REDUCING THE POSSIBILITY OF SUBJECTIVE ERROR IN THE DETERMINATION OF THE STRUCTURE-FUNCTION-BASED EFFECTIVE THERMAL CONDUCTIVITY OF BOARDS

Size: px
Start display at page:

Download "REDUCING THE POSSIBILITY OF SUBJECTIVE ERROR IN THE DETERMINATION OF THE STRUCTURE-FUNCTION-BASED EFFECTIVE THERMAL CONDUCTIVITY OF BOARDS"

Transcription

1 Nice, Côte d Azur, Frace, Septeber 2006 REDUCING THE POSSIBILITY OF SUBJECTIVE ERROR IN THE DETERMINATION OF THE STRUCTURE-FUNCTION-BASED EFFECTIVE THERMAL CONDUCTIVITY OF BOARDS Erő Kollár, Vladiír Székely BUTE, Departet of Electro Devices, H-52 Golda Gy. tér 3, Budapest, Hugary <kollar szekely@eet.be.hu> ABSTRACT The theral respose fuctio give to a uit-step dissipatio accurately characterizes the theral syste. Istead of the theral respose fuctio the so-called structure fuctio describig three-diesioal as the equivalet odel of oe-diesioal heat-spreadig, created fro the theral respose fuctio with the help of coplex atheatical procedures, is ofte used. Usig the structure fuctio the partial theral capacity ad partial heat resistace of certai eleets of the theral syste ca be idetified. If the geoetrical easureets of a theral syste of siple geoetry ad hoogeeous aterial (such as a hoogeeous rod or board, etc.) are kow, the coefficiet of theral coductivity of the aterial i questio ca be deteried fro two poits of the structure fuctio at 2-5 per cet of accuracy. I this paper a ethod is preseted which applies a wide rage/sectio istead of two poits of the cuulative structure fuctio to deterie the theral coefficiet, thus reducig the subjective error derivig fro the selectio of the two poits. The above ethod is preseted ad illustrated i siulated as well as easured theral trasiet resposes. R Σ ( ) = R i i= ad the cuulative theral capacitace is: C Σ ( ) = C i i=, (), (2) where R i ad C i deote the eleet values of the i-th stage of the Cauer-type odel etwork. Plottig the C Σ vs. R Σ values results i the cuulative structure fuctio (Figure 2).. INTRODUCTION The structure fuctios are graphical represetatios of the RC-odel (Cauer-etwork) of the theral syste (Figure ). Figure : The RC-odel of the theral syste. Figure 2: The cuulative structure fuctio. The cuulative structure fuctio characteristic of board-like aterials of hoogeeous isotropic coductivity (Figure 3). The theral resistace betwee the -th eleet of the odel etwork ad the heat source (drivig poit) is: TIMA Editios/THERMINIC page- ISBN:

2 Erő Kollár, Vladiír Székely Reducig the possibility of subjective error i the deteriatio of the structure-fuctio-based... Cth [Ws/K] T3Ster Master: cuulative structure fuctio(s) = W/K THE -FINDER ALGORITHM The -fider algorith deteries the theral coductivity coefficiet fro the itegrated structure fuctio of the board-like aterials. The algorith exaies how the steepess of the graph (curve) chages if the syetrical iediate eighborhood of the give poit i the itegrated structure fuctio is syetrically exteded e Figure 3: The cuulative structure fuctio of hoogeeous board. I order to deterie the coductivity value o the liear rage fro the itegrated structure fuctio []: The steps of the algorith are the followig: Coductivity values are deteried i each poit of the rage accordig to (4) Cth( + ) π Cth( ) ( R ) = l, th (4) w 4 R th( + ) Rth( ) w C Σ2 l C = 4π R R Σ, Σ2 Σ (3) where w is the thickess of the board, ad i the idexes of R th ad C th idicates the R th ad C th values plus (+) saples towards the higher values ad ius ( ) saples towards the saller values fro the poit exaied. ( = 20). where w is the thickess of the board ad the R ad C idexes idicate the values belogig to the selected poits. The ai aspect of the selectio of the two poits is that both should be withi the iddle, liear (labda easurig) rage ad should ot be idetical. Our siulatios carried out by the SuRed [2] siulatio progra showed that cosiderig the criteria of the above etioed ethod as a basis ad keepig i id the aspects of accuracy these criteria are ot eough. I the selectio of the two poits there always reais a certai degree of subjectivity, the subjectivity of the perso carryig out the evaluatio, which appears as a error whe deteriig the theral coductivity. Therefore we have elaborated a ethod to reduce subjective error, which applies a wide rage/sectio istead of two poits of the cuulative structure fuctio to deterie the theral coefficiet [3]. It is a additioal advatage of the ethod that it deteries the iflectio poit of the selected rage ore accurately, tha deteriig it fro the secod derivative accordig to the R th. Fro the coductivity values belogig to a certai poit of the rage (R th ) average(s) (5) ad δ (R th ) relative deviatio(s) (6) are deteried. ( R ) ) = ), (5) = ( R ) ( ) )) = ( ) δ th = (6) th Describe the δ (R th ) relative deviatios ad (R th ) average theral coductivity(ies) i relatio to R th theral resistace. We seek iial values i the δ (R th ) deviatio fuctios. Where the δ (R th ) fuctios together give the sallest iiu, this δ (R th ) value belogig to the R th poit gives the effective theral coductivity o (R th ) fuctio as well as the iflectio poit of the itegrated structure fuctio. Note: The ax = 20 ad values are experietal oes. The algorith does ot exclude the use of ay other ax ad values. 2 TIMA Editios/THERMINIC page- ISBN:

