Direct Partial Modal Approach for Solving. Generalized First Order Systems

Size: px
Start display at page:

Download "Direct Partial Modal Approach for Solving. Generalized First Order Systems"

Transcription

1 Iteratoal Matheatcal Foru Vol. 7 o Drect Partal Modal pproach for Solvg Geeralzed Frst Order Sstes ha. l-saed ad M. Modather M. dou Departet of Matheatcs College of Scece ad uatara Studes Sala B dulazz Uverst l-khar Saud raa stract. I ths Research we propose a explct soluto to the partal egevalue assget prole for o-setrc geeralzed frst order cotrol sstes sgleput case usg orthogoalt relatos etwee egevectors. Our soluto ca e pleeted wth ol a partal owledge of the egevalues ad the correspodg egevectors of geeralzed frst order cotrol sstes. We show that the uer of egevalues ad egevectors that eed to rea uchaged wll ot e affected feedac atrces. We prove the feedac atrx ust e of real for. uercal exaple s gve to llustrate the proposed ethod. Kewords: explct soluto- partal egevalue assget- sgle put. Itroducto he frst order atrx dfferetal equato v& t v t (.) ( ) ( ) eads wth the separato of varales v( t) t xe x a costat vector to the prole of fdg the egevalues ad egevectors of the lear pecl P( ) (.) he scalar s called a egevalue ad the correspodg vector x s called a egevector f the satsf P( ) x (.3) ere we assue that are real o-setrc costat atrces wth s osgular. he sste (.) ca e cotrolled wth applcato of a forcg Correspodg author ha. l-saed: -al address: ha_ath@ahoo.co Peraet address: Departet of Scece ad Matheatcs Facult of Petroleu geerg Suez Caal Uverst gpt

2 .. l-saed ad M. M. M. dou fucto u () t replaced R a costat ad ( t) ( t) v( t) u( t) u a scalar whch case (.) s v& + (.4) hs prole s called geeralzed lear state space sste also called descrptor sste. he sste (.4) s cotrollale.e. ra ( ) C. for Descrptor sstes arse for exaple odelg tercoected sstes ad ecooc processes [89]. B susttutg u fv to (.4) ad the choce of the cotrol vector f R costat leads to closed loop sste ( t) ( f ) v( t) v& (.5) hs prole leads wth the separato of varales of closed pecl P c ( ) ( f ) ; (.6) I a realstc stuato however ol a few egevalues are troulesoe so t aes ore sese to alter ol those troulesoe egevalues whle eepg the rest of the spectru varat. hs leads to ow as the partal egevalue assget prole [3]. Matheatcall gve the lear pecl Ω ( ) { } ad set{ } + P( ) whose spectru closed uder coplex cougato. he the partal egevalue assget prole for the geeralzed lear sste requres us to fd the feedac vector ( f ) { } + Ω. f such that M.. Raada ad ha. l-saed [4] troduced a explct soluto to the partal egevalue assget prole of the sste (.4) the specal case f I where I s dett atrx the sste (.4) has the stadard frst order sste the for v & t v t + u t. (.7) ( ) ( ) ( ) he soluto of the partal egevalue assget prole ca e otaed usg ol a partal owledge of egevalues ad egevectors of the lear

3 Drect partal odal approach pecl P( ) wthout usg a proecto ethods [5 6]. soluto techque of ths tpe wll e called a drect partal odal approach t s drect ecause the soluto s otaed drectl wthout usg a tpes of reforulatos or proecto. It s partal odal ecause ol a part of the egevalues ad egevectors s eeded for soluto [].. Orthogoalt Relatos For Geeralzed No Setrc geprole hs secto troduce orthogoalt relatos for geeralzed egevalue prole Defto (). et ad e ( ) x ( ) x P. (.) atrces. scalar s called a geeralzed egevalue ad a o zero colu vector x s called the rght geeralzed egevector correspodg to f Defto (). et ad e x x (.3) atrces. scalar s called a geeralzed egevalue ad a o zero colu vector satsfg (.4) s called the left geeralzed egevector correspodg to where s the cougate traspose of the vector. Defto (3). scalar C s a egevalue of the lear pecl P( ) wth the correspodg rght egevector x ad the left egevector. Defto (4). he trplet ( x ) Defto (5). he pars ( x) ad ( ) egepars of P. s called the egepar of P. Defto (6). he pecl P s called sgular f for a sgular.e. det ( ) are called respectvel rght ad left the C the atrx P ( ) s. Otherwse the pecl P s called regular. I ths paper we restrct ourselves to regular P.

4 .. l-saed ad M. M. M. dou If s sgular we ca have the fte egevalue. Note that f s o-sgular whch the equvalet prole x x s perfectl well defed ad the fte egevalue correspods to. he geeralzed setrc defte egeprole has ol real egevalues. he geeralzed o-setrc egevalue prole ca have real coplex or fte egevalues. D.R. Sarssa [7] state ad prove a well ow result o the orthogoalt relatos of the egevectors for a atrx. Datta ad et al [] troduced orthogoalt relatos of the egevectors for the setrc defte quadratc pecl. hrough ths paper we cosder the atrx s o-sgular ad postve defte we ca have ol fte egevalues (real or coplex). he followg theore estalshes the orthogoalt relatos of the egevectors for par ( ). heore. et e the egevalues of the lear pecl wth R ad let X ad Y e respectvel the rght ad the left egevector atrces. ssue that { } { } Φ partto ( ) + X X X ad Y ( Y Y ) where X ( x ); X ( ) Y ( ) ( ) Y +. he ad x x + x ad Y X (.5) Y X (.6) If addto ( ) s real setrc the Proof. et Λ ( ) dag sste of the equatos d X X ad X X (.7). We ca rewrte (.) ad (.) the for X XΛ (.8)

5 Drect partal odal approach 3 Y hs ples that ΛY ΛY (.9) X Y he equato (.) ca e wrtte as ΛN NΛ where N XΛ Y X ust e dagoal sce t coutes wth a dagoal Λ. (.) N Y X Y Y Y ( X ) X Y X Y X X Y X he Y X sce Y Y ultplcato X o the rght we ota Λ where Λ dag( ). Fall f ( ) Y X ΛY X s real setrc they X whch proves (.7). he relato (.6) turs out to pla a e role our later developets. Note: the stadard egevalue prole I the aove theore where I dett atrx. x x s the specal of ths theore; put 3. Partal gevalue ssget Prole Suppose R are osetrcal ad s postve defte. et the sste of equatos where X X XΛ (3.) Λ dag C dstct e a C ad ( ) egedecoposto of the pecl P ( ). usg the orthogoalt relato P( ) (3.) Y X (3.3) we ow preset a soluto to the partal egevalue assget prole for the atrx pecl (3.).

