The solution of Euler-Bernoulli beams using variational derivative method

Size: px
Start display at page:

Download "The solution of Euler-Bernoulli beams using variational derivative method"

Transcription

1 Scetfc Research ad Essays Vol. 5(9), pp. 9-4, 4 May Avalable ole at ISSN Academc Jourals Full egth Research Paper The soluto of Euler-Beroull beams usg varatoal dervatve method Atlla Özütok * ad Arfe Ak Selcuk Uversty, Egeerg Archtectural Faculty, 43, Koya, Turkey. Accepted 7 Aprl, Fte dfferece methods are ofte used for aalyzg structures govered by complex dfferetal equatos. The fte dfferece method, well kow as a effcet umercal method, was formerly appled to the case of beam ad plate problems. The basc dsadvatages of ths method are the requremet of out-of-rego pots durg the soluto process ad the dffculty of mplemetg the boudary codtos alog rregular boudares. I ths study, the varatoal dervatve method was proposed to solve the fuctoal of the Euler Beroull beam obtaed by Gâteaux dfferetal method. The ma reaso for the preferece of ths method over the fte dfferece method was the elmato of the eed for the out-of-rego doma pots that complcate the applcato of the fte dfferece method. The momets ad deflectos of beams wth costat ad varyg cross-sectos ad varous support types were calculated order to demostrate the applcablty of the method. The performace of ths formulato s verfed by comparg the obtaed results wth the results of the umercal examples the lterature. Key words: Fte dfferece, varatoal dervatve, beams. INTRODUCTION We should bear md that all methods of structural aalyss are essetally cocered wth solvg the basc dfferetal equatos of equlbrum ad compatblty, although, some of the methods ths fact may be obscured. Aalytcal solutos are lmted to the cases where the load dstrbuto, secto propertes ad boudary codtos ca be descrbed by mathematcal expressos. However, the umercal aalyss methods are geerally more practcal for complex structures. Moreover, varous methods for fdg sutable approxmate solutos have bee uder cotuous developmet for decades. Amog these methods, Fte Dfferece Method (FDM), Raylegh- Rtz Method, Galerk Method, east-squares Method, Fte Elemet Methods (FEM) have domated the applcatos to problems egeerg. I FDM, a umercal soluto of the dfferetal equato for dsplacemet or stress resultat s obtaed for chose pots o the structure, referred to *Correspodg author: E-mal: aozutok@selcuk.edu.tr. Tel: Fax: as odes or smply as pot of dvso. Durg the study performed o the fte dfferece aalyss of the systems ad the comparso of the methods used wth fte elemet techques, we readly recogzed a very close relatoshp betwee fte dfferece ad fte elemet procedures. However, the FEM may appear to be a better choce tha FDM owg the easer defto of the boudary codtos. The FDM has bee comprehedsvely formulated may studes. We ca classfy the FDM to two groups accordg to the lterature amely, Covetoal Fte Dfferece Method (CFDM) ad Fte Dfferece Eergy Method (FDEM). The soluto by the CFDM s obtaed by applyg the fte dfferece expressos o the area equatos drectly. The dsadvatages of the method clude the dffcultes of mplemetg the boudary codtos o rregular boudares ad accurately represetg the rregular domas. The varatoal method s a powerful method that ca be used for both approxmate solutos ad formulato of problems (Reddy, 986). May researchers have developed the FDEM based o varato order to overcome the dffculty stated prevously. Houbolt used ths method 958 to perform

