TESTING HYPOTHESIS ON STABILITY OF EXPECTED VALUE AND VARIANCE

Size: px
Start display at page:

Download "TESTING HYPOTHESIS ON STABILITY OF EXPECTED VALUE AND VARIANCE"

Transcription

1 B A D A N A O P E R A C Y J N E D E C Y Z J E N 6 Gzeoz KOŃCZAK* Jausz WYWAŁ* ENG HYPOHE ON ABLY O EXPECED VALUE AND VARANCE he smple samples ae depedetly tae om omal dstuto. he two utos o the sample meas ad sample aaes ae osdeed. he desty utos o these two statsts hae ee deed. hese statsts a e appled o ey the hypothess o stalty o expeted alue ad aae o omal dstuto osdeed e.. statstal poess otol. he tal alues o these statsts hae ee oud us umeal teato. he tales wth appoxmated tal alues o these statsts hae ee peseted. Keywods: desty uto sample aae test statst umeal teato statstal poess otol. toduto Oe o the polems o statstal poess otol s osdeed. t s a poedue so alled otol hats o moto stalty o the expeted alue ad the aae o daost aales. We assume that du the st peods the mea alues o a daost aale ae the same ut uow. he same stuato s wth the aae o the aale. he uased estmatos o the expeted alue µ ad the aae σ ealuated o the ass o data oseed the st peods ad the peod ae X Ŝ ad X ad espetely. Ou polem s the ollow: s the poess haatezed y the daost aale stale all o the peods? yes the dstaes: X X o should ot e sat. uh a polem s osdeed e.. []. Moe omally we hae the polem o test the hypothess * Depatmet o tatsts Katowe Uesty o Eooms ul. Boua -6 Katowe. oz@ae.atowe.pl wywal@ae.atowe.pl

2 7 G. KOŃCZAK J. WYWAŁ H : E X E X ad E E. We ae o to ostut a test statst o ths hypothess the ext paaaphs.. Bas detos ad popetes Let J a e a olum eto osst o a elemet eual oe ad let a e a ut matx o deee a. Moeoe let X [ X X... X... X ] whee X [ X X...X j...x ] j. We wll osde the ollow statsts: o X X j j XJ X X XJ whee j X j X j XMX M J J j whee M s the lo-daoal matx o deee ~ X X XMX M [ M ] XMX N M J J whee s the sample aae wth the -th oup Ŝ s the mea o oup aaes ad ~ s the aae etwee oups. Moeoe let us ote that M M M M ad N N. he patula ase o the theoem o depedee o the uadat o lea oms o omal etos oespod to ou polem s as ollows see [] pp. ad ext.

3 est hypothess o stalty o heoem. Let X hae a o-sula omal dstuto NµJ σ ad QA XAX QB XBX L Xa whee a s a olum o-adom eto A B ae symmet ad o-adom mates o deee eah. he the set o eessay ad suet odtos o Q A ad Q B to e depedetly dstuted s a AB O o ABJ O. he uadat om Q A ad the lea om L ae to e depedetly dstuted ad oly Aa O. O the ass o ths theoem we a show that the statsts the ollow pas ~ ae depedetly dstuted X ~ X. Moeoe the statsts X ae depedet ad they ae depedet o eah o the statsts X ~. ad he otaed esult ad the well ow detos let us dee the ollow dstutos: ad Moeoe X X Z : N. σ U U ~ : χ σ χ σ : U : χ σ. O the ass o these expessos we hae ~ Z σ : 5 Z σ : 6 : 7 ~ : 8

4 G. KOŃCZAK J. WYWAŁ 76 whee m deotes the well ow dstuto wth ad m deees o eedom ad the ollow desty uto: m m m m m. 9. he statsts Q ad Q Let us osde two statsts Q ad Q e as ollows ~ Z Q ~ Z Q whee ae deed y expessos 5 8 espetely. O the ass o the peous esults the dstutos o the adom aales Z U U ad U ae depedet. ally ths ad the at the samples ae depedet lead to the oluso that the dstutos o the statsts ad as well as the dstutos o ad ae depedet. he desty uto o adom aale s as ollows: whee A x A x x A.

5 est hypothess o stalty o he desty uto o adom aale s:. he desty utos o ad ae as ollows:. 5 whee ad. Let us dee the dstuto o adom aale. the we hae ad d d ad a. 6 Whe the we hae ± ad d. ] the ad o we hae.

6 G. KOŃCZAK J. WYWAŁ 78 [. 7 [ the. 8 We a wte the desty uto o the ollow way. 9 W: the the desty uto o W s e y expesso. Let V e the adom aale o dstuto wth ad - deees o eedom. he desty uto o V s e y 9. Now we ae o to ealuate the desty utos o the adom aale: Q W V. he desty uto o the statst Q s as ollows d h

7 est hypothess o stalty o h whee. mlaly the desty uto o Q s deed the ollow way. d h whee s the desty uto o [

8 G. KOŃCZAK J. WYWAŁ 8 ally the desty uto h o the statst Q s as ollows [ h whee. he dstuto utos o Q o Q ae ealuated y meas o the ollow teal < ds s h Q P H. 5 o the e sae leel α the uatl α s detemed o the ass o the teal: α α ds s h. 6. Numeal omputatos A exat soluto o euato 6 s ey dult. ths stuato the uatles o Q ad Q a e oud us umeal teato see e.. [] []. he ua-

9 est hypothess o stalty o... 8 tles wee oud o thee sae leels α..5.. ale pesets uatles o the statst Q ad ale pesets uatles o the statst Q. hese uatles wee ealuated o the ase 5. hese uatles hae ee ealuated o the umes o oups om to ad o 5 5 ad. Quatles o statst Q Nume o ae leel α oups ale he aph dsplay o uatles o statst Q o sae leel α..5 ad. he ue pesets uatles o the statst Q o the sae leels..5 ad.. hese uatles ae peseted o the same ases as ale. ue pesets the same esults as ue ut o the statst Q.

