Current Methodology for Dynamic Stress-Strain Prediction for Structural Health Monitoring and System Load Prediction. Peter Avitabile, Chris Niezrecki

Size: px
Start display at page:

Download "Current Methodology for Dynamic Stress-Strain Prediction for Structural Health Monitoring and System Load Prediction. Peter Avitabile, Chris Niezrecki"

Transcription

1 Curret Methodology for Predictio for Structurl Helth Moitorig d System Lod Predictio Peter Avitbile, Chris Niezrecki Structurl Dymics d Acoustic Systems Lb Uiversity of Msschusetts Lowell

2 Curret Methodology for Dymic Respose Criticl ssumptio tht the lods d boudry coditios for the model re kow DISCRETIZATION ASSEMBLY BC & LOADS SOLVE FOR DISPLACEMENT SOLVE FOR DYNAMIC STRESS-STRAIN FE MODEL UNKNOWN OPERATING LOADS INCORRECT VIRTUAL MODEL PREDICTION INTERIOR MESH UNPREDICTABLE WIND LOADS UNCERTAIN BOUNDARY CONDITIONS DYNAMIC STRESS-STRAIN NOT ACCURATE TRADITIONAL MODELS DO NOT INCORPORATE REAL LOADING AND TRUE IN-OPERATION DEFORMATIONS Fluid structure iterctio models help predict forces but hve my usubsttited ssumptios

3 Fudmetl Chge i Approch Develop FEA model s usul DESCRETIZATION ASSEMBLY Mesure respose usig full field pproches - Potos for discrete poits - Armis for surfce stri Advtge No ssumptio s to lod or boudry coditios Actul displcemet directly obtied MEASURE DISLACEMENT IN-SITU WHILE ROTATING WITH DIC 2 imte

4 Fudmetl Chge i Approch Opertig (Rel-time) displcemets re expded to the full set of lyticl degrees of freedom i the fiite elemet model usig orthogol shpe bsed expsio fuctios. Provides full field displcemet solutio MEASURE DISLACEMENT IN-SITU WHILE ROTATING WITH DIC SURFACE POINT INTERIOR POINT DEVELOP EXPANSION E E g U 2 EXPAND OPERATING DATA T RTO T RTO

5 Theoreticl Approch Expsio Methodology Full-set degrees of freedom obtied from X T X Reduced system mtrices c be writte s T M T T M T K T K T System Equivlet Reductio Expsio Process (SEREP) Trsformtio T U U g u Rel time opertig dt expded usig ERTO T RTO

6 Accelertio (m/s^2) Accelertio (m/s^2) Accelertio (m/s^2) Velocity (m/s) Velocity (m/s) Rel Time Opertig Expsio Expsio process hs bee demostrted for severl structures such s - Apche wig - dryer pel 8 x x Time Steps Apche Helicopter Wig Missile Firig System X directio Y - directio Dryer Pel Rel Time Opertig Dt Whirlpool Dryer Pel Model Correltio Some ctul rel time opertig dt expsio for pel structures Time Steps Z - directio Time Steps Mesuremet Poits Time Steps Expsio Shpe Poits

7 Velocity (m/s) Experimetl Dt Whirlpool Dryer Bse - RTO Expded from 31 set to 31 set with experimetl modes E E g T RTO T U RTO 4 x Time Steps

8 Experimetl Dt Pel Structure Mode 1 Mode 2 Mode 3 set Limited Mesuremet Poits g T U E E RTO T RTO RTO Polytec Scig Vibrometer imte

9 Fudmetl Chge i Approch Usig the rel time opertig dt, expsio of limited sets of dt will be iterjected bck ito the fiite elemet model to predict full field dymic stress-stri SOLVE FOR DYNAMIC STRESS-STRAIN FULL NODAL DISPLACE. SOLUTION FROM REAL-TIME OPERATING DATA EXPANSION WHILE ROTATING t 1 FULL-SPACE REAL-TIME OPERATING DATA STRESS-STRAIN AT TIME 1 FULL-SPACE REAL-TIME OPERATING DATA STRESS-STRAIN AT TIME 2 t 2

10 Mgitude(dB) Amplitude DISPLACEMENT MAGNITUDE (db) Geeric Rib Stiffeed Pel Structure A geeric model is studied to prove methodology SENSOR LOCATION FORCE LOCATION TOP PLATE l b t () Iput Pulse Time (sec) Mode 1: 12.7 Hz Mode 3: 71.2 Hz Mode 2: 45 Hz Mode 4: 9.4 Hz w FIXED END t 1 INTERNAL RIBS BOTTOM PLATE FFT of Iput Pulse FFT of Output Respose t oe sesor loctio Frequecy(Hz) FREQUENCY (Hz) 3D Lser Vibrometer

11 Geeric Structure Expsio Results 3D Lser Vibrometer

12 Geeric Structure Dymic Stress Expsio MODAL CHARACTERISTICS DEVELOP EXPANSION T E E g U EXPAND OPERATING DATA RTO T RTO 4 x Time Time 4 Time 2 Time 3 Dymic stress predictio t vrious times durig trsiet

13 Geeric Structure Dymic Stress Expsio imte

14 Fudmetl Chge i Approch The etire process is summrized below

15 Displcemet (mm) Displcemet (mm) Displcemet (mm) Displcemet (mm) Displcemet (mm) Dymic Displcemet Results Lbortory Structure Extesive testig d lysis hs bee performed to vlidte the proposed methodology 4 Expded PONTOS 4 Expded PONTOS TRAC 99.89%.25 Time (s).7 4 Expded PONTOS TRAC 99.88%.25 Time (s) TRAC 99.27%.25 Time (s).7 4 Expded PONTOS 4 Expded PONTOS 8 7 TRAC 99.63%.25 Time (s).7 TRAC 99.71%.25 Time (s).7

16 Y Norml Stri Y Norml Stri Y Norml Stri Y Norml Stri 1.5 x Dymic Stri Results Lbortory Structure Stri t Loctio 8 FEA Expded 8 x Stri t Loctio 7 FEA Expded Time (s) 1 x 1-5 Modl Stri t Loctio Modl FEA Expded Time (s) 8 x 1-6 Modl Stri t Loctio Modl FEA Expded Time (s) imte Time (s)