2 Sc. Res. Essays the statc aalyss of the beams ad plates. I 983, Barve ad Dey ad 99 Sgh ad Dey appled the FDEM to the statc, vbrato ad stablty tests of the plates. Arsla (4) studed o the fuctoal of the Euler-Beroull beam obtaed by usg the Gâteaux dfferetal approach to solve the fuctoal by the ad of the varatoal dervatve method based o FDM, ad cosequetly, the momets ad deflectos of the beams wth costat ad varyg cross-sectos ad varous support types were determed by cosderg the out-ofrego pots. Gelfad ad Fom (963) carred out the bucklg aalyss of the elastc bars usg the varatoal dervatve method. Gürsoy (4); Eratl ad Gürsoy (5) solved all the bucklg problems of elastc bars usg the methods of varatoal dervatve ad fte dfferece ad to determed the elemet matrx of the bar elemet usg varatoal dervatve method. As a result of ths study, the varatoal dervatve method was foud to be extremely smlar but more advatageous whe compared to FDM; due to ot beg eed of outof-rego pots that complcate the applcato of FDM. I ths work, we cosder the soluto for the Euler- Beroull beam s fuctoal obtaed by usg the Gâteaux dfferetal approach. The purpose of ths study s to solve the fuctoal by the ad of the varatoal dervatve method based o FDM. The momet ad deflecto values were selected as the ukows of the fuctoal, modfed by Aköz (985). Some sgfcat advatages of the Gâteaux dfferetal approach were explaed by Özütok (). The elemet matrx for Euler-Beroull beam s derved based o the varatoal dervatve. The performace of the matrx for bedg aalyss s verfed wth a good accuracy by comparg wth the umercal examples ad aalytcal solutos preseted the lterature. The fuctoal for Euler-Beroullı beam The equatos volvg the boudary codtos for Euler-Beroull beam whch ca be wrtte the operator form as: Q y f () Havg obtaed the feld equatos, oe eeds a method to obta the fuctoal. We beleve that the Gâteaux dfferetal method s sutable for ths am. Sce ths method was extesvely used ad explaed other studes (Aköz et al., 99), for the sake of smplcty, the basc steps ad deftos wll be summarzed brefly. The Gâteaux dervatve of a operator s defed as Q ( y + τ y ) d Q ( y ; y ) τ () τ Where, s a scalar. A ecessary ad suffcet codto for Q to be a potetal s (Ode ad Reddy, 976) dq( y; y), y * dq( y; y * ), y (3) Where, paretheses dcate the er products. If the operator Q s a potetal, the the fuctoal whch correspods to the feld equatos s gve by l I ( y) Q( sy), y ds (4) Where, s s a scalar quatty. The clear form of the fuctoal correspodg to the feld equatos are obtaed as the followg (Arsla, 4), M I ( y ) [ M, v ] [ q, v ], [ ˆ, ] M v M E I ε v, Tˆ ( M Mˆ ), v ( vˆ + v ), T σ σ (5) Where, the subscrpts ε ad σ dcate the geometrc ad dyamc boudary codtos, respectvely. As see Equato (5), the momet ad deflecto values selected as ukows of the fuctoal are tegrated smultaeously to the fuctoal ad are obtaed easly wthout eedg the boudary codtos to be kow. Varatoal dervatve f ( x, x,... x ), f For a fucto wth multple argumets, the dfferetal df ca be wrtte as df g( x, x,.. x) dx, the g ( x, x,.. x) dx s called the dervatve of f wth respect to,..., ad s gve by f x g ( x, x,.. x ) Notce that the dervatve of fucto ε x, for (6) f ( x,,.. x ) wth respect to x wll be aother fucto amed g ( x,,.. x ). Smlarly, f the frst varatoal dervatve as of a fuctoal [ ] b (7) I y ( x ) F ( x, y, ) dx a

3 Ozutok ad Ak M - M v v - M + Fgure. Nodal pots ad the elemets. s wrtte as b δ I y( x) g( x) δ y( x) dx [ ] a v + (8) The, the fuctoal dervatve of I wll be δ I g( x) (9) δ y( x) The fuctoal dervatve of a fuctoal I [ y( x )] s aother fucto g( x ). Image that we approxmate the fucto y( x) by a pece-wse lear curve that passes through a set of pots ( x, y ),,..., +, where x x, y y( x ), x a ad +. et y( x ) be subjected to essetal boudary codtos, so that are fxed. The, the y y( a) ad y y( b) + fuctoal I [ y( x )] ca be approxmated by a sum. y + y I ( y, y,... y ) F( x, y, ) The partal dervatve of argumets s, x () b I wth respect to oe of ts I F y + F y y F y k yk yk yk yk k y x + () Comparg ths wth the defto of the fuctoal dervatve, the followg equato s wrtte δi d I F ( x, y, ) ( F ( x, y, ) lm δ y y dx yk () The, the above expresso s called varatoal dervatve (Kag et al., 6), ad the frst codto for y(x) to make I [y(x)] fuctoal maxmum s I. Usg ths codto, the δ I δ y expresso wll be equal to zero at every pot. Varatoal dervatve method dffers from FDM by ot eedg to use the out-of-rego pots (Eratlı ad Gürsoy, 5). A formulato based o varatoal dervatve method that does ot requre ay out-of-rego pots s developed to calculate the bedg momets ad deflectos of the bars makg use of the fuctoal obtaed here. The, the elemet matrx ca be wrtte as M e I M e v e q v e EI (3) by usg ths equato [ ( )] I y x. Here, x + x ad e s elemet umber. If the followg relatoshps are replaced wth the dervatve expressos the fuctoal v v M M v, M + + (4) ad the dervatves are take wth respect to the momets ad deflectos defed as the ukows at each odal pot of th elemet of the bar system show Fgure ad are equalzed to zero, as follows δ I d I F ( x, y, ) ( F ( x, y, ) lm δ y y dx yk the, the elemet matrx s obtaed as λ M M + v q v + Where, λ EI. Numercal examples (5) (6) Several problems of beams wth varous boudary codtos have bee studed the past. I order to check the performace of varatoal dervatve method, varous problems are solved ad the results are compared wth those of smlar examples the lterature.