10 8 G. KOŃCZAK J. WYWAŁ ale Quatles o statst Q Nume o ae leel α oups he aph dsplay o uatles o statst Q o sae leel α..5 ad. Reeees [] BRAND. tatstal ad Computatoal Methods Data Aalyss pe Vela New Yo 997. [] DAHLQU G. BJORCK A. Numeal Methods Polsh PWN Waszawa 99. [] MAHA A.M. PROVO.B. Quadat oms adom aales Mael Dee. New Yo Basel Ho Ko 99. [] HOMPON J.R. KORONACK J. tatstal Poess Cotol: he Dem Paadm ad Beyod Chapma ad Hall/CRC New Yo Lodo.

11 est hypothess o stalty o... 8 estowae hpotezy o staloś watoś ozewaej waaj W pay jest ozważae zaadee jedozesej staloś watoś pzeętej waaj. Póy poste są poeae ezależe z populaj o ozładze omalym. Rozważa sę dwe uje śedej waaj z póy. Dla ozważayh statysty zostały wypowadzoe uje ęstoś. Popoowae statysty moą yć wyozystae do weyaj hpotezy o staloś watoś ozewaej waaj dla ozładu omaleo. Hpoteza taa może yć ozważaa p. w statystyzym steowau poesem pzy ostuj at otolyh. Badzo tude jest dołade wyzazee watyl ozważayh statysty. Dlateo watoś ytyze dla tyh statysty zostały wyzazoe dla tzeh zwyle używayh pozomów stotoś α 5 dla pó o lzeośah od do z wyozystaem ałowaa umeyzeo. Zapezetowao tale watoś ytyzyh dla tyh statysty. Zapopoowae statysty wyzazoe watoś ytyze moą yć óweż pzydate do wyywaa zma w poesah poduyjyh. łowa luzowe: uja ęstoś waaja z póy test umeyze ałowae statystyza otola poesu

SYSTEMS OF NON-LINEAR EQUATIONS. Introduction Graphical Methods Close Methods Open Methods Polynomial Roots System of Multivariable Equations

SYSTEMS OF NON-LINEAR EQUATIONS. Introduction Graphical Methods Close Methods Open Methods Polynomial Roots System of Multivariable Equations SYSTEMS OF NON-LINEAR EQUATIONS Itoduto Gaphal Method Cloe Method Ope Method Polomal Root Stem o Multvaale Equato Chapte Stem o No-Lea Equato /. Itoduto Polem volvg o-lea equato egeeg lude optmato olvg

More information

Professor Wei Zhu. 1. Sampling from the Normal Population

Professor Wei Zhu. 1. Sampling from the Normal Population AMS570 Pofesso We Zhu. Samplg fom the Nomal Populato *Example: We wsh to estmate the dstbuto of heghts of adult US male. It s beleved that the heght of adult US male follows a omal dstbuto N(, ) Def. Smple

More information

φ (x,y,z) in the direction of a is given by

φ (x,y,z) in the direction of a is given by UNIT-II VECTOR CALCULUS Dectoal devatve The devatve o a pot ucto (scala o vecto) a patcula decto s called ts dectoal devatve alo the decto. The dectoal devatve o a scala pot ucto a ve decto s the ate o

More information

CE 561 Lecture Notes. Optimal Timing of Investment. Set 3. Case A- C is const. cost in 1 st yr, benefits start at the end of 1 st yr

CE 561 Lecture Notes. Optimal Timing of Investment. Set 3. Case A- C is const. cost in 1 st yr, benefits start at the end of 1 st yr CE 56 Letue otes Set 3 Optmal Tmg of Ivestmet Case A- C s ost. ost st y, beefts stat at the ed of st y C b b b3 0 3 Case B- Cost. s postpoed by oe yea C b b3 0 3 (B-A C s saved st yea C C, b b 0 3 Savg

More information

Lattice planes. Lattice planes are usually specified by giving their Miller indices in parentheses: (h,k,l)

Lattice planes. Lattice planes are usually specified by giving their Miller indices in parentheses: (h,k,l) Ltte ples Se the epol ltte of smple u ltte s g smple u ltte d the Mlle des e the oodtes of eto oml to the ples, the use s ey smple lttes wth u symmety. Ltte ples e usully spefed y gg the Mlle des petheses:

More information

The Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof

The Linear Probability Density Function of Continuous Random Variables in the Real Number Field and Its Existence Proof MATEC Web of Cofeeces ICIEA 06 600 (06) DOI: 0.05/mateccof/0668600 The ea Pobablty Desty Fucto of Cotuous Radom Vaables the Real Numbe Feld ad Its Estece Poof Yya Che ad Ye Collee of Softwae, Taj Uvesty,

More information

On EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx

On EPr Bimatrices II. ON EP BIMATRICES A1 A Hence x. is said to be EP if it satisfies the condition ABx Iteatoal Joual of Mathematcs ad Statstcs Iveto (IJMSI) E-ISSN: 3 4767 P-ISSN: 3-4759 www.jms.og Volume Issue 5 May. 4 PP-44-5 O EP matces.ramesh, N.baas ssocate Pofesso of Mathematcs, ovt. ts College(utoomous),Kumbakoam.

More information

VECTOR MECHANICS FOR ENGINEERS: Vector Mechanics for Engineers: Dynamics. In the current chapter, you will study the motion of systems of particles.