6 4.. l-saed ad M. M. M. dou Gve coplex uers { } setrc aout x-axs ad a vector R we are requred to fd f R whch are such that the closed loop pecl. has spectru P c ( ) ( f ) ; (3.4) { } + (3.5) hs s the partal pole assget prole whch we use the vector f R to replace the egevalues { of the pecl ( ) whle leavg the } other egevalues uchaged. et us partto the egevector atrx P { } rght egevector atrx X the left Y ad egevalues atrx Λ as follows: X ( ) X X Y Y Y Λ dag ( ) Λ Λ where X ( x x ); X ( x + x ) Y ( ) ad Y ( + ) wth Λ ( ) ad Λ dag( ). dag heore 3. et he for a choce of we have + f Y (3.6) ( f ) X X Λ (3.7) I words ths theore assures us that a choce of wth f as (3.6) guaratees that the last egepars ( Λ X ) of (3.) are also egepars of the closed loop pecl (3.4). Proof et ( Λ) he X e the egevector-egevalue atrx par of the pecl P( ) X XΛ

7 Drect partal odal approach 5 et X ad Y e respectvel the rght ad the left egevector atrces of the pecl P( ). o prove ths expadg the left had sde of (3.7) susttutg (3.7) we ota f Y ( f ) X X Λ X X Λ Y X ( Y ) X Because X X Λ. Furtherore Y X fro the theore. hus he theore s proved. ( f ) X X Λ Rear. Fro heore 3.we see that there s a paraeters fal of feedac vectors that ca e used to chage soe egevalues the closed loop pecl whle the reag uchaged. 3. Choosg I order to use heore3. to solve the partal pole assget prole we eed to choose whch wll ove { } of the pecl ( ) { } P c ( ) there exst a egevector atrx f that s possle. If there s such a vector Z C ; Z ( z z z ) z ad atrx D dag( ) ( f ) Z ZD. whch are such that Susttutg for f ad rearragg we have P to the (3.8) Z ZD Y Z G Where G Y Z ad c G s a vector that wll deped o the scalg chose for the egevectors Z. o ota Z we ca solve for each of the egevalues z usg the equatos c ( ) z (3.9)

8 6.. l-saed ad M. M. M. dou hs correspods to choosg the vector ( ) egevectors we could solve the c. So havg coputed the square lear sste ( ) G (3.) for ad hece detere the vector f. he aove dscusso leads us to forula the followg algorth for the soluto of the partal egevalue assget prole. lgorth. he sgle put partal pole assget algorth Iputs: R ad a -vector D dag( ) coplex cougato. closed uder ssupto: Nuers ; are all dstct where are the egevalues of P( ) ad s osgular postve defte. Output: the feedac vector P c ( ) ( f ) ; f such that the spectru of the closed-loop pecl s{ ; + } where + are the last egevalues of the pecl P( ). Step. Ota the frst egevalues of the pecl P( ) that eed to e reassged ad the correspodg left egevectors. For Λ dag( ). Y ( ) Step. Solve for Step 3. For z z ; ( ) z G Y Z where Z ( z ) ad Y ( ) z. Step 4. Solve for : G ( ) Step 5. For f Y.

9 Drect partal odal approach 7 3. xplct xpresso For heore 3. Suppose the pecl (3.) has egedecoposto (3.) ad f s chose as (3.6) wth the copoets of chose as. (3.) he the closed loop pecl (3.4) has spectru (3.5) ad ts frst egevectors ca e scaled to satsf (3.9). Proof. I vew of heore 3. we eed ol show that ( ) ( ) [ ]. z f Φ (3.) where ( ) z (3.3) for the choce of f ad dcated. Now ( ) Φ wth f replaced the expressos (3.6) gves ( ) ( ) [ ] z Y Φ he fro (3.3) ( ) [ ] z Y Φ (3.3). Now susttutg for usg (3.) gves ( ) z Φ ( ) ( ) z Φ he

10 8.. l-saed ad M. M. M. dou ( ) ( ) z Φ he -th colu of (3.) ca e wrtte as. x x ece for a choce of ( ) x x + the ( ) ( ) x x (3.4) Susttutg (3.4) to the last expresso for ( ) Φ gves ( ) ( ) z Φ usg (3.3) ( ) Φ ( ) ( ) Φ Cacelg the coo ter we get ( ) Φ ( ) Φ.

11 Drect partal odal approach 9 We ow show that (3.5) for a sets of { } ( ) ad{ } Φ vashes as requred. Defe the oc poloal P whch the are dstct ad thus estalsh that () t ( t ). (3.6) he agrage poloal whch terpolates P at the dstct pots t recovers P tself so we a wrte P ( ) t () t P ( ) ( ) P () t a ( t ) (3.7) where Moreover a P ( ) ( ) a (3.8) ecause P () t s oc. quatg the two fors (3.6) ad (3.7) of P () t at t gves

12 3.. l-saed ad M. M. M. dou a fro whch (3.5) follows (3.8). hs copletes the proof. Fro the expresso (3.) t s clear those suffcet codtos for the exstece of ad cosequetl for a soluto to the partal pole assget prole to exst are that heore et (a) o vashes () the { } are dstct (c) ust e ot orthogoal to. + e the egevalues of the lear pecl wth R. et the egevalues to e chaged to ad the reag egevalues to sta varat. he partal egevalue assget prole s solvale for a artrar set { } f ad ol f for all ad. Proof We frst prove the ecesst. Suppose that. Sce for all ad. hs eas that for a f we have c ( f ) ( f ) whch ples that s a egevalue of par for ever f ad thus caot e reassged. Next we prove the suffcec. We assue that Y. he we eed to prove that there exsts a feedac f whch assgs the egevalues Λ artrarl whle eepg all the other egevalues uchaged. Deote ( ) ad Y ( ) wth ( ) Y + Λ dag