3 Erő Kollár, Vladiír Székely Reducig the possibility of subjective error i the deteriatio of the structure-fuctio-based EXAMPLE I. I this exaple we started fro the siulatio of the theral trasiet heat respose of the --thick hoogeeous copper board i vacuu. We created a itegrated structure fuctio fro the gaied theral respose fuctio usig the T3Ster-Master [4] progra. The progra deteries coductivity fro two poits of the itegrated structure fuctio selected at rado ad a board thickess give at rado. The calculated theral coductivity of the saple ay differ fro the 390 W/K value set as siulatio paraeter eve with.5 per cet, depedig o the two selected poits (Figure 4). Cth [Ws/K] T3Ster Master: cuulative structure fuctio(s) = W/K e Figure 4: The itegrated structure fuctio of the -thick ECU57 saple siulated i vacuu Let us eploy the -fider algorith for the calculated itegrated structure fuctio ad describe the δ (R th ) relative deviatios i relatio to the R th theral resistace. Relative deviatio 3,5% 3,0% 2,5% 2,0%,5%,0% 0,5% =20 =5 =0 =5 The sallest deviatios 0,0%,0,2,4,6,8 2,0 2,2 2,4 Figure 5: The δ (R th ) relative deviatio fuctios of the saple The sallest deviatios are gaied at R th =.73 W/K. Describig the (R th ) average theral coductivity values i relatio to R th heat resistace we ca read the values belogig to the above theral coductivity resistace. Figure 6 shows the fuctio ad Chart suarizes the values read. The sallest iius of the relative deviatio fuctios desigate accurately that R th poit where the deteriatio of the theral coductivity value is advisable. With the help of the sallest iiu poits foud i the relative deviatio fuctio of theral coductivity we are able to prevet the appearace of subjective error at the deteriatio of theral coductivity value derived fro two poits. Theral coductivity [W/K] W/K = =5 384 =0 382 = K/W 374,0,2,4,6,8 2,0 2,2 2,4 Figure 6: The (R th ) average theral coductivity fuctios of the saple I certai cases it ight be ecessary to deterie the iflectio poit of the cuulative structure fuctio. How-ever, the deteriatio fro the secod derivative accordig to the R th is ot always a preferable solutio. The double derivatio ay icrease the oise the fuctio so uch that we ca select the iflectio poit oly i a subjective aer. The -fider algorith sooths dow this oise ad provides the iflectio poit of the cuulative structure fuctio at the sallest iiu poit of the deviatio fuctios. M δ [%] [W/K] R th [K/W] Chart : Theral coductivity of the ECU-57 saple deteried by the -fider ethod (w = ) TIMA Editios/THERMINIC page- ISBN:

4 Erő Kollár, Vladiír Székely Reducig the possibility of subjective error i the deteriatio of the structure-fuctio-based EXAMPLE II, EFFECTIVE THERMAL CONDUCTIVITY OF PCBS Fro the aspect of easureet techology the easure of the effective theral coductivity of PCBs is greatly siplified by the fact that it ca be carried out i the air as well ad it is ot ecessary to use vacuu. I that case, however, the shutig effect of the air ust soehow be take ito cosideratio. I this experiet we siulated the theral trasiet respose of --thick boards havig theral coductivity betwee 2 ad 4 W/K i air. Due to the shutig effect of the air the theral coductivity values of the board siulated i the air deteried o the basis of the structure fuctio are, of course, higher tha the values adjusted as the paraeters of the siulatio. The shutig effect of the air chages the derivig theral coductivity oly a little, but the size of this error ca be easured i relatio to the subjective error appearig at the selectio of the two poits. I the experiets we eployed the followig cylider-syetrical structure (Figure 7). Fro the aspect of easureet techology it is advisable to use such a group of graphs which gives the theral coductivity of the saple (that is, easured i vacuu) fro the theral coductivity values easured i the air (Figure 9). Theral coductivity i siulator / deteried theral coductivity 00% 99% 98% 97% 96% 95% 94% 93% 92% 9% 90% w = radius = 0 radius = 20 radius = Theral coductivity deteried withi the labda easurig rage, siulated i the air [W/K] Figure 9: Theral coductivity adjustet curves of the saple for the easy easurig 5. CONCLUSIONS Figure 7: The board theral coductivity easureet setup Usig the -fider algorith we deteried the relative icrease of the theral coductivity values of the board ad plotted it i relatio to the paraeter of the siulatio burdeed with the shutig effect of the air (Figure 8). Relative icrease of the theral coductivity deteried withi the labda easurig rage, siulated i the air 0% 9% 8% 7% 6% 5% 4% 3% 2% % 0% y = 3,57E-0x -,47E+00 R 2 = 9,75E-0 y = 3,80E-0x -,75E+00 R 2 = 9,54E-0 radius = 30 radius = 20 radius = 0 w = y = 4,75E-0x -2,39E+00 R 2 = 9,70E Theral coductivity as the paraeter of the siulator, Labda [W/K] Figure 8: The air surroudig the board icreases theral coductivity We have created a algorith which reduces the subjective error appearig at the deteriatio of the local theral coductivity based o structure fuctio of board-like aterials i a way that it applies a wide rage istead of two poits of the cuulative structure fuctio to deterie the theral coefficiet. We have show two applicatios for the algorith. This algorith is advatageous whe the subjective error is coesurable to other errors, for exaple the shutig effect of the air at the deteriatio of the effective theral coductivity of boards. 6. ACKNOWLEDGEMENTS This work was partially supported by the PATENT IST Project of the EU, ad by the 2/08/NKFP- 200 INFOTERM Projects of the Hugaria Goveret. 7. REFERENCES [] V. Székely, M. Recz, S. Török, ad S. Ress: Calculatig effective board theral paraeters fro trasiet easureets, IEEE Trasactios o Copoets ad Packagig Techology, Vol. 24, NO.4, pp , Deceber 200. [2] TIMA Editios/THERMINIC page- ISBN:

5 Erő Kollár, Vladiír Székely Reducig the possibility of subjective error i the deteriatio of the structure-fuctio-based... [3] M. Recz, A. Poppe, E. Kollár, S. Ress, ad V. Székely: Icreasig the accuracy of structure fuctio based theral aterial paraeter easureets, IEEE Trasactios o Copoets ad Packagig Techologies, Vol. 28, ISS, pp. 5-57, March [4] TIMA Editios/THERMINIC page- ISBN:

(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1

(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1 ROOT LOCUS TECHNIQUE 93 should be desiged differetly to eet differet specificatios depedig o its area of applicatio. We have observed i Sectio 6.4 of Chapter 6, how the variatio of a sigle paraeter like

More information

AVERAGE MARKS SCALING

AVERAGE MARKS SCALING TERTIARY INSTITUTIONS SERVICE CENTRE Level 1, 100 Royal Street East Perth, Wester Australia 6004 Telephoe (08) 9318 8000 Facsiile (08) 95 7050 http://wwwtisceduau/ 1 Itroductio AVERAGE MARKS SCALING I

More information

The state space model needs 5 parameters, so it is not as convenient to use in this control study.