VECTOR MECHANICS FOR ENGINEERS: Vector Mechanics for Engineers: Dynamics. In the current chapter, you will study the motion of systems of particles. Seeth Edto CHPTER 4 VECTOR MECHNICS FOR ENINEERS: DYNMICS Fedad P. ee E. Russell Johsto, J. Systems of Patcles Lectue Notes: J. Walt Ole Texas Tech Uesty 003 The Mcaw-Hll Compaes, Ic. ll ghts eseed. Seeth

More information

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi Assgmet /MATH 47/Wte Due: Thusday Jauay The poblems to solve ae umbeed [] to [] below Fst some explaatoy otes Fdg a bass of the colum-space of a max ad povg that the colum ak (dmeso of the colum space)

More information

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1

such that for 1 From the definition of the k-fibonacci numbers, the firsts of them are presented in Table 1. Table 1: First k-fibonacci numbers F 1 Scholas Joual of Egeeg ad Techology (SJET) Sch. J. Eg. Tech. 0; (C):669-67 Scholas Academc ad Scetfc Publshe (A Iteatoal Publshe fo Academc ad Scetfc Resouces) www.saspublshe.com ISSN -X (Ole) ISSN 7-9

More information

Objectives. Learning Outcome. 7.1 Centre of Gravity (C.G.) 7. Statics. Determine the C.G of a lamina (Experimental method)

Objectives. Learning Outcome. 7.1 Centre of Gravity (C.G.) 7. Statics. Determine the C.G of a lamina (Experimental method) Ojectves 7 Statcs 7. Cete of Gavty 7. Equlum of patcles 7.3 Equlum of g oes y Lew Sau oh Leag Outcome (a) efe cete of gavty () state the coto whch the cete of mass s the cete of gavty (c) state the coto

More information

Section 3. Measurement Errors

Section 3. Measurement Errors eto 3 Measuremet Errors Egeerg Measuremets 3 Types of Errors Itrs errors develops durg the data aqusto proess. Extrs errors foud durg data trasfer ad storage ad are due to the orrupto of the sgal y ose.

More information

Applied Mathematical Sciences, Vol. 2, 2008, no. 9, Parameter Estimation of Burr Type X Distribution for Grouped Data

Applied Mathematical Sciences, Vol. 2, 2008, no. 9, Parameter Estimation of Burr Type X Distribution for Grouped Data pplied Mathematical Scieces Vol 8 o 9 45-43 Paamete stimatio o Bu Type Distibutio o Gouped Data M ludaat M T lodat ad T T lodat 3 3 Depatmet o Statistics Yamou Uivesity Ibid Joda aludaatm@hotmailcom ad

More information

Analyzing Control Structures

Analyzing Control Structures Aalyzg Cotrol Strutures sequeg P, P : two fragmets of a algo. t, t : the tme they tae the tme requred to ompute P ;P s t t Θmaxt,t For loops for to m do P t: the tme requred to ompute P total tme requred

More information

Reliability Analysis of Structural Systems based on Universal Generating Function

Reliability Analysis of Structural Systems based on Universal Generating Function Iteatoal Joual of efomablty Egeeg Vol. 6, No. 3, ay 00, pp. 43-54. RAS osultats ted Ida Relablty Aalyss of Stutual Systems based o vesal Geeatg Futo JINY ZHO* Jagsu Teahe s vesty of Tehology, 80 Zhogwu

More information

Minimum Hyper-Wiener Index of Molecular Graph and Some Results on Szeged Related Index

Minimum Hyper-Wiener Index of Molecular Graph and Some Results on Szeged Related Index Joual of Multdscplay Egeeg Scece ad Techology (JMEST) ISSN: 359-0040 Vol Issue, Febuay - 05 Mmum Hype-Wee Idex of Molecula Gaph ad Some Results o eged Related Idex We Gao School of Ifomato Scece ad Techology,

More information

Best Linear Unbiased Estimators of the Three Parameter Gamma Distribution using doubly Type-II censoring

Best Linear Unbiased Estimators of the Three Parameter Gamma Distribution using doubly Type-II censoring Best Lea Ubased Estmatos of the hee Paamete Gamma Dstbuto usg doubly ype-ii cesog Amal S. Hassa Salwa Abd El-Aty Abstact Recetly ode statstcs ad the momets have assumed cosdeable teest may applcatos volvg

More information

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S Fomulae Fo u Pobablty By OP Gupta [Ida Awad We, +91-9650 350 480] Impotat Tems, Deftos & Fomulae 01 Bascs Of Pobablty: Let S ad E be the sample space ad a evet a expemet espectvely Numbe of favouable evets

More information

GCE AS and A Level MATHEMATICS FORMULA BOOKLET. From September Issued WJEC CBAC Ltd.

GCE AS and A Level MATHEMATICS FORMULA BOOKLET. From September Issued WJEC CBAC Ltd. GCE AS d A Level MATHEMATICS FORMULA BOOKLET Fom Septeme 07 Issued 07 Pue Mthemtcs Mesuto Suce e o sphee = 4 Ae o cuved suce o coe = heght slt Athmetc Sees S = + l = [ + d] Geometc Sees S = S = o < Summtos

More information

148 CIVIL ENGINEERING

148 CIVIL ENGINEERING STRUTUR NYSS fluee es fo Bems d Tusses fluee le sows te vto of effet (eto, se d momet ems, foe tuss) used movg ut lod oss te stutue. fluee le s used to deteme te posto of movele set of lods tt uses te

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

A Dynamical Quasi-Boolean System

A Dynamical Quasi-Boolean System ULETNUL Uestăţ Petol Gze Ploeşt Vol LX No / - 9 Se Mtetă - otă - Fză l Qs-oole Sste Gel Mose Petole-Gs Uest o Ploest ots etet est 39 Ploest 68 o el: ose@-loesto stt Ths e oes the esto o ol theoetl oet:

More information

Council for Innovative Research

Council for Innovative Research Geometc-athmetc Idex ad Zageb Idces of Ceta Specal Molecula Gaphs efe X, e Gao School of Tousm ad Geogaphc Sceces, Yua Nomal Uesty Kumg 650500, Cha School of Ifomato Scece ad Techology, Yua Nomal Uesty

More information

SOME REMARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOMIAL ASYMPTOTE

SOME REMARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOMIAL ASYMPTOTE D I D A C T I C S O F A T H E A T I C S No (4) 3 SOE REARKS ON HORIZONTAL, SLANT, PARABOLIC AND POLYNOIAL ASYPTOTE Tdeusz Jszk Abstct I the techg o clculus, we cosde hozotl d slt symptote I ths ppe the

More information

The formulae in this booklet have been arranged according to the unit in which they are first

The formulae in this booklet have been arranged according to the unit in which they are first Fomule Booklet Fomule Booklet The fomule ths ooklet hve ee ge og to the ut whh the e fst toue. Thus te sttg ut m e eque to use the fomule tht wee toue peeg ut e.g. tes sttg C mght e epete to use fomule

More information

Chapter 14 Logistic Regression Models

Chapter 14 Logistic Regression Models Chapter 4 Logstc Regresso Models I the lear regresso model X β + ε, there are two types of varables explaatory varables X, X,, X k ad study varable y These varables ca be measured o a cotuous scale as

More information

LECTURE 8: Topics in Chaos Ricker Equation. Period doubling bifurcation. Period doubling cascade. A Quadratic Equation Ricker Equation 1.0. x x 4 0.

LECTURE 8: Topics in Chaos Ricker Equation. Period doubling bifurcation. Period doubling cascade. A Quadratic Equation Ricker Equation 1.0. x x 4 0. LECTURE 8: Topcs Chaos Rcker Equato (t ) = (t ) ep( (t )) Perod doulg urcato Perod doulg cascade 9....... A Quadratc Equato Rcker Equato (t ) = (t ) ( (t ) ). (t ) = (t ) ep( (t )) 6. 9 9. The perod doulg

More information

Estimation of Population Mean with. a New Imputation Method

Estimation of Population Mean with. a New Imputation Method Aled Mathematal Sees, Vol. 9, 015, o. 34, 1663-167 HIKARI Ltd, www.m-hka.om htt://d.do.og/10.1988/ams.015.593 Estmato of Poulato Mea wth a New Imutato Method Abdeltawab A. Ga Isttute of Statstal Studes

More information

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then Secto 5 Vectors of Radom Varables Whe workg wth several radom varables,,..., to arrage them vector form x, t s ofte coveet We ca the make use of matrx algebra to help us orgaze ad mapulate large umbers

More information

Simple Linear Regression Analysis

Simple Linear Regression Analysis LINEAR REGREION ANALYSIS MODULE II Lecture - 5 Smple Lear Regreo Aaly Dr Shalabh Departmet of Mathematc Stattc Ida Ittute of Techology Kapur Jot cofdece rego for A jot cofdece rego for ca alo be foud Such

More information

Dr. Shalabh. Indian Institute of Technology Kanpur

Dr. Shalabh. Indian Institute of Technology Kanpur Aalyss of Varace ad Desg of Expermets-I MODULE -I LECTURE - SOME RESULTS ON LINEAR ALGEBRA, MATRIX THEORY AND DISTRIBUTIONS Dr. Shalabh Departmet t of Mathematcs t ad Statstcs t t Ida Isttute of Techology

More information

Lecture 9 Multiple Class Models

Lecture 9 Multiple Class Models Lectue 9 Multple Class Models Multclass MVA Appoxmate MVA 8.4.2002 Copyght Teemu Keola 2002 1 Aval Theoem fo Multple Classes Wth jobs the system, a job class avg to ay seve sees the seve as equlbum wth

More information

LOAD-FLOW CALCULATIONS IN MESHED SYSTEMS Node voltage method A system part with the node k and its direct neighbour m

LOAD-FLOW CALCULATIONS IN MESHED SYSTEMS Node voltage method A system part with the node k and its direct neighbour m LOAD-FLOW CALCLATIONS IN MESHED SYSTEMS Node oltage method A system part wth the ode ad ts dret eghbor m Î Îm Î m m Crrets Î m m m Î Î m m m m Î m m m m m m m Let s dee the ode sel-admttae (adm. matr dagoal

More information

= y and Normed Linear Spaces

= y and Normed Linear Spaces 304-50 LINER SYSTEMS Lectue 8: Solutos to = ad Nomed Lea Spaces 73 Fdg N To fd N, we eed to chaacteze all solutos to = 0 Recall that ow opeatos peseve N, so that = 0 = 0 We ca solve = 0 ecusvel backwads

More information

Fairing of Parametric Quintic Splines

Fairing of Parametric Quintic Splines ISSN 46-69 Eglad UK Joual of Ifomato ad omputg Scece Vol No 6 pp -8 Fag of Paametc Qutc Sples Yuau Wag Shagha Isttute of Spots Shagha 48 ha School of Mathematcal Scece Fuda Uvesty Shagha 4 ha { P t )}

More information

DANIEL YAQUBI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD

DANIEL YAQUBI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD MIXED -STIRLING NUMERS OF THE SEOND KIND DANIEL YAQUI, MADJID MIRZAVAZIRI AND YASIN SAEEDNEZHAD Abstact The Stilig umbe of the secod id { } couts the umbe of ways to patitio a set of labeled balls ito

More information

Counting Functions and Subsets

Counting Functions and Subsets CHAPTER 1 Coutig Fuctios ad Subsets This chapte of the otes is based o Chapte 12 of PJE See PJE p144 Hee ad below, the efeeces to the PJEccles book ae give as PJE The goal of this shot chapte is to itoduce

More information

Minimizing spherical aberrations Exploiting the existence of conjugate points in spherical lenses