13 Drect partal odal approach 3 Λ dag( ) ad D dag( ). et Y ( ) + egevector atrx of. Sce ( Y ) Y I the the spectru of { } Y Y e left ad Y dag( ) Y Λ Λ or equvaletl the atrx par ( ) +. We assue that there exsts a feedac vector that the closed-loop atrx he dag Multplg ths o the rght dag s Φ such Λ Y Φ has the desred egevalues. ( D Λ ) dag( Λ Λ ) Y ( ) Φ Y gves ( D Λ ) Y dag( Λ Λ ) Y Y ( ) Y Φ Sce Y Y Y the dag Y Y ( D Λ ) Y Y Y ( Φ ) Multplg ths o the left gves ( Y ) Deote f ( Y ) dag( D Λ ) Y ( ΦY ) ( Y ) dag( D Λ ) Y ( ΦY ) ΦY ad c f the the spectru of c { } +. s 4. Real For Of Feedac Vector f. I ths secto we prove that f s real f all the{ setrc aout x-axs. heore 4. et { } ad { } closed uder coplex cougato ad let { } } are coplex uers e two dstct sets of coplex uers e a part of egevalues

14 3.. l-saed ad M. M. M. dou of lear pecl P( ) wth colu vectors { } R. We assue that o zero are the left egevector correspodg to{ }. he ad wheever where s a copoet of as (3.). Proof Frst Sce (4.) We cougate to oth sdes of (4.) (4.) (4.3) Sce the R ad Copare (4.) wth (4.4) we ota (4.4) (4.5) B traspose we ota Secod Fro the relato (3.). (4.6) he Sce ad the. (4.7). (4.8)

15 Drect partal odal approach 33 ad hece.. he theore s proved. Now we descre how to trasfor a coplex cougate set of ad the set of left egevectors Y to the real oes the followg theore. hs wll e requred to ota real feedac vector f fro coplex oes. heore 4. et { } e a set of coplex uers closed uder coplex cougato { } ad let vectors { } e such that ad wheever. he I- here exst a osgular atrx C such that R Y Y Where { } ad Y { } C ad Y R are real atrces. C R (4.9) ad oth R II-here exst real feedac vector f such that f Y (4.) R R Proof I-Defe Where S followg propertes. S M S S ad S M O O O S S M (4.) S the the atrx S has the thus the atrx s osgular ad

16 34.. l-saed ad M. M. M. dou We rewrte { } other for { } where { } a Sce we assue that + ad the { a + a } ad S { a + a } S { a } + + { S 34S + S S } R. We rewrte Y { } loc for Y { 34 + } where { } + +. Sce c + d we assue that + ad where c [ c c c ] ad d [ d d d ] the + { c + d c d }. + S { c + d c d } S { c d } { S 34S + S S } Y R Y. (4.) B usg traspose cougate of (4.) we ota Y Y R II-ow we show that feedac vector f ust e real. Fro the secto 3 we show that spectru of the closed loop pecl ( ) ( f ) ; { } + such that f Y. P c s Sce R Y Y R the f Y Y RY R where oth R ad Y are real atrces the there exst real feedac f Y such R R R that the spectru of the closed loop pecl ( ) ( f ) ; { } P c s +. he theore s proved. Clearl f all the{ } are real the Y s real as well. If addto all the { are real the ad so f s also real. }

17 Drect partal odal approach Nuercal xaple he pecl show ale P( ) has egevalues ordered accordg to ther real parts ale We ow copute the feedac vector gevalues of P( ) f

18 36.. l-saed ad M. M. M. dou [ ] f ale gevalues of P( ) gevalues of ( ) ( f ) ; P c

19 Drect partal odal approach 37 6 Cocluso I ths paper we derved a explct soluto to the partal egevalue prole usg oe of the orthogoalt relatos etwee the egevectors for the lear pecl P( ). We eed ol a partal owledge of the spectru (ad the assocated left egevectors) of the atrx. hese egevalues ad egevectors are requred to e reassged. We proved that the soluto (feedac vector ) for ths prole s the real for. cowledgeets he authors gratefull acowledge Research Cetre Sala B dulazz Uverst Saud raa for supportg ad ecourageet durg ths wor Refereces [] B. N. Datta Recet developets o oodal ad partal odal approaches for cotrol of vrato ppled Nuercal Matheatcs 3 () (999) 4-5. [] B. N. Datta S. lha Y. M. Ra Ortogoalt ad Partal Pole ssget for the Setrc Defte Quadratc Pecl. lg. ppl. 57 (997) [3] B. N. Datta D. R. Sarssa Partal gevalue ssget ear Sstes: xstece Uqueess ad Nuercal Soluto Proc. MNS' Notre Dae ug () [4] M.. Raada ad ha. l-saed Partal egevalue assget prole of lear cotrol sstes usg orthogoalt relatos cta Motastca Slovaca() (6) 6-5

20 38.. l-saed ad M. M. M. dou [5] M.. Raada ad ha. l-saed Proecto lgorth for Partal gevalue ssget Prole Usg Iplctl Restarted rold Method Joural of Vrato ad Cotrol (7) () [6] Y. Saad Proecto ad deflato ethods for partal pole assget lear state Feedac I ras. uto. Cotrol Vol. 33(3) (988) [7] D. R. Sarssa heor ad Coputatos of Partal gevalue ad gestructure ssget Proles Matrx Secod-Order ad Dstruted-Paraeter sstes Ph. D. thess orther llos uverst [8]. Varga Roust pole assget for descrptor sstes : Proceedgs of the MNS Sposu Perpga Frace (). [9]. Varga uercall relale approach to roust pole assget for descrptor sstes Future Geerato Coputer sstes 9 (3). -3. Receved: prl

Some Different Perspectives on Linear Least Squares

Some Different Perspectives on Linear Least Squares Soe Dfferet Perspectves o Lear Least Squares A stadard proble statstcs s to easure a respose or depedet varable, y, at fed values of oe or ore depedet varables. Soetes there ests a deterstc odel y f (,,

More information

A New Method for Solving Fuzzy Linear. Programming by Solving Linear Programming

A New Method for Solving Fuzzy Linear. Programming by Solving Linear Programming ppled Matheatcal Sceces Vol 008 o 50 7-80 New Method for Solvg Fuzzy Lear Prograg by Solvg Lear Prograg S H Nasser a Departet of Matheatcs Faculty of Basc Sceces Mazadara Uversty Babolsar Ira b The Research

More information

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

More information

KURODA S METHOD FOR CONSTRUCTING CONSISTENT INPUT-OUTPUT DATA SETS. Peter J. Wilcoxen. Impact Research Centre, University of Melbourne.