The state space model needs 5 parameters, so it is not as convenient to use in this control study. Trasfer fuctio for of the odel G θ K ω 2 θ / v θ / v ( s) = = 2 2 vi s + 2ζωs + ω The followig slides detail a derivatio of this aalog eter odel both as state space odel ad trasfer fuctio (TF) as show

More information

Chapter 2. Asymptotic Notation

Chapter 2. Asymptotic Notation Asyptotic Notatio 3 Chapter Asyptotic Notatio Goal : To siplify the aalysis of ruig tie by gettig rid of details which ay be affected by specific ipleetatio ad hardware. [1] The Big Oh (O-Notatio) : It

More information

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data Lecture 9 Curve fittig I Itroductio Suppose we are preseted with eight poits of easured data (x i, y j ). As show i Fig. o the left, we could represet the uderlyig fuctio of which these data are saples

More information

Vasyl Moisyshyn*, Bogdan Borysevych*, Oleg Vytyaz*, Yuriy Gavryliv*

Vasyl Moisyshyn*, Bogdan Borysevych*, Oleg Vytyaz*, Yuriy Gavryliv* AGH DRILLING, OIL, GAS Vol. 3 No. 3 204 http://dx.doi.org/0.7494/drill.204.3.3.43 Vasyl Moisyshy*, Bogda Borysevych*, Oleg Vytyaz*, Yuriy Gavryliv* DEVELOPMENT OF THE MATHEMATICAL MODELS OF THE INTEGRAL

More information

CHAPTER 6 RESISTANCE FACTOR FOR THE DESIGN OF COMPOSITE SLABS

CHAPTER 6 RESISTANCE FACTOR FOR THE DESIGN OF COMPOSITE SLABS CHAPTER 6 RESISTANCE FACTOR FOR THE DESIGN OF COMPOSITE SLABS 6.1. Geeral Probability-based desig criteria i the for of load ad resistace factor desig (LRFD) are ow applied for ost costructio aterials.

More information

AN EFFICIENT ESTIMATION METHOD FOR THE PARETO DISTRIBUTION

AN EFFICIENT ESTIMATION METHOD FOR THE PARETO DISTRIBUTION Joural of Statistics: Advaces i Theory ad Applicatios Volue 3, Nuber, 00, Pages 6-78 AN EFFICIENT ESTIMATION METHOD FOR THE PARETO DISTRIBUTION Departet of Matheatics Brock Uiversity St. Catharies, Otario

More information

Sample size calculations. $ available $ per sample

Sample size calculations. $ available $ per sample Saple size calculatios = $ available $ per saple Too few aials A total waste Too ay aials A partial waste Power X 1,...,X iid oralµ A, A Y 1,...,Y iid oralµ B, B Test H 0 : µ A = µ B vs H a : µ A µ B at

More information

Note that the argument inside the second square root is always positive since R L > Z 0. The series reactance can be found as

Note that the argument inside the second square root is always positive since R L > Z 0. The series reactance can be found as Ipedace Matchig Ipedace Matchig Itroductio Ipedace atchig is the process to atch the load to a trasissio lie by a atchig etwork, as depicted i Fig Recall that the reflectios are eliiated uder the atched

More information

Optimal Estimator for a Sample Set with Response Error. Ed Stanek

Optimal Estimator for a Sample Set with Response Error. Ed Stanek Optial Estiator for a Saple Set wit Respose Error Ed Staek Itroductio We develop a optial estiator siilar to te FP estiator wit respose error tat was cosidered i c08ed63doc Te first 6 pages of tis docuet

More information

Hypothesis tests and confidence intervals

Hypothesis tests and confidence intervals Hypothesis tests ad cofidece itervals The 95% cofidece iterval for µ is the set of values, µ 0, such that the ull hypothesis H 0 : µ = µ 0 would ot be rejected by a two-sided test with α = 5%. The 95%

More information

Studying Interaction of Cotton-Raw Material with Working Bodies of Cotton-Cleaning Machines

Studying Interaction of Cotton-Raw Material with Working Bodies of Cotton-Cleaning Machines ISSN: 35-38 Iteratioal Joural of AdvacedResearch i Sciece, Egieerig ad Techology Vol. 5, Issue, Deceber 8 Studyig Iteractio of Cotto-Raw Material with Workig Bodies of Cotto-Cleaig Machies R.H. Rosulov,

More information

Orthogonal Functions

Orthogonal Functions Royal Holloway Uiversity of odo Departet of Physics Orthogoal Fuctios Motivatio Aalogy with vectors You are probably failiar with the cocept of orthogoality fro vectors; two vectors are orthogoal whe they

More information

Statistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting

Statistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting Statistics ad Data Aalysis i MATLAB Kedrick Kay, kedrick.kay@wustl.edu February 28, 2014 Lecture 4: Model fittig 1. The basics - Suppose that we have a set of data ad suppose that we have selected the

More information

We have also learned that, thanks to the Central Limit Theorem and the Law of Large Numbers,