Minimizing spherical aberrations Exploiting the existence of conjugate points in spherical lenses Mmzg sphecal abeatos Explotg the exstece of cojugate pots sphecal leses Let s ecall that whe usg asphecal leses, abeato fee magg occus oly fo a couple of, so called, cojugate pots ( ad the fgue below)

More information

Range Symmetric Matrices in Minkowski Space

Range Symmetric Matrices in Minkowski Space BULLETIN of the Bull. alaysia ath. Sc. Soc. (Secod Seies) 3 (000) 45-5 LYSIN THETICL SCIENCES SOCIETY Rae Symmetic atices i ikowski Space.R. EENKSHI Depatmet of athematics, amalai Uivesity, amalaiaa 608

More information

Department of Mathematics UNIVERSITY OF OSLO. FORMULAS FOR STK4040 (version 1, September 12th, 2011) A - Vectors and matrices

Department of Mathematics UNIVERSITY OF OSLO. FORMULAS FOR STK4040 (version 1, September 12th, 2011) A - Vectors and matrices Deartet of Matheatcs UNIVERSITY OF OSLO FORMULAS FOR STK4040 (verso Seteber th 0) A - Vectors ad atrces A) For a x atrx A ad a x atrx B we have ( AB) BA A) For osgular square atrces A ad B we have ( )

More information

χ be any function of X and Y then

χ be any function of X and Y then We have show that whe we ae gve Y g(), the [ ] [ g() ] g() f () Y o all g ()() f d fo dscete case Ths ca be eteded to clude fuctos of ay ube of ado vaables. Fo eaple, suppose ad Y ae.v. wth jot desty fucto,

More information

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures.

are positive, and the pair A, B is controllable. The uncertainty in is introduced to model control failures. Lectue 4 8. MRAC Desg fo Affe--Cotol MIMO Systes I ths secto, we cosde MRAC desg fo a class of ult-ut-ult-outut (MIMO) olea systes, whose lat dyacs ae lealy aaetezed, the ucetates satsfy the so-called

More information

The Geometric Proof of the Hecke Conjecture

The Geometric Proof of the Hecke Conjecture The Geometc Poof of the Hecke Cojectue Kada Sh Depatmet of Mathematc Zhejag Ocea Uvety Zhouha Cty 6 Zhejag Povce Cha Atact Begg fom the eoluto of Dchlet fucto ug the e poduct fomula of two fte-dmeoal vecto

More information

FIXED POINT AND HYERS-ULAM-RASSIAS STABILITY OF A QUADRATIC FUNCTIONAL EQUATION IN BANACH SPACES

FIXED POINT AND HYERS-ULAM-RASSIAS STABILITY OF A QUADRATIC FUNCTIONAL EQUATION IN BANACH SPACES IJRRAS 6 () July 0 www.apapess.com/volumes/vol6issue/ijrras_6.pdf FIXED POINT AND HYERS-UAM-RASSIAS STABIITY OF A QUADRATIC FUNCTIONA EQUATION IN BANACH SPACES E. Movahedia Behbaha Khatam Al-Abia Uivesity

More information

XII. Addition of many identical spins

XII. Addition of many identical spins XII. Addto of may detcal sps XII.. ymmetc goup ymmetc goup s the goup of all possble pemutatos of obects. I total! elemets cludg detty opeato. Each pemutato s a poduct of a ceta fte umbe of pawse taspostos.

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

Unsupervised Learning and Other Neural Networks

Unsupervised Learning and Other Neural Networks CSE 53 Soft Computg NOT PART OF THE FINAL Usupervsed Learg ad Other Neural Networs Itroducto Mture Destes ad Idetfablty ML Estmates Applcato to Normal Mtures Other Neural Networs Itroducto Prevously, all

More information

Introduction to Matrices and Matrix Approach to Simple Linear Regression

Introduction to Matrices and Matrix Approach to Simple Linear Regression Itroducto to Matrces ad Matrx Approach to Smple Lear Regresso Matrces Defto: A matrx s a rectagular array of umbers or symbolc elemets I may applcatos, the rows of a matrx wll represet dvduals cases (people,

More information

SOLVING SYSTEMS OF EQUATIONS, DIRECT METHODS

SOLVING SYSTEMS OF EQUATIONS, DIRECT METHODS ELM Numecl Alyss D Muhem Mecmek SOLVING SYSTEMS OF EQUATIONS DIRECT METHODS ELM Numecl Alyss Some of the cotets e dopted fom Luee V. Fusett Appled Numecl Alyss usg MATLAB. Petce Hll Ic. 999 ELM Numecl

More information

PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM

PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM Joual o Mathematcal Sceces: Advaces ad Applcatos Volume 6 Numbe 00 Pages 77-9 PENALTY FUNCTIONS FOR THE MULTIOBJECTIVE OPTIMIZATION PROBLEM DAU XUAN LUONG ad TRAN VAN AN Depatmet o Natual Sceces Quag Nh

More information

Chapter 5. Long Waves

Chapter 5. Long Waves ape 5. Lo Waes Wae e s o compaed ae dep: < < L π Fom ea ae eo o s s ; amos ozoa moo z p s ; dosac pesse Dep-aeaed coseao o mass

More information

Robust Feedback Linearization

Robust Feedback Linearization 4th WSEAS It Co o NON-LINEAR ANALYSIS NON-LINEAR SYSEMS ad CHAOS Soa laa Otobe 7-9 5 pp4-9 Robst Feedbak Leazato M A AAEI R ESMAEILZAEH GH ALIZAEH Isaha Reoal Elet Compa Azabaja Reoal Elet Compa Falt o