17 Vlidtio of Methodology Lbortory Structure Predictio of Full Field Dymic Stress/Stri from Limited Sets of Mesured Dt DEVELOP EXPANSION T E E g U EXPAND OPERATING DATA RTO T RTO 4 x Pw Pigle

18 Covetiol Approch vs. Alterte Approch DISCRETIZATION ASSEMBLY BC & LOADS SOLVE FOR DISPLACEMENT SOLVE FOR DYNAMIC STRESS-STRAIN FE MODEL UNKNOWN OPERATING LOADS INCORRECT VIRTUAL MODEL PREDICTION INTERIOR MESH UNPREDICTABLE WIND LOADS UNCERTAIN BOUNDARY CONDITIONS DYNAMIC STRESS-STRAIN NOT ACCURATE TRADITIONAL MODELS DO NOT INCORPORATE REAL LOADING AND TRUE IN-OPERATION DEFORMATIONS

19 Advtges of Alterte Approch Lodig ssumptios re goe Actul boudry coditios re icluded Displcemet of ctul opertio is obtied Opertig dt is expded directly without the pproximte estimte of force from limited dt Dymic stress-stri obtied for full field

20 Dmge Detectio usig Full Field Stress Stri Model used for expsio with mesured dmge t limited set of mesuremet poits i opertio M K MODEL M T M T M T K T T K T EXPANSION REDUCTION K FORCE PREDICT DYNAMIC STRAIN T U U g U M K M K TEST DAMAGE FORCE TU U U g ERTO T RTO PREDICT DYNAMIC STRAIN FULL FIELD EXPANDED RESPONSE

21 Dmge Detectio usig Full Field Stress Stri Redistributio of lod d stri idicte dmge M K FORCE M K MODEL T M T M T K T T K T EXPANSION REDUCTION T U U g U PREDICT DYNAMIC STRAIN COMPARE DYNAMIC STRAIN M K M K TEST DAMAGE FORCE TU U U g ERTO T RTO PREDICT DYNAMIC STRAIN FULL FIELD EXPANDED RESPONSE

22 Dmge Detectio usig Full Field Stress Stri Respose chge is ot oticeble but curvture d stri due to multimode respose c be see

23 Dmge Detectio usig Full Field Stress Stri FEA predictio, expsio d ctul stri field FE Aticipted Stri Mesured Expded Stri Actul Dmged Stri Stge 18 Stge 14 Stge 1 Stge 6 Stge 2

24 Dmge Detectio usig Full Field Stress Stri FEA predictio, expsio d ctul stri field FE Aticipted Stri Stge 1 Mesured Expded Stri Actul Dmged Stri

25 Curret Methodology for Predictio for Structurl Helth Moitorig d System Lod Predictio DISCRETIZATION ASSEMBLY BC & LOADS SOLVE FOR DISPLACEMENT SOLVE FOR DYNAMIC STRESS-STRAIN UNKNOWN OPERATING LOADS 2 FE MODEL UNPREDICTABLE WIND LOADS UNCERTAIN BOUNDARY CONDITIONS INCORRECT VIRTUAL MODEL PREDICTION DYNAMIC STRESS-STRAIN NOT ACCURATE DISCRETIZATION ASSEMBLY BC & LOADS SOLVE FOR DISPLACEMENT SOLVE FOR DYNAMIC STRESS-STRAIN MEASURE DISLACEMENT IN-SITU WHILE ROTATING WITH DIC IMAGING SYSTEM DEVELOP EXPANSION 2 t 1 t 2 SURFACE POINT PREDICTED INTERIOR POINT EXPAND OPERATING DATA FULL NODAL DISP. SOLUTION FROM REAL-TIME OPERATING DATA EXPANSION WHILE ROTATING t 1 t 2 ARBITRARY TIME 1 FULLY PREDICTED INTERIOR AND SURFACE STRESS-STRAIN ARBITRARY TIME 2 Peter Avitbile, Chris Niezrecki Structurl Dymics d Acoustic Systems Lb Uiversity of Msschusetts Lowell

Prediction of full field dynamic strain from limited sets of measured data

Prediction of full field dynamic strain from limited sets of measured data Shock and Vibration 19 (1) 765 785 765 DOI 1.333/SAV-1-686 IOS Press Prediction of full field dynamic strain from limited sets of measured data Peter Avitabile* and Pawan Pingle Structural Dynamics and

More information

z line a) Draw the single phase equivalent circuit. b) Calculate I BC.

z line a) Draw the single phase equivalent circuit. b) Calculate I BC. ECE 2260 F 08 HW 7 prob 4 solutio EX: V gyb' b' b B V gyc' c' c C = 101 0 V = 1 + j0.2 Ω V gyb' = 101 120 V = 6 + j0. Ω V gyc' = 101 +120 V z LΔ = 9 j1.5 Ω ) Drw the sigle phse equivlet circuit. b) Clculte

More information

sin m a d F m d F m h F dy a dy a D h m h m, D a D a c1cosh c3cos 0

sin m a d F m d F m h F dy a dy a D h m h m, D a D a c1cosh c3cos 0 Q1. The free vibrtio of the plte is give by By ssumig h w w D t, si cos w W x y t B t Substitutig the deflectio ito the goverig equtio yields For the plte give, the mode shpe W hs the form h D W W W si

More information

9.6 Blend-Out Repairs

9.6 Blend-Out Repairs 9.6 Bled-Out Repirs Oe of the ccepted procedures for removig smll mout of crck dmge i the field is through the use of bled-out repirs. These repirs re efficietly ccomplished d for the most prt, retur the

More information

S. Socrate 2013 K. Qian

S. Socrate 2013 K. Qian S. Socrte 213 K. Qi odig Coditios o ech Sectio () pplied lodig oly log the is () of the br. The oly iterl resultt t y sectios is the il force N() Fid N()log the br (il force digrm) by cuttig the br t ech

More information

Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning

Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning Hdout # Title: FAE Course: Eco 8/ Sprig/5 Istructor: Dr I-Mig Chiu Itroductio to Mtrix: Mtrix opertios & Geometric meig Mtrix: rectgulr rry of umers eclosed i pretheses or squre rckets It is covetiolly

More information

S(x)along the bar (shear force diagram) by cutting the bar at x and imposing force_y equilibrium.