We have also learned that, thanks to the Central Limit Theorem and the Law of Large Numbers, Cofidece Itervals III What we kow so far: We have see how to set cofidece itervals for the ea, or expected value, of a oral probability distributio, both whe the variace is kow (usig the stadard oral,

More information

Perturbation Theory, Zeeman Effect, Stark Effect

Perturbation Theory, Zeeman Effect, Stark Effect Chapter 8 Perturbatio Theory, Zeea Effect, Stark Effect Ufortuately, apart fro a few siple exaples, the Schrödiger equatio is geerally ot exactly solvable ad we therefore have to rely upo approxiative

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/21 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-25 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

PARTIAL DIFFERENTIAL EQUATIONS SEPARATION OF VARIABLES

PARTIAL DIFFERENTIAL EQUATIONS SEPARATION OF VARIABLES Diola Bagayoko (0 PARTAL DFFERENTAL EQUATONS SEPARATON OF ARABLES. troductio As discussed i previous lectures, partial differetial equatios arise whe the depedet variale, i.e., the fuctio, varies with

More information

Exercise 8 CRITICAL SPEEDS OF THE ROTATING SHAFT

Exercise 8 CRITICAL SPEEDS OF THE ROTATING SHAFT Exercise 8 CRITICA SEEDS OF TE ROTATING SAFT. Ai of the exercise Observatio ad easureet of three cosecutive critical speeds ad correspodig odes of the actual rotatig shaft. Copariso of aalytically coputed

More information

x !1! + 1!2!

x !1! + 1!2! 4 Euler-Maclauri Suatio Forula 4. Beroulli Nuber & Beroulli Polyoial 4.. Defiitio of Beroulli Nuber Beroulli ubers B (,,3,) are defied as coefficiets of the followig equatio. x e x - B x! 4.. Expreesio

More information

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1)

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1) Suer MA 1500 Lesso 1 Sectio 1.6, Sectio 1.7 (part 1) I Solvig Polyoial Equatios Liear equatio ad quadratic equatios of 1 variable are specific types of polyoial equatios. Soe polyoial equatios of a higher

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

Statistics for Applications Fall Problem Set 7

Statistics for Applications Fall Problem Set 7 18.650. Statistics for Applicatios Fall 016. Proble Set 7 Due Friday, Oct. 8 at 1 oo Proble 1 QQ-plots Recall that the Laplace distributio with paraeter λ > 0 is the cotiuous probaλ bility easure with

More information

Lecture 11. Solution of Nonlinear Equations - III

Lecture 11. Solution of Nonlinear Equations - III Eiciecy o a ethod Lecture Solutio o Noliear Equatios - III The eiciecy ide o a iterative ethod is deied by / E r r: rate o covergece o the ethod : total uber o uctios ad derivative evaluatios at each step

More information

The Binomial Multi-Section Transformer

The Binomial Multi-Section Transformer 4/15/2010 The Bioial Multisectio Matchig Trasforer preset.doc 1/24 The Bioial Multi-Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where:

More information

X. Perturbation Theory

X. Perturbation Theory X. Perturbatio Theory I perturbatio theory, oe deals with a ailtoia that is coposed Ĥ that is typically exactly solvable of two pieces: a referece part ad a perturbatio ( Ĥ ) that is assued to be sall.

More information

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions ECE 9 Lecture 4: Estiatio of Lipschitz sooth fuctios R. Nowak 5/7/29 Cosider the followig settig. Let Y f (X) + W, where X is a rado variable (r.v.) o X [, ], W is a r.v. o Y R, idepedet of X ad satisfyig

More information

1 Inferential Methods for Correlation and Regression Analysis

1 Inferential Methods for Correlation and Regression Analysis 1 Iferetial Methods for Correlatio ad Regressio Aalysis I the chapter o Correlatio ad Regressio Aalysis tools for describig bivariate cotiuous data were itroduced. The sample Pearso Correlatio Coefficiet

More information

Geometry Unit 3 Notes Parallel and Perpendicular Lines

Geometry Unit 3 Notes Parallel and Perpendicular Lines Review Cocepts: Equatios of Lies Geoetry Uit Notes Parallel ad Perpedicular Lies Syllabus Objective:. - The studet will differetiate aog parallel, perpedicular, ad skew lies. Lies that DO NOT itersect:

More information

Integrals of Functions of Several Variables

Integrals of Functions of Several Variables Itegrals of Fuctios of Several Variables We ofte resort to itegratios i order to deterie the exact value I of soe quatity which we are uable to evaluate by perforig a fiite uber of additio or ultiplicatio

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information

Non-asymptotic sequential confidence regions with fixed sizes for the multivariate nonlinear parameters of regression. Andrey V.