More information

5 - Determinants. r r. r r. r r. r s r = + det det det

5 - Determinants. r r. r r. r r. r s r = + det det det 5 - Detemts Assote wth y sque mtx A thee s ume lle the etemt of A eote A o et A. Oe wy to efe the etemt, ths futo fom the set of ll mtes to the set of el umes, s y the followg thee popetes. All mtes elow

More information

YEAR VSA (1 Mark) SA (4 Marks) LA (6 Marks) Total Marks

YEAR VSA (1 Mark) SA (4 Marks) LA (6 Marks) Total Marks VECTOR ALGEBRA D Weghtge 7 Ms SYLLABUS: VECTOR ALGEBRA Vetos sls, mgtue eto of veto Deto oses eto tos of veto Tpes of vetos (equl, ut, eo, pllel olle vetos, posto veto of pot, egtve of veto, ompoets of

More information

Non-axial symmetric loading on axial symmetric. Final Report of AFEM

Non-axial symmetric loading on axial symmetric. Final Report of AFEM No-axal symmetc loadg o axal symmetc body Fal Repot of AFEM Ths poject does hamoc aalyss of o-axal symmetc loadg o axal symmetc body. Shuagxg Da, Musket Kamtokat 5//009 No-axal symmetc loadg o axal symmetc

More information

Crosscorrelation of m-sequences, Exponential sums and Dickson

Crosscorrelation of m-sequences, Exponential sums and Dickson Cosscoelatio o m-equeces, Epoetial sums ad Dicso polyomials To Helleseth Uiesity o Bege NORWAY Joit wo with Aia Johase ad Aleade Kholosha Itoductio Outlie m-sequeces Coelatio o sequeces Popeties o m-sequeces

More information

of the contestants play as Falco, and 1 6

of the contestants play as Falco, and 1 6 JHMT 05 Algeba Test Solutions 4 Febuay 05. In a Supe Smash Bothes tounament, of the contestants play as Fox, 3 of the contestants play as Falco, and 6 of the contestants play as Peach. Given that thee

More information

MATH Midterm Solutions

MATH Midterm Solutions MATH 2113 - Midtem Solutios Febuay 18 1. A bag of mables cotais 4 which ae ed, 4 which ae blue ad 4 which ae gee. a How may mables must be chose fom the bag to guaatee that thee ae the same colou? We ca

More information

Chapter 1 Counting Methods

Chapter 1 Counting Methods AlbertLudwgs Uversty Freburg Isttute of Empral Researh ad Eoometrs Dr. Sevtap Kestel Mathematal Statsts - Wter 2008 Chapter Coutg Methods Am s to determe how may dfferet possbltes there are a gve stuato.

More information

Debabrata Dey and Atanu Lahiri

Debabrata Dey and Atanu Lahiri RESEARCH ARTICLE QUALITY COMPETITION AND MARKET SEGMENTATION IN THE SECURITY SOFTWARE MARKET Debabrata Dey ad Atau Lahr Mchael G. Foster School of Busess, Uersty of Washgto, Seattle, Seattle, WA 9895 U.S.A.

More information

T T V e g em D e j ) a S D } a o "m ek j g ed b m "d mq m [ d, )

T T V e g em D e j ) a S D } a o m ek j g ed b m d mq m [ d, ) . ) 6 3 ; 6 ;, G E E W T S W X D ^ L J R Y [ _ ` E ) '" " " -, 7 4-4 4-4 ; ; 7 4 4 4 4 4 ;= : " B C CA BA " ) 3D H E V U T T V e g em D e j ) a S D } a o "m ek j g ed b m "d mq m [ d, ) W X 6 G.. 6 [ X

More information

EVALUATION OF SUMS INVOLVING GAUSSIAN q-binomial COEFFICIENTS WITH RATIONAL WEIGHT FUNCTIONS

EVALUATION OF SUMS INVOLVING GAUSSIAN q-binomial COEFFICIENTS WITH RATIONAL WEIGHT FUNCTIONS EVALUATION OF SUMS INVOLVING GAUSSIAN -BINOMIAL COEFFICIENTS WITH RATIONAL WEIGHT FUNCTIONS EMRAH KILIÇ AND HELMUT PRODINGER Abstact We coside sums of the Gaussia -biomial coefficiets with a paametic atioal

More information

SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES

SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES #A17 INTEGERS 9 2009), 181-190 SOME ARITHMETIC PROPERTIES OF OVERPARTITION K -TUPLES Deick M. Keiste Depatmet of Mathematics, Pe State Uivesity, Uivesity Pak, PA 16802 dmk5075@psu.edu James A. Selles Depatmet

More information

Fredholm Type Integral Equations with Aleph-Function. and General Polynomials

Fredholm Type Integral Equations with Aleph-Function. and General Polynomials Iteto Mthetc Fou Vo. 8 3 o. 989-999 HIKI Ltd.-h.co Fedho Te Iteg uto th eh-fucto d Gee Poo u J K.J. o Ittute o Mgeet tude & eech Mu Id u5@g.co Kt e K.J. o Ittute o Mgeet tude & eech Mu Id dehuh_3@hoo.co

More information

Linear Approximating to Integer Addition

Linear Approximating to Integer Addition Lear Approxmatg to Iteger Addto L A-Pg Bejg 00085, P.R. Cha apl000@a.com Abtract The teger addto ofte appled cpher a a cryptographc mea. I th paper we wll preet ome reult about the lear approxmatg for

More information

Mixed Integer Optimal Control in Minimum Time Multi-points Traversal Problem of Robotic Manipulators 1

Mixed Integer Optimal Control in Minimum Time Multi-points Traversal Problem of Robotic Manipulators 1 Pepts o the 9th Wold Cogess he Iteatoal Fedeato o Automat Cotol Cape ow South Aa August 4-9 04 Mxed Itege Optmal Cotol Mmum me Mult-pots avesal Poblem o Robot Mapulatos Qag Zhag * Shuog L * Jax Guo **