KURODA S METHOD FOR CONSTRUCTING CONSISTENT INPUT-OUTPUT DATA SETS. Peter J. Wilcoxen. Impact Research Centre, University of Melbourne. KURODA S METHOD FOR CONSTRUCTING CONSISTENT INPUT-OUTPUT DATA SETS by Peter J. Wlcoxe Ipact Research Cetre, Uversty of Melboure Aprl 1989 Ths paper descrbes a ethod that ca be used to resolve cossteces

More information

Algorithms behind the Correlation Setting Window

Algorithms behind the Correlation Setting Window Algorths behd the Correlato Settg Wdow Itroducto I ths report detaled forato about the correlato settg pop up wdow s gve. See Fgure. Ths wdow s obtaed b clckg o the rado butto labelled Kow dep the a scree

More information

for each of its columns. A quick calculation will verify that: thus m < dim(v). Then a basis of V with respect to which T has the form: A

for each of its columns. A quick calculation will verify that: thus m < dim(v). Then a basis of V with respect to which T has the form: A Desty of dagoalzable square atrces Studet: Dael Cervoe; Metor: Saravaa Thyagaraa Uversty of Chcago VIGRE REU, Suer 7. For ths etre aer, we wll refer to V as a vector sace over ad L(V) as the set of lear

More information

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions Appled Matheatcs, 1, 4, 8-88 http://d.do.org/1.4/a.1.448 Publshed Ole Aprl 1 (http://www.scrp.org/joural/a) A Covetoal Approach for the Soluto of the Ffth Order Boudary Value Probles Usg Sth Degree Sple

More information

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II CEE49b Chapter - Free Vbrato of Mult-Degree-of-Freedom Systems - II We ca obta a approxmate soluto to the fudametal atural frequecy through a approxmate formula developed usg eergy prcples by Lord Raylegh

More information

7.0 Equality Contraints: Lagrange Multipliers

7.0 Equality Contraints: Lagrange Multipliers Systes Optzato 7.0 Equalty Cotrats: Lagrage Multplers Cosder the zato of a o-lear fucto subject to equalty costrats: g f() R ( ) 0 ( ) (7.) where the g ( ) are possbly also olear fuctos, ad < otherwse

More information

2/20/2013. Topics. Power Flow Part 1 Text: Power Transmission. Power Transmission. Power Transmission. Power Transmission

2/20/2013. Topics. Power Flow Part 1 Text: Power Transmission. Power Transmission. Power Transmission. Power Transmission /0/0 Topcs Power Flow Part Text: 0-0. Power Trassso Revsted Power Flow Equatos Power Flow Proble Stateet ECEGR 45 Power Systes Power Trassso Power Trassso Recall that for a short trassso le, the power

More information

PRACTICAL CONSIDERATIONS IN HUMAN-INDUCED VIBRATION

PRACTICAL CONSIDERATIONS IN HUMAN-INDUCED VIBRATION PRACTICAL CONSIDERATIONS IN HUMAN-INDUCED VIBRATION Bars Erkus, 4 March 007 Itroducto Ths docuet provdes a revew of fudaetal cocepts structural dyacs ad soe applcatos hua-duced vbrato aalyss ad tgato of

More information

Unique Common Fixed Point of Sequences of Mappings in G-Metric Space M. Akram *, Nosheen

Unique Common Fixed Point of Sequences of Mappings in G-Metric Space M. Akram *, Nosheen Vol No : Joural of Facult of Egeerg & echolog JFE Pages 9- Uque Coo Fed Pot of Sequeces of Mags -Metrc Sace M. Ara * Noshee * Deartet of Matheatcs C Uverst Lahore Pasta. Eal: ara7@ahoo.co Deartet of Matheatcs

More information

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming

A Penalty Function Algorithm with Objective Parameters and Constraint Penalty Parameter for Multi-Objective Programming Aerca Joural of Operatos Research, 4, 4, 33-339 Publshed Ole Noveber 4 ScRes http://wwwscrporg/oural/aor http://ddoorg/436/aor4463 A Pealty Fucto Algorth wth Obectve Paraeters ad Costrat Pealty Paraeter

More information

MATH 247/Winter Notes on the adjoint and on normal operators.

MATH 247/Winter Notes on the adjoint and on normal operators. MATH 47/Wter 00 Notes o the adjot ad o ormal operators I these otes, V s a fte dmesoal er product space over, wth gve er * product uv, T, S, T, are lear operators o V U, W are subspaces of V Whe we say

More information

SUBCLASS OF HARMONIC UNIVALENT FUNCTIONS ASSOCIATED WITH SALAGEAN DERIVATIVE. Sayali S. Joshi

SUBCLASS OF HARMONIC UNIVALENT FUNCTIONS ASSOCIATED WITH SALAGEAN DERIVATIVE. Sayali S. Joshi Faculty of Sceces ad Matheatcs, Uversty of Nš, Serba Avalable at: http://wwwpfacyu/float Float 3:3 (009), 303 309 DOI:098/FIL0903303J SUBCLASS OF ARMONIC UNIVALENT FUNCTIONS ASSOCIATED WIT SALAGEAN DERIVATIVE

More information

TESTS BASED ON MAXIMUM LIKELIHOOD

TESTS BASED ON MAXIMUM LIKELIHOOD ESE 5 Toy E. Smth. The Basc Example. TESTS BASED ON MAXIMUM LIKELIHOOD To llustrate the propertes of maxmum lkelhood estmates ad tests, we cosder the smplest possble case of estmatg the mea of the ormal

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

DUALITY FOR MINIMUM MATRIX NORM PROBLEMS

DUALITY FOR MINIMUM MATRIX NORM PROBLEMS HE PUBLISHING HOUSE PROCEEDINGS OF HE ROMNIN CDEMY, Seres, OF HE ROMNIN CDEMY Vole 6, Nber /2005,. 000-000 DULIY FOR MINIMUM MRI NORM PROBLEMS Vasle PRED, Crstca FULG Uverst of Bcharest, Faclt of Matheatcs

More information

A Characterization of Jacobson Radical in Γ-Banach Algebras

A Characterization of Jacobson Radical in Γ-Banach Algebras Advaces Pure Matheatcs 43-48 http://dxdoorg/436/ap66 Publshed Ole Noveber (http://wwwscrporg/joural/ap) A Characterzato of Jacobso Radcal Γ-Baach Algebras Nlash Goswa Departet of Matheatcs Gauhat Uversty