Non-asymptotic sequential confidence regions with fixed sizes for the multivariate nonlinear parameters of regression. Andrey V. No-asyptotic sequetial cofidece regios with fixed sizes for the ultivariate oliear paraeters of regressio Adrey V Tiofeev Abstract I this paper we cosider a sequetial desig for estiatio of o-liear paraeters

More information

Group Technology and Facility Layout

Group Technology and Facility Layout Group Techology ad Facility Layout Chapter 6 Beefits of GT ad Cellular Maufacturig (CM) REDUCTIONS Setup tie Ivetory Material hadlig cost Direct ad idirect labor cost IMPROVEMENTS Quality Material Flow

More information

ORDANOVA: Analysis of Ordinal Variation

ORDANOVA: Analysis of Ordinal Variation It. Statistical Ist.: Proc. 58th World Statistical Cogress, 0, Dubli (Sessio CPS040) p.48 ORDANOVA: Aalysis of Ordial Variatio Gadrich, Taar ORT Braude College, Idustrial Egieerig ad aageet Departet 5

More information

Bertrand s postulate Chapter 2

Bertrand s postulate Chapter 2 Bertrad s postulate Chapter We have see that the sequece of prie ubers, 3, 5, 7,... is ifiite. To see that the size of its gaps is ot bouded, let N := 3 5 p deote the product of all prie ubers that are

More information

) is a square matrix with the property that for any m n matrix A, the product AI equals A. The identity matrix has a ii

) is a square matrix with the property that for any m n matrix A, the product AI equals A. The identity matrix has a ii square atrix is oe that has the sae uber of rows as colus; that is, a atrix. he idetity atrix (deoted by I, I, or [] I ) is a square atrix with the property that for ay atrix, the product I equals. he

More information

Define a Markov chain on {1,..., 6} with transition probability matrix P =

Define a Markov chain on {1,..., 6} with transition probability matrix P = Pla Group Work 0. The title says it all Next Tie: MCMC ad Geeral-state Markov Chais Midter Exa: Tuesday 8 March i class Hoework 4 due Thursday Uless otherwise oted, let X be a irreducible, aperiodic Markov

More information

1.2 AXIOMATIC APPROACH TO PROBABILITY AND PROPERTIES OF PROBABILITY MEASURE 1.2 AXIOMATIC APPROACH TO PROBABILITY AND

1.2 AXIOMATIC APPROACH TO PROBABILITY AND PROPERTIES OF PROBABILITY MEASURE 1.2 AXIOMATIC APPROACH TO PROBABILITY AND NTEL- robability ad Distributios MODULE 1 ROBABILITY LECTURE 2 Topics 1.2 AXIOMATIC AROACH TO ROBABILITY AND ROERTIES OF ROBABILITY MEASURE 1.2.1 Iclusio-Exclusio Forula I the followig sectio we will discuss

More information

II. Descriptive Statistics D. Linear Correlation and Regression. 1. Linear Correlation

II. Descriptive Statistics D. Linear Correlation and Regression. 1. Linear Correlation II. Descriptive Statistics D. Liear Correlatio ad Regressio I this sectio Liear Correlatio Cause ad Effect Liear Regressio 1. Liear Correlatio Quatifyig Liear Correlatio The Pearso product-momet correlatio

More information

Lecture 8 & Tutorial 1: Experimental idention of low order model

Lecture 8 & Tutorial 1: Experimental idention of low order model Eurother Advaced School Metti 5 Roscoff Jue 13-18, 211 Lecture 8 & utorial 1: Experietal idetio of low order odel Jea-Luc Battaglia, Laboratory I2M, Departet REFLE, I2M Bordeaux Measureet iversio 35 3

More information

The Hypergeometric Coupon Collection Problem and its Dual

The Hypergeometric Coupon Collection Problem and its Dual Joural of Idustrial ad Systes Egieerig Vol., o., pp -7 Sprig 7 The Hypergeoetric Coupo Collectio Proble ad its Dual Sheldo M. Ross Epstei Departet of Idustrial ad Systes Egieerig, Uiversity of Souther

More information

S. A. ALIEV, Y. I. YELEYKO, Y. V. ZHERNOVYI. STEADY-STATE DISTRIBUTIONS FOR CERTAIN MODIFICATIONS OF THE M/M/1/m QUEUEING SYSTEM