4 Sc. Res. Essays q Fgure. The smply supported beam to be aalyzed uder uformly dstrbuted trasverse loadg. Table. Comparso of the VD ad exact solutos. Values ( v exact 4 5 q α ) 384 EI Number of members CFD FDEM VD of (Arsla, 4) VD of ths study Exact Mx 3, v Fgure 3. The dstrbuto of momet ad deflecto alog the beam obtaed wth VD ad MFEM. Smply-supported beam wth uform loadg Frst of all, we decded to cosder the accuracy ad covergece of the varatoal dervatve elemet matrx o a smply supported beam subjected to a uform vertcal loadg of q kn/m as show Fgure. The materal propertes ad dmesos are E x 7 kn/m, m, h.5 m ad b. m. The maxmum deflectos obtaed from varous types of aalyses cludg CFD, FDEM ad VD of Arsla (4) gve the lterature ad the curret study are preseted Table to allow comparso wth the exact soluto. As t s see, the deflectos foud from the curret study coverge to the exact results. CFD: covetoal fte dfferece method; FDEM: fte dfferece eergy method, VD: Varatoal dervatve. I addto to the maxmum deflecto values, the dstrbuto of momet ad deflecto alog the beam axs from VD of ths study ad MFEM s plotted ad show Fgure 3. The effect of the umber of elemets

5 Ozutok ad Ak 3.4. M (KNm), v (m) Fgure 4. Deflecto ad momet covergece vs. umber of elemets. Fgure 5. A catlever beam wth uform dstrbuted loadg. q Table. Comparso of VD results wth the lterature ad exact results. m h b/h s Gul, 3 MFEM (v x ) Deflecto VD of ths study Exact used beam dscretzato o the deflecto ad momet are show Fgure 4, where the odmesoalzed maxmum deflecto v v EI q 4 ad momet M M q of a smply supported beam subjected to a uformly dstrbtued load s plotted. Catlever beam wth uform dstrbuted loadg: Costat cross-secto case Cosderg the problem of fdg the trasverse deflecto of a catlever beam uder a uform dstrbuted loadg by usg varatoal dervatve method Fgure 5; the deflecto ad momet of the free tp versus the umber of elemets are plotted as show Fgure 6. I the fgure, the deflecto ad momet coverge to the exact soluto results wth a error proportoal to the umber of elemets used. Catlever beam wth uform dstrbuted loadg: Varable cross-secto case I order to test the effect of heght varato o the deflecto ad momet, a catlever beam subjected to a uform dstrbuted loadg as show Fgure 7 was aalyzed for dfferet heghts. I Fgure 7, h b ad h s are the heght of beam cross-secto at the left ad rght had sdes of the beam, respectvely. The varato of the momet of erta alog the beam ca be defed for elemet by I 3 bh + 3 z (7) Where, m-, m h b /h s ad z s the legth of elemet. The maxmum deflectos for four cases wth dfferet heght ratos are show Table. I the table, results of the study by (Gul, 3) ad exact results are gve for comparso. DISCUSSION AND CONCUSION I ths study, the solutos of Euler Beroull beams of costat ad varyg cross-sectos uder uformly dstrbuted loadg are carred out usg varatoal dervatve method wthout the eed of out-of-rego pots