More information

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK Far East Joural of Appled Mathematcs Volume, Number, 2008, Pages Ths paper s avalable ole at http://www.pphm.com 2008 Pushpa Publshg House ANALYSIS ON THE NATURE OF THE ASI EQUATIONS IN SYNERGETI INTER-REPRESENTATION

More information

Parallelized methods for solving polynomial equations

Parallelized methods for solving polynomial equations IOSR Joural of Matheatcs (IOSR-JM) e-issn: 2278-5728, p-issn: 239-765X. Volue 2, Issue 4 Ver. II (Jul. - Aug.206), PP 75-79 www.osrourals.org Paralleled ethods for solvg polyoal equatos Rela Kapçu, Fatr

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

Symmetry of the Solution of Semidefinite Program by Using Primal-Dual Interior-Point Method

Symmetry of the Solution of Semidefinite Program by Using Primal-Dual Interior-Point Method Syetry of the Soluto of Sedefte Progra by Usg Pral-Dual Iteror-Pot Method Yoshhro Kao Makoto Ohsak ad Naok Katoh Departet of Archtecture ad Archtectural Systes Kyoto Uversty Kyoto 66-85 Japa kao@s-jarchkyoto-uacjp

More information

Hájek-Rényi Type Inequalities and Strong Law of Large Numbers for NOD Sequences

Hájek-Rényi Type Inequalities and Strong Law of Large Numbers for NOD Sequences Appl Math If Sc 7, No 6, 59-53 03 59 Appled Matheatcs & Iforato Sceces A Iteratoal Joural http://dxdoorg/0785/as/070647 Háje-Réy Type Iequaltes ad Strog Law of Large Nuers for NOD Sequeces Ma Sogl Departet

More information

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K ROOT-LOCUS ANALYSIS Coder a geeral feedback cotrol yte wth a varable ga. R( Y( G( + H( Root-Locu a plot of the loc of the pole of the cloed-loop trafer fucto whe oe of the yte paraeter ( vared. Root locu

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

On the construction of symmetric nonnegative matrix with prescribed Ritz values

On the construction of symmetric nonnegative matrix with prescribed Ritz values Joural of Lear ad Topologcal Algebra Vol. 3, No., 14, 61-66 O the costructo of symmetrc oegatve matrx wth prescrbed Rtz values A. M. Nazar a, E. Afshar b a Departmet of Mathematcs, Arak Uversty, P.O. Box

More information

1 Lyapunov Stability Theory

1 Lyapunov Stability Theory Lyapuov Stablty heory I ths secto we cosder proofs of stablty of equlbra of autoomous systems. hs s stadard theory for olear systems, ad oe of the most mportat tools the aalyss of olear systems. It may

More information

Assignment 5/MATH 247/Winter Due: Friday, February 19 in class (!) (answers will be posted right after class)

Assignment 5/MATH 247/Winter Due: Friday, February 19 in class (!) (answers will be posted right after class) Assgmet 5/MATH 7/Wter 00 Due: Frday, February 9 class (!) (aswers wll be posted rght after class) As usual, there are peces of text, before the questos [], [], themselves. Recall: For the quadratc form

More information

On Convergence a Variation of the Converse of Fabry Gap Theorem

On Convergence a Variation of the Converse of Fabry Gap Theorem Scece Joural of Appled Matheatcs ad Statstcs 05; 3(): 58-6 Pulshed ole Aprl 05 (http://www.scecepulshggroup.co//sas) do: 0.648/.sas.05030.5 ISSN: 376-949 (Prt); ISSN: 376-953 (Ole) O Covergece a Varato

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

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix.

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix. Revew + v, + y = v, + v, + y, + y, Cato! v, + y, + v, + y geeral Let A be a atr Let f,g : Ω R ( ) ( ) R y R Ω R h( ) f ( ) g ( ) ( ) ( ) ( ( )) ( ) dh = f dg + g df A, y y A Ay = = r= c= =, : Ω R he Proof

More information

Some results and conjectures about recurrence relations for certain sequences of binomial sums.

Some results and conjectures about recurrence relations for certain sequences of binomial sums. Soe results ad coectures about recurrece relatos for certa sequeces of boal sus Joha Cgler Faultät für Matheat Uverstät We A-9 We Nordbergstraße 5 Joha Cgler@uveacat Abstract I a prevous paper [] I have

More information

The Geometric Least Squares Fitting Of Ellipses

The Geometric Least Squares Fitting Of Ellipses IOSR Joural of Matheatcs (IOSR-JM) e-issn: 78-578, p-issn: 39-765X. Volue 4, Issue 3 Ver.I (May - Jue 8), PP -8 www.osrourals.org Abdellatf Bettayeb Departet of Geeral Studes, Jubal Idustral College, Jubal

More information

3D Reconstruction from Image Pairs. Reconstruction from Multiple Views. Computing Scene Point from Two Matching Image Points

3D Reconstruction from Image Pairs. Reconstruction from Multiple Views. Computing Scene Point from Two Matching Image Points D Recostructo fro Iage ars Recostructo fro ultple Ves Dael Deetho Fd terest pots atch terest pots Copute fudaetal atr F Copute caera atrces ad fro F For each atchg age pots ad copute pot scee Coputg Scee

More information

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution: Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler

BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler Mathematcal ad Computatoal Applcatos, Vol. 8, No. 3, pp. 293-300, 203 BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS Aysegul Ayuz Dascoglu ad Nese Isler Departmet of Mathematcs,

More information

Solutions to problem set ); (, ) (

Solutions to problem set ); (, ) ( Solutos to proble set.. L = ( yp p ); L = ( p p ); y y L, L = yp p, p p = yp p, + p [, p ] y y y = yp + p = L y Here we use for eaple that yp, p = yp p p yp = yp, p = yp : factors that coute ca be treated

More information

The Lie Algebra of Smooth Sections of a T-bundle

The Lie Algebra of Smooth Sections of a T-bundle IST Iteratoal Joural of Egeerg Scece, Vol 7, No3-4, 6, Page 8-85 The Le Algera of Smooth Sectos of a T-udle Nadafhah ad H R Salm oghaddam Astract: I ths artcle, we geeralze the cocept of the Le algera