S. A. ALIEV, Y. I. YELEYKO, Y. V. ZHERNOVYI. STEADY-STATE DISTRIBUTIONS FOR CERTAIN MODIFICATIONS OF THE M/M/1/m QUEUEING SYSTEM Trasactios of Azerbaija Natioal Acadey of Scieces, Series of Physical-Techical ad Matheatical Scieces: Iforatics ad Cotrol Probles 009 Vol XXIX, 6 P 50-58 S A ALIEV, Y I YELEYKO, Y V ZHERNOVYI STEADY-STATE

More information

The Binomial Multi- Section Transformer

The Binomial Multi- Section Transformer 4/4/26 The Bioial Multisectio Matchig Trasforer /2 The Bioial Multi- Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where: ( ω ) = + e +

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/2010 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-250 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

Binomial transform of products

Binomial transform of products Jauary 02 207 Bioial trasfor of products Khristo N Boyadzhiev Departet of Matheatics ad Statistics Ohio Norther Uiversity Ada OH 4580 USA -boyadzhiev@ouedu Abstract Give the bioial trasfors { b } ad {

More information

Closed virial equation-of-state for the hard-disk fluid

Closed virial equation-of-state for the hard-disk fluid Physical Review Letter LT50 receipt of this auscript 6 Jue 00 Closed virial equatio-of-state for the hard-disk fluid Athoy Beris ad Leslie V. Woodcock Departet of Cheical Egieerig Colbur Laboratory Uiversity

More information

Summary: CORRELATION & LINEAR REGRESSION. GC. Students are advised to refer to lecture notes for the GC operations to obtain scatter diagram.

Summary: CORRELATION & LINEAR REGRESSION. GC. Students are advised to refer to lecture notes for the GC operations to obtain scatter diagram. Key Cocepts: 1) Sketchig of scatter diagram The scatter diagram of bivariate (i.e. cotaiig two variables) data ca be easily obtaied usig GC. Studets are advised to refer to lecture otes for the GC operatios

More information

Automated Proofs for Some Stirling Number Identities

Automated Proofs for Some Stirling Number Identities Autoated Proofs for Soe Stirlig Nuber Idetities Mauel Kauers ad Carste Scheider Research Istitute for Sybolic Coputatio Johaes Kepler Uiversity Altebergerstraße 69 A4040 Liz, Austria Subitted: Sep 1, 2007;

More information

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter Time Respose & Frequecy Respose d -Order Dyamic System -Pole, Low-Pass, Active Filter R 4 R 7 C 5 e i R 1 C R 3 - + R 6 - + e out Assigmet: Perform a Complete Dyamic System Ivestigatio of the Two-Pole,

More information

Application of Homotopy Analysis Method for Solving various types of Problems of Ordinary Differential Equations

Application of Homotopy Analysis Method for Solving various types of Problems of Ordinary Differential Equations Iteratioal Joural o Recet ad Iovatio Treds i Coputig ad Couicatio IN: 31-8169 Volue: 5 Issue: 5 16 Applicatio of Hootopy Aalysis Meod for olvig various types of Probles of Ordiary Differetial Equatios

More information

1 (12 points) Red-Black trees and Red-Purple trees

1 (12 points) Red-Black trees and Red-Purple trees CS6 Hoework 3 Due: 29 April 206, 2 oo Subit o Gradescope Haded out: 22 April 206 Istructios: Please aswer the followig questios to the best of your ability. If you are asked to desig a algorith, please

More information

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions Nae Period ALGEBRA II Chapter B ad A Notes Solvig Iequalities ad Absolute Value / Nubers ad Fuctios SECTION.6 Itroductio to Solvig Equatios Objectives: Write ad solve a liear equatio i oe variable. Solve

More information

Sequences I. Chapter Introduction

Sequences I. Chapter Introduction Chapter 2 Sequeces I 2. Itroductio A sequece is a list of umbers i a defiite order so that we kow which umber is i the first place, which umber is i the secod place ad, for ay atural umber, we kow which

More information

Adv. Studies Theor. Phys., Vol. 5, 2011, no. 4, A Numerical Computation of Non-Dimensional. Form of a Mathematical Model of Soil Salinity

Adv. Studies Theor. Phys., Vol. 5, 2011, no. 4, A Numerical Computation of Non-Dimensional. Form of a Mathematical Model of Soil Salinity Adv. Studies Theor. Phs. Vol. 5 11 o. 4 185-191 A Nuerical Coputatio of No-Diesioal For of a Matheatical Model of Soil Saliit Profile i a Rice Field ear Marie Shrip Aquaculture Far Nattawoot Pogoo 1 ad