S(x)along the bar (shear force diagram) by cutting the bar at x and imposing force_y equilibrium. mmetric leder Bems i Bedig Lodig Coditios o ech ectio () pplied -Forces & z-omets The resultts t sectio re: the bedig momet () d z re sectio smmetr es the sher force () [ for sleder bems stresses d deformtio

More information

NUMERICAL RESEARCH ON THE EQUIVALENT TRANSFORMATION BETWEEN STRUCTURAL DYNAMIC ANALYSIS IN TIME-DOMAIN AND FREQUENCY DOMAIN

NUMERICAL RESEARCH ON THE EQUIVALENT TRANSFORMATION BETWEEN STRUCTURAL DYNAMIC ANALYSIS IN TIME-DOMAIN AND FREQUENCY DOMAIN he 4 th World Coferece o Erthquke Egieerig October -7, 8, Beijig, Chi NUMERICAL RESEARCH ON HE EQUIVALEN RANSFORMAION BEWEEN SRUCURAL DYNAMIC ANALYSIS IN IME-DOMAIN AND FREQUENCY DOMAIN Yuelig Jig,Jibo

More information

Remarks: (a) The Dirac delta is the function zero on the domain R {0}.

Remarks: (a) The Dirac delta is the function zero on the domain R {0}. Sectio Objective(s): The Dirc s Delt. Mi Properties. Applictios. The Impulse Respose Fuctio. 4.4.. The Dirc Delt. 4.4. Geerlized Sources Defiitio 4.4.. The Dirc delt geerlized fuctio is the limit δ(t)

More information

CHAPTER 6: USING MULTIPLE REGRESSION

CHAPTER 6: USING MULTIPLE REGRESSION CHAPTER 6: USING MULTIPLE REGRESSION There re my situtios i which oe wts to predict the vlue the depedet vrible from the vlue of oe or more idepedet vribles. Typiclly: idepedet vribles re esily mesurble

More information

Full-Field Dynamic Stress/Strain from Limited Sets of Measured Data

Full-Field Dynamic Stress/Strain from Limited Sets of Measured Data Full-Field Dynamic Stress/Strain from Limited Sets of Measured Data Pawan Pingle and Peter Avitabile, University of Massachusetts Lowell, Lowell, Massachusetts Often times, occasional events may cause

More information

Section 7.3, Systems of Linear Algebraic Equations; Linear Independence, Eigenvalues, Eigenvectors (the variable vector of the system) and

Section 7.3, Systems of Linear Algebraic Equations; Linear Independence, Eigenvalues, Eigenvectors (the variable vector of the system) and Sec. 7., Boyce & DiPrim, p. Sectio 7., Systems of Lier Algeric Equtios; Lier Idepedece, Eigevlues, Eigevectors I. Systems of Lier Algeric Equtios.. We c represet the system...... usig mtrices d vectors

More information

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k.

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k. . Computtio of Fourier Series I this sectio, we compute the Fourier coefficiets, f ( x) cos( x) b si( x) d b, i the Fourier series To do this, we eed the followig result o the orthogolity of the trigoometric

More information

Definite Integral. The Left and Right Sums

Definite Integral. The Left and Right Sums Clculus Li Vs Defiite Itegrl. The Left d Right Sums The defiite itegrl rises from the questio of fidig the re betwee give curve d x-xis o itervl. The re uder curve c be esily clculted if the curve is give

More information

Impedance Matching Equation: Developed Using Wheeler s Methodology

Impedance Matching Equation: Developed Using Wheeler s Methodology Impedce Mtchig Equtio: Developed Usig Wheeler s Methodology IEEE Log Isld Sectio Ates & Propgtio Society Presettio December 4, 03 By Alfred R. Lopez Outlie. Bckgroud Iformtio. The Impedce Mtchig Equtio

More information

EVALUATING DEFINITE INTEGRALS

EVALUATING DEFINITE INTEGRALS Chpter 4 EVALUATING DEFINITE INTEGRALS If the defiite itegrl represets re betwee curve d the x-xis, d if you c fid the re by recogizig the shpe of the regio, the you c evlute the defiite itegrl. Those

More information

Error-free compression

Error-free compression Error-free compressio Useful i pplictio where o loss of iformtio is tolerble. This mybe due to ccurcy requiremets, legl requiremets, or less th perfect qulity of origil imge. Compressio c be chieved by

More information

Impedance Matching Equation: Developed Using Wheeler s Methodology

Impedance Matching Equation: Developed Using Wheeler s Methodology Impedce Mtchig Equtio: Developed Usig Wheeler s Methodology IEEE Log Isld Sectio Ates & Propgtio Society Presettio December 4, 0 y Alfred R. Lopez Outlie. ckgroud Iformtio. The Impedce Mtchig Equtio. The

More information

Chapter 11 Design of State Variable Feedback Systems

Chapter 11 Design of State Variable Feedback Systems Chpter Desig of Stte Vrible Feedbck Systems This chpter dels with the desig of cotrollers utilizig stte feedbck We will cosider three mjor subjects: Cotrollbility d observbility d the the procedure for

More information

4. When is the particle speeding up? Why? 5. When is the particle slowing down? Why?

4. When is the particle speeding up? Why? 5. When is the particle slowing down? Why? AB CALCULUS: 5.3 Positio vs Distce Velocity vs. Speed Accelertio All the questios which follow refer to the grph t the right.. Whe is the prticle movig t costt speed?. Whe is the prticle movig to the right?