6 4 Sc. Res. Essays.3.5 V3 Mm Fgure 6. Deflecto ad momet covergeces wth respect to umber of elemets. q h b h s Fgure 7. A catlever beam wth varable cross-secto uder uformly dstrbuted loadg. of FDM. The elemet matrx of the beam s obtaed by applyg the fuctoal (Arsla, 4) to the varatoal dervatve method whch was derved for straght-axs bars usg Gâteaux dfferetal method. Besdes, observg the smlarty of the proposed elemet matrx to that of FDM, the obtaed matrx s superor beam problems sce t does ot requre ay out-of-rego pots. A computer code s developed Fortra to compute the proposed elemet matrx by cosderg the boudary codtos. Usg ths computer code, the ukow momets ad the dsplacemets at the odal pots are calculated ad foud to be agreemet wth the results of the prevous studes the lterature ad the exact results. I the etre example problems cosdered, the proposed approach coverges to the exact soluto as log as the umber of members s creased. Therefore, t s expected that the method wll provde a better approach to the case of hgher degree beam problems. REFERENCES Aköz AY (985). A ew fuctoal for bars ad ts applcatos, ( Turksh), IV. Natoal Mechacs Meetg, Turkey pp. -. Aköz AY, Omurtag MH, Doruolu AN (99). The mxed fte elemet formulato for three dmesoal bars. It. J. Solds Struct. Ege 8: Aköz AY, Özutok A (). A fuctoal for shells of arbtrary geometry ad a mxed fte elemet method for parabolc ad crcular cyldrcal shells, It. J. Numer. Meth. Ege 47: Arsla A (4). The soluto of Euler-Beroull beams by varatoal dervatve method, ( Turksh), M.Sc. Dssertato, Selcuk Uversty, Koya. Barve VD, Dey SS (983). Isoparametrc fte dfferece eergy method for plate bedg problems, Computer Struct. 7: Eratl N, Gürsoy A (5). Varatoal dervatve for bucklg loads of beams ad frames, It. Appl. Mech. 4(7): Gelfad IM, Fom SV (963). Calculus of varatos, Pretce-Hall, New Jersey. Gul M (3). Dyamcs aalyss of stffeed plate, ( Turksh), M.Sc. Dssertato,.T.Ü., stabul. Gürsoy A (4). The aalyss of the bucklg loads for beams ad frames wth varatoal dervatve ( Turksh), M.Sc. Dssertato,.T.Ü., stabul. Houbolt JC (958). A study of several aerothermoelastc problems of arcraft structures Hgh-Speed Flght, eema, Zurch Kag K, Weberger C, Ca W (6). A short essay o varatoal calculus, Staford Uversty. Ode JT, Reddy JN (976). Varatoal Method Theortcal Mechacs. Sprger, Berl. Reddy JN (986). A Itroducto to the Fte Elemet Method, McGraw-Hll, New York. Sgh JP, Dey SS (99). Varatoal fte dfferece method for free vbrato of sector plates, J. Soud Vb. 36: 9-4.

Beam Warming Second-Order Upwind Method

Beam Warming Second-Order Upwind Method Beam Warmg Secod-Order Upwd Method Petr Valeta Jauary 6, 015 Ths documet s a part of the assessmet work for the subject 1DRP Dfferetal Equatos o Computer lectured o FNSPE CTU Prague. Abstract Ths documet

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load Dyamc Aalyss of Axally Beam o Vsco - Elastc Foudato wth Elastc Supports uder Movg oad Saeed Mohammadzadeh, Seyed Al Mosayeb * Abstract: For dyamc aalyses of ralway track structures, the algorthm of soluto

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

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

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

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

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

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

12.2 Estimating Model parameters Assumptions: ox and y are related according to the simple linear regression model

12.2 Estimating Model parameters Assumptions: ox and y are related according to the simple linear regression model 1. Estmatg Model parameters Assumptos: ox ad y are related accordg to the smple lear regresso model (The lear regresso model s the model that says that x ad y are related a lear fasho, but the observed

More information

Mu Sequences/Series Solutions National Convention 2014

Mu Sequences/Series Solutions National Convention 2014 Mu Sequeces/Seres Solutos Natoal Coveto 04 C 6 E A 6C A 6 B B 7 A D 7 D C 7 A B 8 A B 8 A C 8 E 4 B 9 B 4 E 9 B 4 C 9 E C 0 A A 0 D B 0 C C Usg basc propertes of arthmetc sequeces, we fd a ad bm m We eed

