < t < 2. f(t) = (t 2 4) 2 < t In tep-function form, f(t) = u 2 (t 2 4) The graph i the olid
More information6. Stochastic processes (2)
6. Stochastc processes () Lect6.ppt S-38.45 - Introducton to Teletraffc Theory Sprng 5 6. Stochastc processes () Contents Markov processes Brth-death processes 6. Stochastc processes () Markov process
More informationx = , so that calculated
Stat 4, secton Sngle Factor ANOVA notes by Tm Plachowsk n chapter 8 we conducted hypothess tests n whch we compared a sngle sample s mean or proporton to some hypotheszed value Chapter 9 expanded ths to
More informationImprovements on Waring s Problem
Imrovement on Warng Problem L An-Png Bejng 85, PR Chna al@nacom Abtract By a new recurve algorthm for the auxlary equaton, n th aer, we wll gve ome mrovement for Warng roblem Keyword: Warng Problem, Hardy-Lttlewood
More informationMore metrics on cartesian products
More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of
More informationProblem #1. Known: All required parameters. Schematic: Find: Depth of freezing as function of time. Strategy:
BEE 3500 013 Prelm Soluton Problem #1 Known: All requred parameter. Schematc: Fnd: Depth of freezng a functon of tme. Strategy: In thee mplfed analy for freezng tme, a wa done n cla for a lab geometry,
More informationChapter 7 Channel Capacity and Coding
Chapter 7 Channel Capacty and Codng Contents 7. Channel models and channel capacty 7.. Channel models Bnary symmetrc channel Dscrete memoryless channels Dscrete-nput, contnuous-output channel Waveform
More informationConvexity preserving interpolation by splines of arbitrary degree
Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete
More informationM. Mechee, 1,2 N. Senu, 3 F. Ismail, 3 B. Nikouravan, 4 and Z. Siri Introduction
Hndaw Publhng Corporaton Mathematcal Problem n Engneerng Volume 23, Artcle ID 795397, 7 page http://dx.do.org/.55/23/795397 Reearch Artcle A Three-Stage Ffth-Order Runge-Kutta Method for Drectly Solvng
More informationStatistics for Managers Using Microsoft Excel/SPSS Chapter 13 The Simple Linear Regression Model and Correlation
Statstcs for Managers Usng Mcrosoft Excel/SPSS Chapter 13 The Smple Lnear Regresson Model and Correlaton 1999 Prentce-Hall, Inc. Chap. 13-1 Chapter Topcs Types of Regresson Models Determnng the Smple Lnear
More informationCHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE
CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng
More informationProblem Free Expansion of Ideal Gas
Problem 4.3 Free Expanon o Ideal Ga In general: ds ds du P dv P dv NR V dn Snce U o deal ga ndependent on olume (du=), and N = cont n the proce: dv In a ere o nntemal ree expanon, entropy change by: S
More informationMarkov chains. Definition of a CTMC: [2, page 381] is a continuous time, discrete value random process such that for an infinitesimal
Markov chans M. Veeraraghavan; March 17, 2004 [Tp: Study the MC, QT, and Lttle s law lectures together: CTMC (MC lecture), M/M/1 queue (QT lecture), Lttle s law lecture (when dervng the mean response tme
More informationis the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors
Multple Lnear and Polynomal Regresson wth Statstcal Analyss Gven a set of data of measured (or observed) values of a dependent varable: y versus n ndependent varables x 1, x, x n, multple lnear regresson
More informationA note on almost sure behavior of randomly weighted sums of φ-mixing random variables with φ-mixing weights
ACTA ET COMMENTATIONES UNIVERSITATIS TARTUENSIS DE MATHEMATICA Volume 7, Number 2, December 203 Avalable onlne at http://acutm.math.ut.ee A note on almost sure behavor of randomly weghted sums of φ-mxng
More informationISSN X Reliability of linear and circular consecutive-kout-of-n systems with shock model
Afrka Statstka Vol. 101, 2015, pages 795 805. DOI: http://dx.do.org/10.16929/as/2015.795.70 Afrka Statstka ISSN 2316-090X Relablty of lnear and crcular consecutve-kout-of-n systems wth shock model Besma
More informationDigital Signal Processing
Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over
More informationNegative Binomial Regression
STATGRAPHICS Rev. 9/16/2013 Negatve Bnomal Regresson Summary... 1 Data Input... 3 Statstcal Model... 3 Analyss Summary... 4 Analyss Optons... 7 Plot of Ftted Model... 8 Observed Versus Predcted... 10 Predctons...