More information

A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD

A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD Diol Bgoo () A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD I. Itroductio The first seprtio of vribles (see pplictios to Newto s equtios) is ver useful method

More information

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields Lecture 38 (Trpped Prticles) Physics 6-01 Sprig 018 Dougls Fields Free Prticle Solutio Schrödiger s Wve Equtio i 1D If motio is restricted to oe-dimesio, the del opertor just becomes the prtil derivtive

More information

F x = 2x λy 2 z 3 = 0 (1) F y = 2y λ2xyz 3 = 0 (2) F z = 2z λ3xy 2 z 2 = 0 (3) F λ = (xy 2 z 3 2) = 0. (4) 2z 3xy 2 z 2. 2x y 2 z 3 = 2y 2xyz 3 = ) 2

F x = 2x λy 2 z 3 = 0 (1) F y = 2y λ2xyz 3 = 0 (2) F z = 2z λ3xy 2 z 2 = 0 (3) F λ = (xy 2 z 3 2) = 0. (4) 2z 3xy 2 z 2. 2x y 2 z 3 = 2y 2xyz 3 = ) 2 0 微甲 07- 班期中考解答和評分標準 5%) Fid the poits o the surfce xy z = tht re closest to the origi d lso the shortest distce betwee the surfce d the origi Solutio Cosider the Lgrge fuctio F x, y, z, λ) = x + y + z

More information

Limit of a function:

Limit of a function: - Limit of fuctio: We sy tht f ( ) eists d is equl with (rel) umer L if f( ) gets s close s we wt to L if is close eough to (This defiitio c e geerlized for L y syig tht f( ) ecomes s lrge (or s lrge egtive

More information

Test Info. Test may change slightly.

Test Info. Test may change slightly. 9. 9.6 Test Ifo Test my chge slightly. Short swer (0 questios 6 poits ech) o Must choose your ow test o Tests my oly be used oce o Tests/types you re resposible for: Geometric (kow sum) Telescopig (kow

More information

: : 8.2. Test About a Population Mean. STT 351 Hypotheses Testing Case I: A Normal Population with Known. - null hypothesis states 0

: : 8.2. Test About a Population Mean. STT 351 Hypotheses Testing Case I: A Normal Population with Known. - null hypothesis states 0 8.2. Test About Popultio Me. Cse I: A Norml Popultio with Kow. H - ull hypothesis sttes. X1, X 2,..., X - rdom smple of size from the orml popultio. The the smple me X N, / X X Whe H is true. X 8.2.1.

More information

A Gear Cutting Predictive Model Using the Finite Element Method

A Gear Cutting Predictive Model Using the Finite Element Method Avilble olie t www.sciecedirect.com Procedi CIP 8 (23 ) 5 56 4 th CIP Coferece o Modelig of Mchiig Opertios (CIP CMMO) A Ger Cuttig Predictive Model Usig the Fiite Elemet Method W. Liu, D. e, S. Usui,

More information

The Reimann Integral is a formal limit definition of a definite integral

The Reimann Integral is a formal limit definition of a definite integral MATH 136 The Reim Itegrl The Reim Itegrl is forml limit defiitio of defiite itegrl cotiuous fuctio f. The costructio is s follows: f ( x) dx for Reim Itegrl: Prtitio [, ] ito suitervls ech hvig the equl

More information

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018

DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS. Assoc. Prof. Dr. Burak Kelleci. Spring 2018 DEPARTMENT OF ELECTRICAL &ELECTRONICS ENGINEERING SIGNALS AND SYSTEMS Assoc. Prof. Dr. Bur Kelleci Sprig 8 OUTLINE The Z-Trsform The Regio of covergece for the Z-trsform The Iverse Z-Trsform Geometric

More information

Algebra II, Chapter 7. Homework 12/5/2016. Harding Charter Prep Dr. Michael T. Lewchuk. Section 7.1 nth roots and Rational Exponents

Algebra II, Chapter 7. Homework 12/5/2016. Harding Charter Prep Dr. Michael T. Lewchuk. Section 7.1 nth roots and Rational Exponents Algebr II, Chpter 7 Hrdig Chrter Prep 06-07 Dr. Michel T. Lewchuk Test scores re vilble olie. I will ot discuss the test. st retke opportuit Sturd Dec. If ou hve ot tke the test, it is our resposibilit

More information

Structural Analysis of Truss Structures using Stiffness Matrix. Dr. Nasrellah Hassan Ahmed

Structural Analysis of Truss Structures using Stiffness Matrix. Dr. Nasrellah Hassan Ahmed Structural Analysis of Truss Structures using Stiffness Matrix Dr. Nasrellah Hassan Ahmed FUNDAMENTAL RELATIONSHIPS FOR STRUCTURAL ANALYSIS In general, there are three types of relationships: Equilibrium

More information

Certain sufficient conditions on N, p n, q n k summability of orthogonal series

Certain sufficient conditions on N, p n, q n k summability of orthogonal series Avilble olie t www.tjs.com J. Nolier Sci. Appl. 7 014, 7 77 Reserch Article Certi sufficiet coditios o N, p, k summbility of orthogol series Xhevt Z. Krsiqi Deprtmet of Mthemtics d Iformtics, Fculty of

More information

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory SMH Uit Polyomils, Epoets, Rdicls & Comple Numbers Notes.1 Number Theory .1 Addig, Subtrctig, d Multiplyig Polyomils Notes Moomil: A epressio tht is umber, vrible, or umbers d vribles multiplied together.

More information

ELG4156 Design of State Variable Feedback Systems

ELG4156 Design of State Variable Feedback Systems ELG456 Desig of Stte Vrible Feedbck Systems This chpter dels with the desig of cotrollers utilizig stte feedbck We will cosider three mjor subjects: Cotrollbility d observbility d the the procedure for

More information

A GENERALIZATION OF GAUSS THEOREM ON QUADRATIC FORMS

A GENERALIZATION OF GAUSS THEOREM ON QUADRATIC FORMS A GENERALIZATION OF GAU THEOREM ON QUADRATIC FORM Nicole I Brtu d Adi N Cret Deprtmet of Mth - Criov Uiversity, Romi ABTRACT A origil result cocerig the extesio of Guss s theorem from the theory of biry

More information

Convergence rates of approximate sums of Riemann integrals

Convergence rates of approximate sums of Riemann integrals Jourl of Approximtio Theory 6 (9 477 49 www.elsevier.com/locte/jt Covergece rtes of pproximte sums of Riem itegrls Hiroyuki Tski Grdute School of Pure d Applied Sciece, Uiversity of Tsukub, Tsukub Ibrki