More information

A New Family of Transformations for Lifetime Data

A New Family of Transformations for Lifetime Data Proceedgs of the World Cogress o Egeerg 4 Vol I, WCE 4, July - 4, 4, Lodo, U.K. A New Famly of Trasformatos for Lfetme Data Lakhaa Watthaacheewakul Abstract A famly of trasformatos s the oe of several

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

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

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES

AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES Jose Javer Garca Moreta Graduate Studet of Physcs ( Sold State ) at UPV/EHU Address: P.O 6 890 Portugalete, Vzcaya (Spa) Phoe: (00) 3 685 77 16

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

Analysis of Variance with Weibull Data

Analysis of Variance with Weibull Data Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad

More information

Analysis of von Kármán plates using a BEM formulation

Analysis of von Kármán plates using a BEM formulation Boudary Elemets ad Other Mesh Reducto Methods XXIX 213 Aalyss of vo Kármá plates usg a BEM formulato L. Wademam & W. S. Vetur São Carlos School of Egeerg, Uversty of São Paulo, Brazl Abstract Ths work

More information

8.1 Hashing Algorithms

8.1 Hashing Algorithms CS787: Advaced Algorthms Scrbe: Mayak Maheshwar, Chrs Hrchs Lecturer: Shuch Chawla Topc: Hashg ad NP-Completeess Date: September 21 2007 Prevously we looked at applcatos of radomzed algorthms, ad bega

More information

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements Aoucemets No-Parametrc Desty Estmato Techques HW assged Most of ths lecture was o the blacboard. These sldes cover the same materal as preseted DHS Bometrcs CSE 90-a Lecture 7 CSE90a Fall 06 CSE90a Fall

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

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

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013 ECE 595, Secto 0 Numercal Smulatos Lecture 9: FEM for Electroc Trasport Prof. Peter Bermel February, 03 Outle Recap from Wedesday Physcs-based devce modelg Electroc trasport theory FEM electroc trasport

More information

2C09 Design for seismic and climate changes

2C09 Design for seismic and climate changes 2C09 Desg for sesmc ad clmate chages Lecture 08: Sesmc aalyss of elastc MDOF systems Aurel Strata, Poltehca Uversty of Tmsoara 06/04/2017 Europea Erasmus Mudus Master Course Sustaable Costructos uder atural

More information

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Joural of Appled Matematcs ad Computatoal Mecacs 04, 3(4), 7-34 FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Ata Cekot, Stasław Kukla Isttute of Matematcs, Czestocowa Uversty of Tecology Częstocowa,

More information

LINEAR REGRESSION ANALYSIS

LINEAR REGRESSION ANALYSIS LINEAR REGRESSION ANALYSIS MODULE V Lecture - Correctg Model Iadequaces Through Trasformato ad Weghtg Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur Aalytcal methods for

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted

More information

Comparison of Analytical and Numerical Results in Modal Analysis of Multispan Continuous Beams with LS-DYNA

Comparison of Analytical and Numerical Results in Modal Analysis of Multispan Continuous Beams with LS-DYNA th Iteratoal S-N Users oferece Smulato Techology omparso of alytcal ad Numercal Results Modal alyss of Multspa otuous eams wth S-N bht Mahapatra ad vk hatteree etral Mechacal Egeerg Research Isttute, urgapur

More information

On the convergence of derivatives of Bernstein approximation

On the convergence of derivatives of Bernstein approximation O the covergece of dervatves of Berste approxmato Mchael S. Floater Abstract: By dfferetatg a remader formula of Stacu, we derve both a error boud ad a asymptotc formula for the dervatves of Berste approxmato.