More information

3.1 Introduction to Multinomial Logit and Probit

3.1 Introduction to Multinomial Logit and Probit ES3008 Ecooetrcs Lecture 3 robt ad Logt - Multoal 3. Itroducto to Multoal Logt ad robt 3. Estato of β 3. Itroducto to Multoal Logt ad robt The ultoal Logt odel s used whe there are several optos (ad therefore

More information

Arithmetic Mean and Geometric Mean

Arithmetic Mean and Geometric Mean Acta Mathematca Ntresa Vol, No, p 43 48 ISSN 453-6083 Arthmetc Mea ad Geometrc Mea Mare Varga a * Peter Mchalča b a Departmet of Mathematcs, Faculty of Natural Sceces, Costate the Phlosopher Uversty Ntra,

More information

Estimation of R= P [Y < X] for Two-parameter Burr Type XII Distribution

Estimation of R= P [Y < X] for Two-parameter Burr Type XII Distribution World Acade of Scece, Egeerg ad Techolog Iteratoal Joural of Matheatcal ad Coputatoal Sceces Vol:4, No:, Estato of R P [Y < X] for Two-paraeter Burr Tpe XII Dstruto H.Paah, S.Asad Iteratoal Scece Ide,

More information

Application of Legendre Bernstein basis transformations to degree elevation and degree reduction

Application of Legendre Bernstein basis transformations to degree elevation and degree reduction Computer Aded Geometrc Desg 9 79 78 www.elsever.com/locate/cagd Applcato of Legedre Berste bass trasformatos to degree elevato ad degree reducto Byug-Gook Lee a Yubeom Park b Jaechl Yoo c a Dvso of Iteret

More information

CS 2750 Machine Learning. Lecture 7. Linear regression. CS 2750 Machine Learning. Linear regression. is a linear combination of input components x

CS 2750 Machine Learning. Lecture 7. Linear regression. CS 2750 Machine Learning. Linear regression. is a linear combination of input components x CS 75 Mache Learg Lecture 7 Lear regresso Mlos Hauskrecht los@cs.ptt.edu 59 Seott Square CS 75 Mache Learg Lear regresso Fucto f : X Y s a lear cobato of put copoets f + + + K d d K k - paraeters eghts

More information

Johns Hopkins University Department of Biostatistics Math Review for Introductory Courses

Johns Hopkins University Department of Biostatistics Math Review for Introductory Courses Johs Hopks Uverst Departmet of Bostatstcs Math Revew for Itroductor Courses Ratoale Bostatstcs courses wll rel o some fudametal mathematcal relatoshps, fuctos ad otato. The purpose of ths Math Revew s

More information

Singular Value Decomposition. Linear Algebra (3) Singular Value Decomposition. SVD and Eigenvectors. Solving LEs with SVD

Singular Value Decomposition. Linear Algebra (3) Singular Value Decomposition. SVD and Eigenvectors. Solving LEs with SVD Sgular Value Decomosto Lear Algera (3) m Cootes Ay m x matrx wth m ca e decomosed as follows Dagoal matrx A UWV m x x Orthogoal colums U U I w1 0 0 w W M M 0 0 x Orthoormal (Pure rotato) VV V V L 0 L 0

More information

Order Nonlinear Vector Differential Equations

Order Nonlinear Vector Differential Equations It. Joural of Math. Aalyss Vol. 3 9 o. 3 39-56 Coverget Power Seres Solutos of Hgher Order Nolear Vector Dfferetal Equatos I. E. Kougas Departet of Telecoucato Systes ad Networs Techologcal Educatoal Isttute

More information

Solving the fuzzy shortest path problem on networks by a new algorithm

Solving the fuzzy shortest path problem on networks by a new algorithm Proceedgs of the 0th WSEAS Iteratoal Coferece o FUZZY SYSTEMS Solvg the fuzzy shortest path proble o etworks by a ew algorth SADOAH EBRAHIMNEJAD a, ad REZA TAVAKOI-MOGHADDAM b a Departet of Idustral Egeerg,

More information

Johns Hopkins University Department of Biostatistics Math Review for Introductory Courses

Johns Hopkins University Department of Biostatistics Math Review for Introductory Courses Johs Hopks Uverst Departmet of Bostatstcs Math Revew for Itroductor Courses Ratoale Bostatstcs courses wll rel o some fudametal mathematcal relatoshps, fuctos ad otato. The purpose of ths Math Revew s

More information

A Variable Structure Model Reference Adaptive Control For MIMO Systems

A Variable Structure Model Reference Adaptive Control For MIMO Systems Proceedgs of the Iteratoal ultcoferece of Egeers ad Coputer Scetsts 8 Vol II IECS 8 9- arch 8 Hog Kog A Varale Structure odel Referece Adaptve Cotrol For IO Systes Ardeshr Kara ohaad Astract A Varale Structure

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

A Family of Non-Self Maps Satisfying i -Contractive Condition and Having Unique Common Fixed Point in Metrically Convex Spaces *

A Family of Non-Self Maps Satisfying i -Contractive Condition and Having Unique Common Fixed Point in Metrically Convex Spaces * Advaces Pure Matheatcs 0 80-84 htt://dxdoorg/0436/a04036 Publshed Ole July 0 (htt://wwwscrporg/oural/a) A Faly of No-Self Mas Satsfyg -Cotractve Codto ad Havg Uque Coo Fxed Pot Metrcally Covex Saces *

More information

Non-degenerate Perturbation Theory

Non-degenerate Perturbation Theory No-degeerate Perturbato Theory Proble : H E ca't solve exactly. But wth H H H' H" L H E Uperturbed egevalue proble. Ca solve exactly. E Therefore, kow ad. H ' H" called perturbatos Copyrght Mchael D. Fayer,

More information

9.1 Introduction to the probit and logit models

9.1 Introduction to the probit and logit models EC3000 Ecoometrcs Lecture 9 Probt & Logt Aalss 9. Itroducto to the probt ad logt models 9. The logt model 9.3 The probt model Appedx 9. Itroducto to the probt ad logt models These models are used regressos

More information

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat

More information

18.413: Error Correcting Codes Lab March 2, Lecture 8

18.413: Error Correcting Codes Lab March 2, Lecture 8 18.413: Error Correctg Codes Lab March 2, 2004 Lecturer: Dael A. Spelma Lecture 8 8.1 Vector Spaces A set C {0, 1} s a vector space f for x all C ad y C, x + y C, where we take addto to be compoet wse