More information

Assignment 7/MATH 247/Winter, 2010 Due: Friday, March 19. Powers of a square matrix

Assignment 7/MATH 247/Winter, 2010 Due: Friday, March 19. Powers of a square matrix Assgmet 7/MATH 47/Wter, 00 Due: Frday, March 9 Powers o a square matrx Gve a square matrx A, ts powers A or large, or eve arbtrary, teger expoets ca be calculated by dagoalzg A -- that s possble (!) Namely,

More information

ENGI 4430 Non-Cartesian Coordinates Page xi Fy j Fzk from Cartesian coordinates z to another orthonormal coordinate system u, v, ˆ i ˆ ˆi

ENGI 4430 Non-Cartesian Coordinates Page xi Fy j Fzk from Cartesian coordinates z to another orthonormal coordinate system u, v, ˆ i ˆ ˆi ENGI 44 Non-Catesian Coodinates Page 7-7. Conesions between Coodinate Systems In geneal, the conesion of a ecto F F xi Fy j Fzk fom Catesian coodinates x, y, z to anothe othonomal coodinate system u,,

More information

Lecture 7: Linear and quadratic classifiers

Lecture 7: Linear and quadratic classifiers Lecture 7: Lear ad quadratc classfers Bayes classfers for ormally dstrbuted classes Case : Σ σ I Case : Σ Σ (Σ daoal Case : Σ Σ (Σ o-daoal Case 4: Σ σ I Case 5: Σ Σ j eeral case Lear ad quadratc classfers:

More information

2.Decision Theory of Dependence

2.Decision Theory of Dependence .Deciio Theoy of Depedece Theoy :I et of vecto if thee i uet which i liely depedet the whole et i liely depedet too. Coolly :If the et i liely idepedet y oepty uet of it i liely idepedet. Theoy : Give

More information

Lecture Notes 2. The ability to manipulate matrices is critical in economics.

Lecture Notes 2. The ability to manipulate matrices is critical in economics. Lecture Notes. Revew of Matrces he ablt to mapulate matrces s crtcal ecoomcs.. Matr a rectagular arra of umbers, parameters, or varables placed rows ad colums. Matrces are assocated wth lear equatos. lemets

More information

c- : r - C ' ',. A a \ V

c- : r - C ' ',. A a \ V HS PAGE DECLASSFED AW EO 2958 c C \ V A A a HS PAGE DECLASSFED AW EO 2958 HS PAGE DECLASSFED AW EO 2958 = N! [! D!! * J!! [ c 9 c 6 j C v C! ( «! Y y Y ^ L! J ( ) J! J ~ n + ~ L a Y C + J " J 7 = [ " S!

More information

Properties of the natural logarithm and exponential functions

Properties of the natural logarithm and exponential functions Poeties of the natual logaithm an eonential functions Define fo ositive the function A() as the aea fom to une the hyeolay Since thee is no with, A() 0 By efinition the eivative of A() is given y the limit

More information

Bayesian Analysis of Simple Random Densities

Bayesian Analysis of Simple Random Densities Ope Joual of Statstcs 4 4 377-39 Pulshed Ole ugust 4 ScRes http://wwwscpog/joual/ojs http://dxdoog/436/ojs44537 Bayesa alyss of Smple Radom Destes Paulo C Maques F Calos de B Peea Depatameto de Estatístca

More information

ENGI 4430 Numerical Integration Page 5-01

ENGI 4430 Numerical Integration Page 5-01 ENGI 443 Numercal Itegrato Page 5-5. Numercal Itegrato I some o our prevous work, (most otaly the evaluato o arc legth), t has ee dcult or mpossle to d the dete tegral. Varous symolc algera ad calculus

More information

E-Companion: Mathematical Proofs

E-Companion: Mathematical Proofs E-omnon: Mthemtcl Poo Poo o emm : Pt DS Sytem y denton o t ey to vey tht t ncee n wth d ncee n We dene } ] : [ { M whee / We let the ttegy et o ech etle n DS e ]} [ ] [ : { M w whee M lge otve nume oth

More information

Mathematical Statistics

Mathematical Statistics Mathematal Statsts 2 1 Chapter II Probablty 21 Bas Coepts The dsple of statsts deals wth the olleto ad aalyss of data Whe measuremets are tae, eve seemgly uder the same odtos, the results usually vary

More information

Using Difference Equations to Generalize Results for Periodic Nested Radicals

Using Difference Equations to Generalize Results for Periodic Nested Radicals Usig Diffeece Equatios to Geealize Results fo Peiodic Nested Radicals Chis Lyd Uivesity of Rhode Islad, Depatmet of Mathematics South Kigsto, Rhode Islad 2 2 2 2 2 2 2 π = + + +... Vieta (593) 2 2 2 =

More information

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b CS 70 Dscrete Mathematcs ad Probablty Theory Fall 206 Sesha ad Walrad DIS 0b. Wll I Get My Package? Seaky delvery guy of some compay s out delverg packages to customers. Not oly does he had a radom package

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

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic Covergece of the Desrozers scheme ad ts relato to the lag ovato dagostc chard Méard Evromet Caada, Ar Qualty esearch Dvso World Weather Ope Scece Coferece Motreal, August 9, 04 o t t O x x x y x y Oservato

More information

MATH /19: problems for supervision in week 08 SOLUTIONS

MATH /19: problems for supervision in week 08 SOLUTIONS MATH10101 2018/19: poblems fo supevisio i week 08 Q1. Let A be a set. SOLUTIONS (i Pove that the fuctio c: P(A P(A, defied by c(x A \ X, is bijective. (ii Let ow A be fiite, A. Use (i to show that fo each