More information

Riemann Integration. Chapter 1

Riemann Integration. Chapter 1 Mesure, Itegrtio & Rel Alysis. Prelimiry editio. 8 July 2018. 2018 Sheldo Axler 1 Chpter 1 Riem Itegrtio This chpter reviews Riem itegrtio. Riem itegrtio uses rectgles to pproximte res uder grphs. This

More information

POWER SERIES R. E. SHOWALTER

POWER SERIES R. E. SHOWALTER POWER SERIES R. E. SHOWALTER. sequeces We deote by lim = tht the limit of the sequece { } is the umber. By this we me tht for y ε > 0 there is iteger N such tht < ε for ll itegers N. This mkes precise

More information

Uncertainty Analysis of Model for Cuboid Shape Samples Applied on Thermopysical Measurement of Stone Porous Material

Uncertainty Analysis of Model for Cuboid Shape Samples Applied on Thermopysical Measurement of Stone Porous Material MEASUREMENT 11, Proceedigs of the 8th Itertiol Coferece, Smoleice, Slovki Ucertity Alysis of Model for Cuboid Shpe Smples Applied o Thermopysicl Mesuremet of Stoe Porous Mteril 1 V. Boháč, P. Diešk, 1

More information

Fig. 1. I a. V ag I c. I n. V cg. Z n Z Y. I b. V bg

Fig. 1. I a. V ag I c. I n. V cg. Z n Z Y. I b. V bg ymmetricl Compoets equece impedces Although the followig focuses o lods, the results pply eqully well to lies, or lies d lods. Red these otes together with sectios.6 d.9 of text. Cosider the -coected lced

More information

Linear Programming. Preliminaries

Linear Programming. Preliminaries Lier Progrmmig Prelimiries Optimiztio ethods: 3L Objectives To itroduce lier progrmmig problems (LPP To discuss the stdrd d coicl form of LPP To discuss elemetry opertio for lier set of equtios Optimiztio

More information

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1 Appedix A.. Itroductio As discussed i the Chpter 9 o Sequeces d Series, sequece,,...,,... hvig ifiite umber of terms is clled ifiite sequece d its idicted sum, i.e., + + +... + +... is clled ifite series

More information

NONLINEAR MODEL FOR ROTATING MACHINE ROTOR UNDER LARGE DEFORMATION

NONLINEAR MODEL FOR ROTATING MACHINE ROTOR UNDER LARGE DEFORMATION NONINEAR MODE FOR ROTATING MACHINE ROTOR UNDER ARGE DEFORMATION Ami Almsi Rottig Equipmet Deprtmet Tecics Reuids S.A. Mri de Portugl -, Schirro, 85, Mdrid, Spi E-mil: lmsi@trs.es mi_lmssi@yhoo.com KEYWORDS

More information

Notes 17 Sturm-Liouville Theory

Notes 17 Sturm-Liouville Theory ECE 638 Fll 017 Dvid R. Jckso Notes 17 Sturm-Liouville Theory Notes re from D. R. Wilto, Dept. of ECE 1 Secod-Order Lier Differetil Equtios (SOLDE) A SOLDE hs the form d y dy 0 1 p ( x) + p ( x) + p (

More information

Signals & Systems Chapter3

Signals & Systems Chapter3 Sigals & Systems Chapter3 1.2 Discrete-Time (D-T) Sigals Electroic systems do most of the processig of a sigal usig a computer. A computer ca t directly process a C-T sigal but istead eeds a stream of

More information

We will begin by supplying the proof to (a).

We will begin by supplying the proof to (a). (The solutios of problem re mostly from Jeffrey Mudrock s HWs) Problem 1. There re three sttemet from Exmple 5.4 i the textbook for which we will supply proofs. The sttemets re the followig: () The spce

More information

Closed Newton-Cotes Integration

Closed Newton-Cotes Integration Closed Newto-Cotes Itegrtio Jmes Keeslig This documet will discuss Newto-Cotes Itegrtio. Other methods of umericl itegrtio will be discussed i other posts. The other methods will iclude the Trpezoidl Rule,

More information

MODAL ANALYSIS OF CONCRETE ARCH DAMS IN TIME DOMAIN INCLUDING DAM-RESERVOIR INTERACTION

MODAL ANALYSIS OF CONCRETE ARCH DAMS IN TIME DOMAIN INCLUDING DAM-RESERVOIR INTERACTION ABRAC : MODAL ANAL OF CONCREE ARCH DAM N ME DOMAN NCLDNG DAM-REERVOR NERACON B. Poursrtip d V. Lotfi M.c. tudet, Dept. of Civil Eieeri, Amirkbir iversity, ehr, r Professor, Dept. of Civil Eieeri, Amirkbir

More information

Inference on One Population Mean Hypothesis Testing

Inference on One Population Mean Hypothesis Testing Iferece o Oe Popultio Me ypothesis Testig Scerio 1. Whe the popultio is orml, d the popultio vrice is kow i. i. d. Dt : X 1, X,, X ~ N(, ypothesis test, for istce: Exmple: : : : : : 5'7" (ull hypothesis:

More information

Uncertainty Analysis for Uncorrelated Input Quantities and a Generalization

Uncertainty Analysis for Uncorrelated Input Quantities and a Generalization WHITE PAPER Ucertity Alysis for Ucorrelted Iput Qutities d Geerliztio Welch-Stterthwite Formul Abstrct The Guide to the Expressio of Ucertity i Mesuremet (GUM) hs bee widely dopted i the differet fields

More information

Stalnaker s Argument

Stalnaker s Argument Stlker s Argumet (This is supplemet to Coutble Additiviy, Dutch Books d the Sleepig Beuty roblem ) Stlker (008) suggests rgumet tht c be stted thus: Let t be the time t which Beuty wkes o Mody morig. Upo

More information

Time-Domain Representations of LTI Systems

Time-Domain Representations of LTI Systems 2.1 Itroductio Objectives: 1. Impulse resposes of LTI systems 2. Liear costat-coefficiets differetial or differece equatios of LTI systems 3. Bloc diagram represetatios of LTI systems 4. State-variable