More information

Stationary states of atoms and molecules

Stationary states of atoms and molecules Statoary states of atos ad olecules I followg wees the geeral aspects of the eergy level structure of atos ad olecules that are essetal for the terpretato ad the aalyss of spectral postos the rotatoal

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

Analysis of Lagrange Interpolation Formula

Analysis of Lagrange Interpolation Formula P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal

More information

Global Optimization for Solving Linear Non-Quadratic Optimal Control Problems

Global Optimization for Solving Linear Non-Quadratic Optimal Control Problems Joural of Appled Matheatcs ad Physcs 06 4 859-869 http://wwwscrporg/joural/jap ISSN Ole: 37-4379 ISSN Prt: 37-435 Global Optzato for Solvg Lear No-Quadratc Optal Cotrol Probles Jghao Zhu Departet of Appled

More information

4 Inner Product Spaces

4 Inner Product Spaces 11.MH1 LINEAR ALGEBRA Summary Notes 4 Ier Product Spaces Ier product s the abstracto to geeral vector spaces of the famlar dea of the scalar product of two vectors or 3. I what follows, keep these key

More information

Order statistics from non-identical Standard type II Generalized logistic variables and applications at moments

Order statistics from non-identical Standard type II Generalized logistic variables and applications at moments Amerca Joural of Theoretcal ad Appled Statstcs 05; 4(: -5 Pulshed ole Jauar 3, 05 (http://www.scecepulshggroup.com//atas do: 0.648/.atas.05040. ISSN: 36-8999 (Prt; ISSN: 36-9006 (Ole Order statstcs from

More information

Interval extension of Bézier curve

Interval extension of Bézier curve WSEAS TRANSACTIONS o SIGNAL ROCESSING Jucheg L Iterval exteso of Bézer curve JUNCHENG LI Departet of Matheatcs Hua Uversty of Huates Scece ad Techology Dxg Road Loud cty Hua rovce 47 R CHINA E-al: ljucheg8@6co

More information

h-analogue of Fibonacci Numbers

h-analogue of Fibonacci Numbers h-aalogue of Fboacc Numbers arxv:090.0038v [math-ph 30 Sep 009 H.B. Beaoum Prce Mohammad Uversty, Al-Khobar 395, Saud Araba Abstract I ths paper, we troduce the h-aalogue of Fboacc umbers for o-commutatve

More information

The Primitive Idempotents in

The Primitive Idempotents in Iteratoal Joural of Algebra, Vol, 00, o 5, 3 - The Prmtve Idempotets FC - I Kulvr gh Departmet of Mathematcs, H College r Jwa Nagar (rsa)-5075, Ida kulvrsheora@yahoocom K Arora Departmet of Mathematcs,

More information

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION Malasa Joural of Mathematcal Sceces (): 95-05 (00) Fourth Order Four-Stage Dagoall Implct Ruge-Kutta Method for Lear Ordar Dfferetal Equatos Nur Izzat Che Jawas, Fudzah Ismal, Mohamed Sulema, 3 Azm Jaafar

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

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

CHAPTER 4 RADICAL EXPRESSIONS

CHAPTER 4 RADICAL EXPRESSIONS 6 CHAPTER RADICAL EXPRESSIONS. The th Root of a Real Number A real umber a s called the th root of a real umber b f Thus, for example: s a square root of sce. s also a square root of sce ( ). s a cube

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

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

Relations to Other Statistical Methods Statistical Data Analysis with Positive Definite Kernels

Relations to Other Statistical Methods Statistical Data Analysis with Positive Definite Kernels Relatos to Other Statstcal Methods Statstcal Data Aalyss wth Postve Defte Kerels Kej Fukuzu Isttute of Statstcal Matheatcs, ROIS Departet of Statstcal Scece, Graduate Uversty for Advaced Studes October

More information

Can we take the Mysticism Out of the Pearson Coefficient of Linear Correlation?

Can we take the Mysticism Out of the Pearson Coefficient of Linear Correlation? Ca we tae the Mstcsm Out of the Pearso Coeffcet of Lear Correlato? Itroducto As the ttle of ths tutoral dcates, our purpose s to egeder a clear uderstadg of the Pearso coeffcet of lear correlato studets

More information

Entropy ISSN by MDPI

Entropy ISSN by MDPI Etropy 2003, 5, 233-238 Etropy ISSN 1099-4300 2003 by MDPI www.mdp.org/etropy O the Measure Etropy of Addtve Cellular Automata Hasa Aı Arts ad Sceces Faculty, Departmet of Mathematcs, Harra Uversty; 63100,

More information

A Study on Generalized Generalized Quasi hyperbolic Kac Moody algebra QHGGH of rank 10

A Study on Generalized Generalized Quasi hyperbolic Kac Moody algebra QHGGH of rank 10 Global Joural of Mathematcal Sceces: Theory ad Practcal. ISSN 974-3 Volume 9, Number 3 (7), pp. 43-4 Iteratoal Research Publcato House http://www.rphouse.com A Study o Geeralzed Geeralzed Quas (9) hyperbolc

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

A Remark on the Uniform Convergence of Some Sequences of Functions

A Remark on the Uniform Convergence of Some Sequences of Functions Advaces Pure Mathematcs 05 5 57-533 Publshed Ole July 05 ScRes. http://www.scrp.org/joural/apm http://dx.do.org/0.436/apm.05.59048 A Remark o the Uform Covergece of Some Sequeces of Fuctos Guy Degla Isttut

More information

Investigation of Partially Conditional RP Model with Response Error. Ed Stanek

Investigation of Partially Conditional RP Model with Response Error. Ed Stanek Partally Codtoal Radom Permutato Model 7- vestgato of Partally Codtoal RP Model wth Respose Error TRODUCTO Ed Staek We explore the predctor that wll result a smple radom sample wth respose error whe a

More information

Class 13,14 June 17, 19, 2015

Class 13,14 June 17, 19, 2015 Class 3,4 Jue 7, 9, 05 Pla for Class3,4:. Samplg dstrbuto of sample mea. The Cetral Lmt Theorem (CLT). Cofdece terval for ukow mea.. Samplg Dstrbuto for Sample mea. Methods used are based o CLT ( Cetral

More information

An Innovative Algorithmic Approach for Solving Profit Maximization Problems

An Innovative Algorithmic Approach for Solving Profit Maximization Problems Matheatcs Letters 208; 4(: -5 http://www.scecepublshggroup.co/j/l do: 0.648/j.l.208040. ISSN: 2575-503X (Prt; ISSN: 2575-5056 (Ole A Iovatve Algorthc Approach for Solvg Proft Maxzato Probles Abul Kala