More information

F. Inequalities. HKAL Pure Mathematics. 進佳數學團隊 Dr. Herbert Lam 林康榮博士. [Solution] Example Basic properties

F. Inequalities. HKAL Pure Mathematics. 進佳數學團隊 Dr. Herbert Lam 林康榮博士. [Solution] Example Basic properties 進佳數學團隊 Dr. Herbert Lam 林康榮博士 HKAL Pure Mathematcs F. Ieualtes. Basc propertes Theorem Let a, b, c be real umbers. () If a b ad b c, the a c. () If a b ad c 0, the ac bc, but f a b ad c 0, the ac bc. Theorem

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

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

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

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

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

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

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM

EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM Jose Javer Garca Moreta Ph. D research studet at the UPV/EHU (Uversty of Basque coutry) Departmet of Theoretcal

More information

ON THE MOTION OF PLANAR BARS SYSTEMS WITH CLEARANCES IN JOINTS

ON THE MOTION OF PLANAR BARS SYSTEMS WITH CLEARANCES IN JOINTS ON THE MOTION OF PLANAR BARS SYSTEMS WITH CLEARANCES IN JOINTS Şl uv dr g Ja-Crsta GRIGORE, Uverstatea d Pteşt, strtîrgu dvale Nr Prof uv dr g Ncolae PANDREA, Uverstatea d Pteşt, strtîrgu dvale Nr Cof

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

CHAPTER 3 POSTERIOR DISTRIBUTIONS

CHAPTER 3 POSTERIOR DISTRIBUTIONS CHAPTER 3 POSTERIOR DISTRIBUTIONS If scece caot measure the degree of probablt volved, so much the worse for scece. The practcal ma wll stck to hs apprecatve methods utl t does, or wll accept the results

More information

Lecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES

Lecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES FDM: Appromato of Frst Order Dervatves Lecture APPROXIMATION OF FIRST ORDER DERIVATIVES. INTRODUCTION Covectve term coservato equatos volve frst order dervatves. The smplest possble approach for dscretzato

More information

DKA method for single variable holomorphic functions

DKA method for single variable holomorphic functions DKA method for sgle varable holomorphc fuctos TOSHIAKI ITOH Itegrated Arts ad Natural Sceces The Uversty of Toushma -, Mamhosama, Toushma, 770-8502 JAPAN Abstract: - Durad-Kerer-Aberth (DKA method for

More information

ECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity

ECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity ECONOMETRIC THEORY MODULE VIII Lecture - 6 Heteroskedastcty Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur . Breusch Paga test Ths test ca be appled whe the replcated data

More information

EFFECT OF PITCH AND NOMINAL DIAMETER ON LOAD DISTRIBUTION AND EFFICIENCY IN MINIATURE LEAD SCREW DRIVES

EFFECT OF PITCH AND NOMINAL DIAMETER ON LOAD DISTRIBUTION AND EFFICIENCY IN MINIATURE LEAD SCREW DRIVES IJRE: Iteratoal Joural of Research Egeerg ad echology eissn: 2319-1163 pissn: 2321-73 EFFEC OF PICH AND NOMINAL DIAMEER ON LOAD DISRIBUION AND EFFICIENCY IN MINIAURE LEAD SCREW DRIVES Vkrat Karmarkar 1,

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

More information

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971))

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971)) art 4b Asymptotc Results for MRR usg RESS Recall that the RESS statstc s a specal type of cross valdato procedure (see Alle (97)) partcular to the regresso problem ad volves fdg Y $,, the estmate at the

More information

Ahmed Elgamal. MDOF Systems & Modal Analysis

Ahmed Elgamal. MDOF Systems & Modal Analysis DOF Systems & odal Aalyss odal Aalyss (hese otes cover sectos from Ch. 0, Dyamcs of Structures, Al Chopra, Pretce Hall, 995). Refereces Dyamcs of Structures, Al K. Chopra, Pretce Hall, New Jersey, ISBN

More information

A Collocation Method for Solving Abel s Integral Equations of First and Second Kinds

A Collocation Method for Solving Abel s Integral Equations of First and Second Kinds A Collocato Method for Solvg Abel s Itegral Equatos of Frst ad Secod Kds Abbas Saadatmad a ad Mehd Dehgha b a Departmet of Mathematcs, Uversty of Kasha, Kasha, Ira b Departmet of Appled Mathematcs, Faculty

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

n -dimensional vectors follow naturally from the one

n -dimensional vectors follow naturally from the one B. Vectors ad sets B. Vectors Ecoomsts study ecoomc pheomea by buldg hghly stylzed models. Uderstadg ad makg use of almost all such models requres a hgh comfort level wth some key mathematcal sklls. I

More information

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical ECE66: Sold State Devces Lecture 13 Solutos of the Cotuty Eqs. Aalytcal & Numercal Gerhard Klmeck gekco@purdue.edu Outle Aalytcal Solutos to the Cotuty Equatos 1) Example problems ) Summary Numercal Solutos