More informationFUZZY FINITE ELEMENT METHOD
FUZZY FINITE ELEMENT METHOD RELIABILITY TRUCTURE ANALYI UING PROBABILITY 3.. Maxmum Normal tress Internal force s the shear force, V has a magntude equal to the load P and bendng moment, M. Bendng moments
More informationProfit analysis of a computer system with preventive maintenance and priority subject to maximum operation and repair times
https://doorg/7/s4244-8--8 ORIGINAL ARTICLE Proft analyss of a computer system wth preventve mantenance and prorty subect to maxmum operaton and repar tmes Ashsh Kumar Monka San Receved: 27 November 27
More informationApplication of Queuing Theory to Waiting Time of Out-Patients in Hospitals.
Applcaton of Queung Theory to Watng Tme of Out-Patents n Hosptals. R.A. Adeleke *, O.D. Ogunwale, and O.Y. Hald. Department of Mathematcal Scences, Unversty of Ado-Ekt, Ado-Ekt, Ekt State, Ngera. E-mal:
More informationRELIABILITY ASSESSMENT
CHAPTER Rsk Analyss n Engneerng and Economcs RELIABILITY ASSESSMENT A. J. Clark School of Engneerng Department of Cvl and Envronmental Engneerng 4a CHAPMAN HALL/CRC Rsk Analyss for Engneerng Department
More informationReliability Analysis of Embedded System with Different Modes of Failure Emphasizing Reboot Delay
International Journal of Applied Science and Engineering 3., 4: 449-47 Reliability Analyi of Embedded Sytem with Different Mode of Failure Emphaizing Reboot Delay Deepak Kumar* and S. B. Singh Department
More informationMath 702 Midterm Exam Solutions
Math 702 Mdterm xam Solutons The terms measurable, measure, ntegrable, and almost everywhere (a.e.) n a ucldean space always refer to Lebesgue measure m. Problem. [6 pts] In each case, prove the statement
More informationFuzzy Reliability and Fuzzy Availability of the Serial Process in Butter-Oil Processing Plant
Journal of Mathematcs and Statstcs 5 (): 65-7, 2009 ISSN 549-3644 2009 Scence Publcatons uzzy Relablty and uzzy Avalablty of the Seral Process n Butter-Ol Processng Plant Kuldeep Kumar, 2 Ja Sngh and Pawan
More informationbounds compared to SB and SBB bounds as the former two have an index parameter, while the latter two
1 Queung Procee n GPS and PGPS wth LRD Traffc Input Xang Yu, Ian L-Jn Thng, Yumng Jang and Chunmng Qao Department of Computer Scence and Engneerng State Unverty of New York at Buffalo Department of Electrcal
More informationDEMO #8 - GAUSSIAN ELIMINATION USING MATHEMATICA. 1. Matrices in Mathematica
demo8.nb 1 DEMO #8 - GAUSSIAN ELIMINATION USING MATHEMATICA Obectves: - defne matrces n Mathematca - format the output of matrces - appl lnear algebra to solve a real problem - Use Mathematca to perform
More informationThe Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method
Journal of Electromagnetc Analyss and Applcatons, 04, 6, 0-08 Publshed Onlne September 04 n ScRes. http://www.scrp.org/journal/jemaa http://dx.do.org/0.46/jemaa.04.6000 The Exact Formulaton of the Inverse
More informationCS 798: Homework Assignment 2 (Probability)
0 Sample space Assgned: September 30, 2009 In the IEEE 802 protocol, the congeston wndow (CW) parameter s used as follows: ntally, a termnal wats for a random tme perod (called backoff) chosen n the range
More informationDelay Di erential Equations and Oscillations
Lecture 2 Delay D erental Equatons and Oscllatons Readng: Most of the materal n today s lecture comes from Chapter 1, pages 13 17 of James D. Murray (22), Mathematcal Bology I: An Introducton, 3rd edton.
More informationOpen Systems: Chemical Potential and Partial Molar Quantities Chemical Potential
Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,
More informationUncertainty in measurements of power and energy on power networks
Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:
More informationHongyi Miao, College of Science, Nanjing Forestry University, Nanjing ,China. (Received 20 June 2013, accepted 11 March 2014) I)ϕ (k)
ISSN 1749-3889 (prnt), 1749-3897 (onlne) Internatonal Journal of Nonlnear Scence Vol.17(2014) No.2,pp.188-192 Modfed Block Jacob-Davdson Method for Solvng Large Sparse Egenproblems Hongy Mao, College of
More informationA Novel Approach for Testing Stability of 1-D Recursive Digital Filters Based on Lagrange Multipliers
Amercan Journal of Appled Scence 5 (5: 49-495, 8 ISSN 546-939 8 Scence Publcaton A Novel Approach for Tetng Stablty of -D Recurve Dgtal Flter Baed on Lagrange ultpler KRSanth, NGangatharan and Ponnavakko
More informationarxiv: v1 [cs.gt] 15 Jan 2019
Model and algorthm for tme-content rk-aware Markov game Wenje Huang, Pham Vet Ha and Wllam B. Hakell January 16, 2019 arxv:1901.04882v1 [c.gt] 15 Jan 2019 Abtract In th paper, we propoe a model for non-cooperatve
More information