More information

Canonical Form and Separability of PPT States on Multiple Quantum Spaces

Canonical Form and Separability of PPT States on Multiple Quantum Spaces Coicl Form d Seprbility of PPT Sttes o Multiple Qutum Spces Xio-Hog Wg d Sho-Mig Fei, 2 rxiv:qut-ph/050445v 20 Apr 2005 Deprtmet of Mthemtics, Cpitl Norml Uiversity, Beijig, Chi 2 Istitute of Applied Mthemtics,

More information

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2 Mth 3, Clculus II Fil Exm Solutios. (5 poits) Use the limit defiitio of the defiite itegrl d the sum formuls to compute 3 x + x. Check your swer by usig the Fudmetl Theorem of Clculus. Solutio: The limit

More information

Surface profiles with zero and finite adhesion force and adhesion instabilities

Surface profiles with zero and finite adhesion force and adhesion instabilities Surfce profiles with zero d fiite dhesio force d dhesio istbilities Vleti L. Popov Techische Uiversität Berli, Str. des 7. Jui 35, 063 Berli, Germy Abstrct. A simple but geerl lysis of the stbility of

More information

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case Chpter : Algebr: A. Bckgroud lgebr: A. Like ters: I lgebric expressio of the for: () x b y c z x y o z d x... p x.. we cosider x, y, z to be vribles d, b, c, d,,, o,.. to be costts. I lgebric expressio

More information

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [

More information

Eigenfunction Expansion. For a given function on the internal a x b the eigenfunction expansion of f(x):

Eigenfunction Expansion. For a given function on the internal a x b the eigenfunction expansion of f(x): Eigefuctio Epsio: For give fuctio o the iterl the eigefuctio epsio of f(): f ( ) cmm( ) m 1 Eigefuctio Epsio (Geerlized Fourier Series) To determie c s we multiply oth sides y Φ ()r() d itegrte: f ( )

More information

Improving XOR-Dominated Circuits by Exploiting Dependencies between Operands. Ajay K. Verma and Paolo Ienne. csda

Improving XOR-Dominated Circuits by Exploiting Dependencies between Operands. Ajay K. Verma and Paolo Ienne. csda Improvig XOR-Domited Circuits y Exploitig Depedecies etwee Operds Ajy K. Verm d Polo Iee csd Processor Architecture Lortory LAP & Cetre for Advced Digitl Systems CSDA Ecole Polytechique Fédérle de Luse

More information

Convergence rates of approximate sums of Riemann integrals

Convergence rates of approximate sums of Riemann integrals Covergece rtes of pproximte sums of Riem itegrls Hiroyuki Tski Grdute School of Pure d Applied Sciece, Uiversity of Tsuku Tsuku Irki 5-857 Jp tski@mth.tsuku.c.jp Keywords : covergece rte; Riem sum; Riem

More information

Section 6.3: Geometric Sequences

Section 6.3: Geometric Sequences 40 Chpter 6 Sectio 6.: Geometric Sequeces My jobs offer ul cost-of-livig icrese to keep slries cosistet with ifltio. Suppose, for exmple, recet college grdute fids positio s sles mger erig ul slry of $6,000.

More information

Lecture 3: A brief background to multivariate statistics

Lecture 3: A brief background to multivariate statistics Lecture 3: A brief bckgroud to multivrite sttistics Uivrite versus multivrite sttistics The mteril of multivrite lysis Displyig multivrite dt The uses of multivrite sttistics A refresher of mtrix lgebr

More information

18.01 Calculus Jason Starr Fall 2005

18.01 Calculus Jason Starr Fall 2005 18.01 Clculus Jso Strr Lecture 14. October 14, 005 Homework. Problem Set 4 Prt II: Problem. Prctice Problems. Course Reder: 3B 1, 3B 3, 3B 4, 3B 5. 1. The problem of res. The ciet Greeks computed the res

More information

Content. Languages, Alphabets and Strings. Operations on Strings. a ab abba baba. aaabbbaaba b 5. Languages. A language is a set of strings

Content. Languages, Alphabets and Strings. Operations on Strings. a ab abba baba. aaabbbaaba b 5. Languages. A language is a set of strings CD5560 FABER Forml guges, Automt d Models of Computtio ecture Mälrdle Uiversity 006 Cotet guges, Alphets d Strigs Strigs & Strig Opertios guges & guge Opertios Regulr Expressios Fiite Automt, FA Determiistic

More information

The Definite Integral

The Definite Integral The Defiite Itegrl A Riem sum R S (f) is pproximtio to the re uder fuctio f. The true re uder the fuctio is obtied by tkig the it of better d better pproximtios to the re uder f. Here is the forml defiitio,

More information

Schrödinger Equation Via Laplace-Beltrami Operator

Schrödinger Equation Via Laplace-Beltrami Operator IOSR Jourl of Mthemtics (IOSR-JM) e-issn: 78-578, p-issn: 39-765X. Volume 3, Issue 6 Ver. III (Nov. - Dec. 7), PP 9-95 www.iosrjourls.org Schrödiger Equtio Vi Lplce-Beltrmi Opertor Esi İ Eskitşçioğlu,

More information

Calculus II Homework: The Integral Test and Estimation of Sums Page 1

Calculus II Homework: The Integral Test and Estimation of Sums Page 1 Clculus II Homework: The Itegrl Test d Estimtio of Sums Pge Questios Emple (The p series) Get upper d lower bouds o the sum for the p series i= /ip with p = 2 if the th prtil sum is used to estimte the

More information

Lesson 4 Linear Algebra

Lesson 4 Linear Algebra Lesso Lier Algebr A fmily of vectors is lierly idepedet if oe of them c be writte s lier combitio of fiitely my other vectors i the collectio. Cosider m lierly idepedet equtios i ukows:, +, +... +, +,

More information

10.5 Test Info. Test may change slightly.

10.5 Test Info. Test may change slightly. 0.5 Test Ifo Test my chge slightly. Short swer (0 questios 6 poits ech) o Must choose your ow test o Tests my oly be used oce o Tests/types you re resposible for: Geometric (kow sum) Telescopig (kow sum)

More information

Solutions of Chapter 5 Part 1/2

Solutions of Chapter 5 Part 1/2 Page 1 of 8 Solutios of Chapter 5 Part 1/2 Problem 5.1-1 Usig the defiitio, compute the -trasform of x[] ( 1) (u[] u[ 8]). Sketch the poles ad eros of X[] i the plae. Solutio: Accordig to the defiitio,

More information

Name of the Student:

Name of the Student: Egieerig Mthemtics 5 NAME OF THE SUBJECT : Mthemtics I SUBJECT CODE : MA65 MATERIAL NAME : Additiol Prolems MATERIAL CODE : HGAUM REGULATION : R UPDATED ON : M-Jue 5 (Sc the ove QR code for the direct

More information

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J.

Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J. Probbility d Stochstic Processes: A Friedly Itroductio for Electricl d Computer Egieers Roy D. Ytes d Dvid J. Goodm Problem Solutios : Ytes d Goodm,4..4 4..4 4..7 4.4. 4.4. 4..6 4.6.8 4.6.9 4.7.4 4.7.

More information

Computability and computational complexity

Computability and computational complexity Computability ad computatioal complexity Lecture 4: Uiversal Turig machies. Udecidability Io Petre Computer Sciece, Åbo Akademi Uiversity Fall 2015 http://users.abo.fi/ipetre/computability/ 21. toukokuu

More information

Probabilistic Investigation of Sensitivities of Advanced Test- Analysis Model Correlation Methods

Probabilistic Investigation of Sensitivities of Advanced Test- Analysis Model Correlation Methods Probbilistic Investigtion of Sensitivities of Advnced Test- Anlysis Model Correltion Methods Liz Bergmn, Mtthew S. Allen, nd Dniel C. Kmmer Dept. of Engineering Physics University of Wisconsin-Mdison Rndll

More information

Approximations of Definite Integrals

Approximations of Definite Integrals Approximtios of Defiite Itegrls So fr we hve relied o tiderivtives to evlute res uder curves, work doe by vrible force, volumes of revolutio, etc. More precisely, wheever we hve hd to evlute defiite itegrl

More information

ELEG 3143 Probability & Stochastic Process Ch. 5 Elements of Statistics

ELEG 3143 Probability & Stochastic Process Ch. 5 Elements of Statistics Deprtet of Electricl Egieerig Uiversity of Arkss ELEG 3143 Probbility & Stochstic Process Ch. 5 Eleets of Sttistics Dr. Jigxi Wu wuj@urk.edu OUTLINE Itroductio: wht is sttistics? Sple e d sple vrice Cofidece

More information

Finite Difference Derivations for Spreadsheet Modeling John C. Walton Modified: November 15, 2007 jcw

Finite Difference Derivations for Spreadsheet Modeling John C. Walton Modified: November 15, 2007 jcw Fiite Differece Derivatios for Spreadsheet Modelig Joh C. Walto Modified: November 15, 2007 jcw Figure 1. Suset with 11 swas o Little Platte Lake, Michiga. Page 1 Modificatio Date: November 15, 2007 Review

More information

INTEGRATION IN THEORY

INTEGRATION IN THEORY CHATER 5 INTEGRATION IN THEORY 5.1 AREA AROXIMATION 5.1.1 SUMMATION NOTATION Fibocci Sequece First, exmple of fmous sequece of umbers. This is commoly ttributed to the mthemtici Fibocci of is, lthough

More information

THE SOLUTION OF THE FRACTIONAL DIFFERENTIAL EQUATION WITH THE GENERALIZED TAYLOR COLLOCATIN METHOD

THE SOLUTION OF THE FRACTIONAL DIFFERENTIAL EQUATION WITH THE GENERALIZED TAYLOR COLLOCATIN METHOD IJRRAS August THE SOLUTIO OF THE FRACTIOAL DIFFERETIAL EQUATIO WITH THE GEERALIZED TAYLOR COLLOCATI METHOD Slih Ylçıbş Ali Kourlp D. Dömez Demir 3* H. Hilmi Soru 4 34 Cell Byr Uiversity Fculty of Art &

More information

ECE 308 Discrete-Time Signals and Systems

ECE 308 Discrete-Time Signals and Systems ECE 38-5 ECE 38 Discrete-Time Sigals ad Systems Z. Aliyazicioglu Electrical ad Computer Egieerig Departmet Cal Poly Pomoa ECE 38-5 1 Additio, Multiplicatio, ad Scalig of Sequeces Amplitude Scalig: (A Costat

More information

Section IV.6: The Master Method and Applications

Section IV.6: The Master Method and Applications Sectio IV.6: The Mster Method d Applictios Defiitio IV.6.1: A fuctio f is symptoticlly positive if d oly if there exists rel umer such tht f(x) > for ll x >. A cosequece of this defiitio is tht fuctio

More information

Solution of the exam in TMA4212 Monday 23rd May 2013 Time: 9:00 13:00

Solution of the exam in TMA4212 Monday 23rd May 2013 Time: 9:00 13:00 Norwegi Uiversity of Sciece d Techology Deprtmet of Mthemticl Scieces Cotct durig the exm: Ele Celledoi, tlf. 735 93541 Pge 1 of 7 of the exm i TMA4212 Mody 23rd My 2013 Time: 9:00 13:00 Allowed ids: Approved

More information

COMPARISON OF LOW WAVENUMBER MODELS FOR TURBULENT BOUNDARY LAYER EXCITATION

COMPARISON OF LOW WAVENUMBER MODELS FOR TURBULENT BOUNDARY LAYER EXCITATION Fluid Dyaics ad Acoustics Office COMPARISON OF LOW WAVENUMBER MODELS FOR TURBULENT BOUNDARY LAYER EXCITATION Peter D. Lysa, Willia K. Boess, ad Joh B. Fahlie Alied Research Laboratory, Pe State Uiversity

More information

REAL-TIME CONDITION MONITORING OF OFFSHORE WIND TURBINES. Simon Watson, Jianping Xiang

REAL-TIME CONDITION MONITORING OF OFFSHORE WIND TURBINES. Simon Watson, Jianping Xiang REAL-TIME CODITIO MOITORIG OF OFFSHORE WID TURBIES Simo Wtso, Jipig Xig Cetre for Reewble Eergy Systems Techology (CREST), Deprtmet of Electroic d Electricl Egieerig, Loughborough Uiversity, Loughborough,