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

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

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

Quantization in Dynamic Smarandache Multi-Space

Quantization in Dynamic Smarandache Multi-Space Quatzato Dyamc Smaradache Mult-Space Fu Yuhua Cha Offshore Ol Research Ceter, Beg, 7, Cha (E-mal: fuyh@cooc.com.c ) Abstract: Dscussg the applcatos of Dyamc Smaradache Mult-Space (DSMS) Theory. Supposg

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

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch

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

Bayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study

Bayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study IJIEST Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue 5, July 04. Bayes Iterval Estmato for bomal proporto ad dfferece of two bomal proportos wth Smulato Study Masoud Gaj, Solmaz hlmad

More information

Lecture Note to Rice Chapter 8

Lecture Note to Rice Chapter 8 ECON 430 HG revsed Nov 06 Lecture Note to Rce Chapter 8 Radom matrces Let Y, =,,, m, =,,, be radom varables (r.v. s). The matrx Y Y Y Y Y Y Y Y Y Y = m m m s called a radom matrx ( wth a ot m-dmesoal dstrbuto,

More information

Numerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract

Numerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract Numercal Smulatos of the Complex Moded Korteweg-de Vres Equato Thab R. Taha Computer Scece Departmet The Uversty of Georga Athes, GA 002 USA Tel 0-542-2911 e-mal thab@cs.uga.edu Abstract I ths paper mplemetatos

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

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON430 Statstcs Date of exam: Frday, December 8, 07 Grades are gve: Jauary 4, 08 Tme for exam: 0900 am 00 oo The problem set covers 5 pages Resources allowed:

More information

Multiple Linear Regression Analysis

Multiple Linear Regression Analysis LINEA EGESSION ANALYSIS MODULE III Lecture - 4 Multple Lear egresso Aalyss Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur Cofdece terval estmato The cofdece tervals multple

More information

Chapter 8. Inferences about More Than Two Population Central Values

Chapter 8. Inferences about More Than Two Population Central Values Chapter 8. Ifereces about More Tha Two Populato Cetral Values Case tudy: Effect of Tmg of the Treatmet of Port-We tas wth Lasers ) To vestgate whether treatmet at a youg age would yeld better results tha

More information

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS Course Project: Classcal Mechacs (PHY 40) Suja Dabholkar (Y430) Sul Yeshwath (Y444). Itroducto Hamltoa mechacs s geometry phase space. It deals

More information

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i CHEMICAL EQUILIBRIA The Thermodyamc Equlbrum Costat Cosder a reversble reacto of the type 1 A 1 + 2 A 2 + W m A m + m+1 A m+1 + Assgg postve values to the stochometrc coeffcets o the rght had sde ad egatve

More information

Point Estimation: definition of estimators

Point Estimation: definition of estimators Pot Estmato: defto of estmators Pot estmator: ay fucto W (X,..., X ) of a data sample. The exercse of pot estmato s to use partcular fuctos of the data order to estmate certa ukow populato parameters.

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

Stress Wave propagation in Electro-Magneto-Elastic plate of arbitrary cross-sections

Stress Wave propagation in Electro-Magneto-Elastic plate of arbitrary cross-sections Iteratoal Joural of Scetfc & Egeerg Research Volume 3, Issue 8, August-1 1 ISSN 9-5518 Stress Wave propagato Electro-Mageto-Elastc plate of arbtrary cross-sectos P. Pousamy Departmet of Mathematcs Govermet

More information

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1)

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1) Chapter 7 Fuctos o Bouded Varato. Subject: Real Aalyss Level: M.Sc. Source: Syed Gul Shah (Charma, Departmet o Mathematcs, US Sargodha Collected & Composed by: Atq ur Rehma (atq@mathcty.org, http://www.mathcty.org

More information

Multiple Choice Test. Chapter Adequacy of Models for Regression

Multiple Choice Test. Chapter Adequacy of Models for Regression Multple Choce Test Chapter 06.0 Adequac of Models for Regresso. For a lear regresso model to be cosdered adequate, the percetage of scaled resduals that eed to be the rage [-,] s greater tha or equal to

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

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation PGE 30: Formulato ad Soluto Geosystems Egeerg Dr. Balhoff Iterpolato Numercal Methods wth MATLAB, Recktewald, Chapter 0 ad Numercal Methods for Egeers, Chapra ad Caale, 5 th Ed., Part Fve, Chapter 8 ad