More information

Lecture 10: Condensed matter systems

Lecture 10: Condensed matter systems Lectue 0: Codesed matte systems Itoducg matte ts codesed state.! Ams: " Idstgushable patcles ad the quatum atue of matte: # Cosequeces # Revew of deal gas etopy # Femos ad Bosos " Quatum statstcs. # Occupato

More information

Spring Ammar Abu-Hudrouss Islamic University Gaza

Spring Ammar Abu-Hudrouss Islamic University Gaza ١ ١ Chapter Chapter 4 Cyl Blo Cyl Blo Codes Codes Ammar Abu-Hudrouss Islam Uversty Gaza Spr 9 Slde ٢ Chael Cod Theory Cyl Blo Codes A yl ode s haraterzed as a lear blo ode B( d wth the addtoal property

More information

Hyper-wiener index of gear fan and gear wheel related graph

Hyper-wiener index of gear fan and gear wheel related graph Iteatoal Joual of Chemcal Studes 015; (5): 5-58 P-ISSN 49 858 E-ISSN 1 490 IJCS 015; (5): 5-58 014 JEZS Receed: 1-0-015 Accepted: 15-0-015 We Gao School of Ifomato Scece ad Techology, Yua Nomal Uesty,

More information

A NOTE ON DOMINATION PARAMETERS IN RANDOM GRAPHS

A NOTE ON DOMINATION PARAMETERS IN RANDOM GRAPHS Discussioes Mathematicae Gaph Theoy 28 (2008 335 343 A NOTE ON DOMINATION PARAMETERS IN RANDOM GRAPHS Athoy Boato Depatmet of Mathematics Wilfid Lauie Uivesity Wateloo, ON, Caada, N2L 3C5 e-mail: aboato@oges.com

More information

UNIT10 PLANE OF REGRESSION

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

More information

Finite q-identities related to well-known theorems of Euler and Gauss. Johann Cigler

Finite q-identities related to well-known theorems of Euler and Gauss. Johann Cigler Fiite -idetities elated to well-ow theoems of Eule ad Gauss Joha Cigle Faultät fü Mathemati Uivesität Wie A-9 Wie, Nodbegstaße 5 email: oha.cigle@uivie.ac.at Abstact We give geealizatios of a fiite vesio

More information

Chapter 10 Two Stage Sampling (Subsampling)

Chapter 10 Two Stage Sampling (Subsampling) Chapter 0 To tage amplg (usamplg) I cluster samplg, all the elemets the selected clusters are surveyed oreover, the effcecy cluster samplg depeds o sze of the cluster As the sze creases, the effcecy decreases

More information

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance Chapter, Part A Aalyss of Varace ad Epermetal Desg Itroducto to Aalyss of Varace Aalyss of Varace: Testg for the Equalty of Populato Meas Multple Comparso Procedures Itroducto to Aalyss of Varace Aalyss

More information

A New Result On A,p n,δ k -Summabilty

A New Result On A,p n,δ k -Summabilty OSR Joual of Matheatics (OSR-JM) e-ssn: 2278-5728, p-ssn:239-765x. Volue 0, ssue Ve. V. (Feb. 204), PP 56-62 www.iosjouals.og A New Result O A,p,δ -Suabilty Ripeda Kua &Aditya Kua Raghuashi Depatet of

More information

Sebastián Martín Ruiz. Applications of Smarandache Function, and Prime and Coprime Functions

Sebastián Martín Ruiz. Applications of Smarandache Function, and Prime and Coprime Functions Sebastá Martí Ruz Alcatos of Saradache Fucto ad Pre ad Core Fuctos 0 C L f L otherwse are core ubers Aerca Research Press Rehoboth 00 Sebastá Martí Ruz Avda. De Regla 43 Choa 550 Cadz Sa Sarada@telele.es

More information

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings. T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

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

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

More information

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS Joa of Aed Mahema ad Comaoa Meha 4 3( 6-73 APPLCATON OF A Z-TRANSFORMS METHOD FOR NVESTGATON OF MARKOV G-NETWORKS Mha Maay Vo Nameo e of Mahema Ceohowa Uey of Tehoogy Cęohowa Poad Fay of Mahema ad Come

More information

Java Applets / Flash Java Applet vs. Flash

Java Applets / Flash Java Applet vs. Flash ava Alet / Flah ava Alet v. Flah oltal oblem wth Mooft hhl otable moe dfflt develomet ot a oblem le o exellet val develomet tool Alet / Flah ood fo tato volv omlex e t whee XTML t elemet ae ot adeqate

More information

Design of CMOS Analog Integrated Circuits. Basic Building Block

Design of CMOS Analog Integrated Circuits. Basic Building Block Desin of CMOS Analo Inteated Cicuits Fanco Malobeti Basic Buildin Block F. Malobeti : Desin of CMOS Analo Inteated Cicuits - Basic Buildin Block INERTER WITH ACTIE LOAD The simplest fom of ain stae, the

More information

14. MRAC for MIMO Systems with Unstructured Uncertainties We consider affine-in-control MIMO systems in the form, x Ax B u f x t

14. MRAC for MIMO Systems with Unstructured Uncertainties We consider affine-in-control MIMO systems in the form, x Ax B u f x t Lectue 8 14. MAC o MIMO Systes wth Ustuctued Ucetates We cosde ae--cotol MIMO systes the o, ABu t (14.1) whee s the syste state vecto, u s the cotol put, B s kow costat at, A ad (a dagoal at wth postve

More information

By the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences

By the end of this section you will be able to prove the Chinese Remainder Theorem apply this theorem to solve simultaneous linear congruences Chapte : Theoy of Modula Aithmetic 8 Sectio D Chiese Remaide Theoem By the ed of this sectio you will be able to pove the Chiese Remaide Theoem apply this theoem to solve simultaeous liea cogueces The

More information