More information

A STUDY OF VIBRATION MEASURING AND FATIGUE ANALYSIS FOR CANTILEVER BEAMS

A STUDY OF VIBRATION MEASURING AND FATIGUE ANALYSIS FOR CANTILEVER BEAMS Joural of Techology, Vol. 3, No., pp. 47-56 (07) 47, * LabView ANSYS A STUDY OF VIBRATION MEASURING AND FATIGUE ANALYSIS FOR CANTILEVER BEAMS Yuo-Ter Tsai, * Hsie-Yag Li Departmet of Mechaical Egieerig

More information

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS) Mthemtics Revisio Guides Itegrtig Trig, Log d Ep Fuctios Pge of MK HOME TUITION Mthemtics Revisio Guides Level: AS / A Level AQA : C Edecel: C OCR: C OCR MEI: C INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

More information

Failure Theories Des Mach Elem Mech. Eng. Department Chulalongkorn University

Failure Theories Des Mach Elem Mech. Eng. Department Chulalongkorn University Failure Theories Review stress trasformatio Failure theories for ductile materials Maimum-Shear-Stress Theor Distortio-Eerg Theor Coulomb-Mohr Theor Failure theories for brittle materials Maimum-Normal-Stress

More information

Geometric Sequences. Geometric Sequence. Geometric sequences have a common ratio.

Geometric Sequences. Geometric Sequence. Geometric sequences have a common ratio. s A geometric sequece is sequece such tht ech successive term is obtied from the previous term by multiplyig by fixed umber clled commo rtio. Exmples, 6, 8,, 6,..., 0, 0, 0, 80,... Geometric sequeces hve

More information

y udv uv y v du 7.1 INTEGRATION BY PARTS

y udv uv y v du 7.1 INTEGRATION BY PARTS 7. INTEGRATION BY PARTS Ever differetitio rule hs correspodig itegrtio rule. For istce, the Substitutio Rule for itegrtio correspods to the Chi Rule for differetitio. The rule tht correspods to the Product

More information

Quadrature Methods for Numerical Integration

Quadrature Methods for Numerical Integration Qudrture Methods for Numericl Itegrtio Toy Sd Istitute for Cle d Secure Eergy Uiversity of Uth April 11, 2011 1 The Need for Numericl Itegrtio Nuemricl itegrtio ims t pproximtig defiite itegrls usig umericl

More information

TEACHER CERTIFICATION STUDY GUIDE

TEACHER CERTIFICATION STUDY GUIDE COMPETENCY 1. ALGEBRA SKILL 1.1 1.1a. ALGEBRAIC STRUCTURES Kow why the real ad complex umbers are each a field, ad that particular rigs are ot fields (e.g., itegers, polyomial rigs, matrix rigs) Algebra

More information

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication Next. Covered bsics of simple desig techique (Divided-coquer) Ch. of the text.. Next, Strsse s lgorithm. Lter: more desig d coquer lgorithms: MergeSort. Solvig recurreces d the Mster Theorem. Similr ide

More information

5.1 - Areas and Distances

5.1 - Areas and Distances Mth 3B Midterm Review Writte by Victori Kl vtkl@mth.ucsb.edu SH 63u Office Hours: R 9:5 - :5m The midterm will cover the sectios for which you hve received homework d feedbck Sectios.9-6.5 i your book.

More information

3.1 Laplace s Equation 3.2 The Method of Images 3.3 Separation of Variables

3.1 Laplace s Equation 3.2 The Method of Images 3.3 Separation of Variables Lecture Note #3B Chpter 3. Potetis 3. Lpce s Equtio 3. The Method of Imges 3.3 Seprtio of ribes 3.3. Crtesi Coordites 3.3. Spheric coordites 3.4 Mutipoe Expsio Boudry coditios re very importt to sove the

More information

ELEG 5173L Digital Signal Processing Ch. 2 The Z-Transform

ELEG 5173L Digital Signal Processing Ch. 2 The Z-Transform Deprtmet of Electricl Egieerig Uiversity of Arkss ELEG 573L Digitl Sigl Processig Ch. The Z-Trsform Dr. Jigxi Wu wuj@urk.edu OUTLINE The Z-Trsform Properties Iverse Z-Trsform Z-Trsform of LTI system Z-TRANSFORM

More information

2.1.1 Definition The Z-transform of a sequence x [n] is simply defined as (2.1) X re x k re x k r

2.1.1 Definition The Z-transform of a sequence x [n] is simply defined as (2.1) X re x k re x k r Z-Trsforms. INTRODUCTION TO Z-TRANSFORM The Z-trsform is coveiet d vluble tool for represetig, lyig d desigig discrete-time sigls d systems. It plys similr role i discrete-time systems to tht which Lplce

More information

lecture 16: Introduction to Least Squares Approximation

lecture 16: Introduction to Least Squares Approximation 97 lecture 16: Itroductio to Lest Squres Approximtio.4 Lest squres pproximtio The miimx criterio is ituitive objective for pproximtig fuctio. However, i my cses it is more ppelig (for both computtio d

More information

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations ECE-S352 Itroductio to Digital Sigal Processig Lecture 3A Direct Solutio of Differece Equatios Discrete Time Systems Described by Differece Equatios Uit impulse (sample) respose h() of a DT system allows

More information

Chapter 7 Infinite Series

Chapter 7 Infinite Series MA Ifiite Series Asst.Prof.Dr.Supree Liswdi Chpter 7 Ifiite Series Sectio 7. Sequece A sequece c be thought of s list of umbers writte i defiite order:,,...,,... 2 The umber is clled the first term, 2

More information

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Dr. Hamid R. Rabiee Fall 2013

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Dr. Hamid R. Rabiee Fall 2013 Sigls & Systems Chpter 0: The Z-Trsform Adpted from: Lecture otes from MIT, Bighmto Uiversity Dr. Hmid R. Rbiee Fll 03 Lecture 5 Chpter 0 Lecture 6 Chpter 0 Outlie Itroductio to the -Trsform Properties

More information