More information

Special Instructions / Useful Data

Special Instructions / Useful Data JAM 6 Set of all real umbers P A..d. B, p Posso Specal Istructos / Useful Data x,, :,,, x x Probablty of a evet A Idepedetly ad detcally dstrbuted Bomal dstrbuto wth parameters ad p Posso dstrbuto wth

More information

Centroids & Moments of Inertia of Beam Sections

Centroids & Moments of Inertia of Beam Sections RCH 614 Note Set 8 S017ab Cetrods & Momets of erta of Beam Sectos Notato: b C d d d Fz h c Jo L O Q Q = ame for area = ame for a (base) wdth = desgato for chael secto = ame for cetrod = calculus smbol

More information

ANALYTICAL SOLUTION FOR NONLINEAR BENDING OF FG PLATES BY A LAYERWISE THEORY

ANALYTICAL SOLUTION FOR NONLINEAR BENDING OF FG PLATES BY A LAYERWISE THEORY 6 TH ITERATIOAL COFERECE O COMPOSITE MATERIALS AALYTICAL SOLUTIO FOR OLIEAR BEDIG OF FG PLATES BY A LAYERWISE THEORY M. Taha*, S.M. Mrababaee** *Departmet of Mechacal Egeerg, Ferdows Uversty of Mashhad,

More information

Bayes (Naïve or not) Classifiers: Generative Approach

Bayes (Naïve or not) Classifiers: Generative Approach Logstc regresso Bayes (Naïve or ot) Classfers: Geeratve Approach What do we mea by Geeratve approach: Lear p(y), p(x y) ad the apply bayes rule to compute p(y x) for makg predctos Ths s essetally makg

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

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

A tighter lower bound on the circuit size of the hardest Boolean functions

A tighter lower bound on the circuit size of the hardest Boolean functions Electroc Colloquum o Computatoal Complexty, Report No. 86 2011) A tghter lower boud o the crcut sze of the hardest Boolea fuctos Masak Yamamoto Abstract I [IPL2005], Fradse ad Mlterse mproved bouds o the

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

Evaluating Polynomials

Evaluating Polynomials Uverst of Nebraska - Lcol DgtalCommos@Uverst of Nebraska - Lcol MAT Exam Expostor Papers Math the Mddle Isttute Partershp 7-7 Evaluatg Polomals Thomas J. Harrgto Uverst of Nebraska-Lcol Follow ths ad addtoal

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

means the first term, a2 means the term, etc. Infinite Sequences: follow the same pattern forever.

means the first term, a2 means the term, etc. Infinite Sequences: follow the same pattern forever. 9.4 Sequeces ad Seres Pre Calculus 9.4 SEQUENCES AND SERIES Learg Targets:. Wrte the terms of a explctly defed sequece.. Wrte the terms of a recursvely defed sequece. 3. Determe whether a sequece s arthmetc,

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

Lecture 8: Linear Regression

Lecture 8: Linear Regression Lecture 8: Lear egresso May 4, GENOME 56, Sprg Goals Develop basc cocepts of lear regresso from a probablstc framework Estmatg parameters ad hypothess testg wth lear models Lear regresso Su I Lee, CSE

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

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

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

5 Short Proofs of Simplified Stirling s Approximation

5 Short Proofs of Simplified Stirling s Approximation 5 Short Proofs of Smplfed Strlg s Approxmato Ofr Gorodetsky, drtymaths.wordpress.com Jue, 20 0 Itroducto Strlg s approxmato s the followg (somewhat surprsg) approxmato of the factoral,, usg elemetary fuctos:

More information

A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR DIFFERANTIAL EQUATIONS

A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR DIFFERANTIAL EQUATIONS Secer, A., et al.: A New Numerıcal Approach for Solvıg Hıgh-Order Lıear ad No-Lıear... HERMAL SCIENCE: Year 8, Vol., Suppl., pp. S67-S77 S67 A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR

More information

Simple Linear Regression

Simple Linear Regression Correlato ad Smple Lear Regresso Berl Che Departmet of Computer Scece & Iformato Egeerg Natoal Tawa Normal Uversty Referece:. W. Navd. Statstcs for Egeerg ad Scetsts. Chapter 7 (7.-7.3) & Teachg Materal

More information