More information

Introducing Sieve of Eratosthenes as a Theorem

Introducing Sieve of Eratosthenes as a Theorem ISSN(Ole 9-8 ISSN (Prt - Iteratoal Joural of Iovatve Research Scece Egeerg ad echolog (A Hgh Imact Factor & UGC Aroved Joural Webste wwwrsetcom Vol Issue 9 Setember Itroducg Seve of Eratosthees as a heorem

More information

STK4011 and STK9011 Autumn 2016

STK4011 and STK9011 Autumn 2016 STK4 ad STK9 Autum 6 Pot estmato Covers (most of the followg materal from chapter 7: Secto 7.: pages 3-3 Secto 7..: pages 3-33 Secto 7..: pages 35-3 Secto 7..3: pages 34-35 Secto 7.3.: pages 33-33 Secto

More information

Numerical Analysis Formulae Booklet

Numerical Analysis Formulae Booklet Numercal Aalyss Formulae Booklet. Iteratve Scemes for Systems of Lear Algebrac Equatos:.... Taylor Seres... 3. Fte Dfferece Approxmatos... 3 4. Egevalues ad Egevectors of Matrces.... 3 5. Vector ad Matrx

More information

On Submanifolds of an Almost r-paracontact Riemannian Manifold Endowed with a Quarter Symmetric Metric Connection

On Submanifolds of an Almost r-paracontact Riemannian Manifold Endowed with a Quarter Symmetric Metric Connection Theoretcal Mathematcs & Applcatos vol. 4 o. 4 04-7 ISS: 79-9687 prt 79-9709 ole Scepress Ltd 04 O Submafolds of a Almost r-paracotact emaa Mafold Edowed wth a Quarter Symmetrc Metrc Coecto Mob Ahmad Abdullah.

More information

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm Appled Mathematcal Sceces, Vol 6, 0, o 4, 63-7 Soluto of Geeral Dual Fuzzy Lear Systems Usg ABS Algorthm M A Farborz Aragh * ad M M ossezadeh Departmet of Mathematcs, Islamc Azad Uversty Cetral ehra Brach,

More information

L5 Polynomial / Spline Curves

L5 Polynomial / Spline Curves L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a

More information

Ideal multigrades with trigonometric coefficients

Ideal multigrades with trigonometric coefficients Ideal multgrades wth trgoometrc coeffcets Zarathustra Brady December 13, 010 1 The problem A (, k) multgrade s defed as a par of dstct sets of tegers such that (a 1,..., a ; b 1,..., b ) a j = =1 for all

More information

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America SOLUTION OF SYSTEMS OF SIMULTANEOUS LINEAR EQUATIONS Gauss-Sedel Method 006 Jame Traha, Autar Kaw, Kev Mart Uversty of South Florda Uted States of Amerca kaw@eg.usf.edu Itroducto Ths worksheet demostrates

More information

Non-uniform Turán-type problems

Non-uniform Turán-type problems Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at

More information

ASYMPTOTIC STABILITY OF TIME VARYING DELAY-DIFFERENCE SYSTEM VIA MATRIX INEQUALITIES AND APPLICATION

ASYMPTOTIC STABILITY OF TIME VARYING DELAY-DIFFERENCE SYSTEM VIA MATRIX INEQUALITIES AND APPLICATION Joural of the Appled Matheatcs Statstcs ad Iforatcs (JAMSI) 6 (00) No. ASYMPOIC SABILIY OF IME VARYING DELAY-DIFFERENCE SYSEM VIA MARIX INEQUALIIES AND APPLICAION KREANGKRI RACHAGI Abstract I ths paper

More information

International Journal of Mathematical Archive-3(5), 2012, Available online through ISSN

International Journal of Mathematical Archive-3(5), 2012, Available online through   ISSN Iteratoal Joural of Matheatcal Archve-(5,, 88-845 Avalable ole through www.a.fo ISSN 9 546 FULLY FUZZY LINEAR PROGRAMS WITH TRIANGULAR FUZZY NUMERS S. Mohaaselv Departet of Matheatcs, SRM Uversty, Kattaulathur,

More information

Abstract. 1. Introduction

Abstract. 1. Introduction Joura of Mathematca Sceces: Advaces ad Appcatos Voume 4 umber 2 2 Pages 33-34 COVERGECE OF HE PROJECO YPE SHKAWA ERAO PROCESS WH ERRORS FOR A FE FAMY OF OSEF -ASYMPOCAY QUAS-OEXPASVE MAPPGS HUA QU ad S-SHEG

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

Coherent Potential Approximation

Coherent Potential Approximation Coheret Potetal Approxato Noveber 29, 2009 Gree-fucto atrces the TB forals I the tght bdg TB pcture the atrx of a Haltoa H s the for H = { H j}, where H j = δ j ε + γ j. 2 Sgle ad double uderles deote

More information

arxiv: v4 [math.nt] 14 Aug 2015

arxiv: v4 [math.nt] 14 Aug 2015 arxv:52.799v4 [math.nt] 4 Aug 25 O the propertes of terated bomal trasforms for the Padova ad Perr matrx sequeces Nazmye Ylmaz ad Necat Tasara Departmet of Mathematcs, Faculty of Scece, Selcu Uversty,

More information

PROJECTION PROBLEM FOR REGULAR POLYGONS

PROJECTION PROBLEM FOR REGULAR POLYGONS Joural of Mathematcal Sceces: Advaces ad Applcatos Volume, Number, 008, Pages 95-50 PROJECTION PROBLEM FOR REGULAR POLYGONS College of Scece Bejg Forestry Uversty Bejg 0008 P. R. Cha e-mal: sl@bjfu.edu.c

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 17

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 17 CS434a/54a: Patter Recogto Prof. Olga Vesler Lecture 7 Today Paraetrc Usupervsed Learg Expectato Maxato (EM) oe of the ost useful statstcal ethods oldest verso 958 (Hartley) seal paper 977 (Depster et

More information

Construction of Composite Indices in Presence of Outliers

Construction of Composite Indices in Presence of Outliers Costructo of Coposte dces Presece of Outlers SK Mshra Dept. of Ecoocs North-Easter Hll Uversty Shllog (da). troducto: Oftetes we requre costructg coposte dces by a lear cobato of a uber of dcator varables.

More information