More information

Topic 9: Sampling Distributions of Estimators

Topic 9: Sampling Distributions of Estimators Topic 9: Samplig Distributios of Estimators Course 003, 2016 Page 0 Samplig distributios of estimators Sice our estimators are statistics (particular fuctios of radom variables), their distributio ca be

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

PH 411/511 ECE B(k) Sin k (x) dk (1)

PH 411/511 ECE B(k) Sin k (x) dk (1) Fall-27 PH 4/5 ECE 598 A. La Rosa Homework-3 Due -7-27 The Homework is iteded to gai a uderstadig o the Heiseberg priciple, based o a compariso betwee the width of a pulse ad the width of its spectral

More information

and then substitute this into the second equation to get 5(11 4 y) 3y

and then substitute this into the second equation to get 5(11 4 y) 3y Math E-b Lecture # Notes The priary focus of this week s lecture is a systeatic way of solvig ad uderstadig systes of liear equatios algebraically, geoetrically, ad logically. Eaple #: Solve the syste

More information

42 Dependence and Bases

42 Dependence and Bases 42 Depedece ad Bases The spa s(a) of a subset A i vector space V is a subspace of V. This spa ay be the whole vector space V (we say the A spas V). I this paragraph we study subsets A of V which spa V

More information

Contents Two Sample t Tests Two Sample t Tests

Contents Two Sample t Tests Two Sample t Tests Cotets 3.5.3 Two Saple t Tests................................... 3.5.3 Two Saple t Tests Setup: Two Saples We ow focus o a sceario where we have two idepedet saples fro possibly differet populatios. Our

More information

Math 113 Exam 3 Practice

Math 113 Exam 3 Practice Math Exam Practice Exam will cover.-.9. This sheet has three sectios. The first sectio will remid you about techiques ad formulas that you should kow. The secod gives a umber of practice questios for you

More information

CS 70 Second Midterm 7 April NAME (1 pt): SID (1 pt): TA (1 pt): Name of Neighbor to your left (1 pt): Name of Neighbor to your right (1 pt):

CS 70 Second Midterm 7 April NAME (1 pt): SID (1 pt): TA (1 pt): Name of Neighbor to your left (1 pt): Name of Neighbor to your right (1 pt): CS 70 Secod Midter 7 April 2011 NAME (1 pt): SID (1 pt): TA (1 pt): Nae of Neighbor to your left (1 pt): Nae of Neighbor to your right (1 pt): Istructios: This is a closed book, closed calculator, closed

More information

Chapter 2 Feedback Control Theory Continued

Chapter 2 Feedback Control Theory Continued Chapter Feedback Cotrol Theor Cotiued. Itroductio I the previous chapter, the respose characteristic of simple first ad secod order trasfer fuctios were studied. It was show that first order trasfer fuctio,

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

Al Lehnen Madison Area Technical College 10/5/2014

Al Lehnen Madison Area Technical College 10/5/2014 The Correlatio of Two Rado Variables Page Preliiary: The Cauchy-Schwarz-Buyakovsky Iequality For ay two sequeces of real ubers { a } ad = { b } =, the followig iequality is always true. Furtherore, equality

More information

MA131 - Analysis 1. Workbook 2 Sequences I

MA131 - Analysis 1. Workbook 2 Sequences I MA3 - Aalysis Workbook 2 Sequeces I Autum 203 Cotets 2 Sequeces I 2. Itroductio.............................. 2.2 Icreasig ad Decreasig Sequeces................ 2 2.3 Bouded Sequeces..........................

More information

Lab(8) controller design using root locus

Lab(8) controller design using root locus Lab(8) cotroller desig usig root locus I this lab we will lear how to desig a cotroller usig root locus but before this we eed to aswer the followig questios: What is root locus? What is the purpose of

More information

Verification of continuous predictands

Verification of continuous predictands barbara.casati@ec.gc.ca Verificatio of cotiuous predictads Barbara Casati 9 Ja 007 Exploratory ethods: joit distributio Scatter-plot: plot of observatio versus forecast values Perfect forecast obs, poits

More information

APPLICATION OF UNCERTAIN NONLINEAR SYSTEMS PARTIAL STATE VARIABLES CONTROL TO A CLASS OF PENDULUM SYSTEMS

APPLICATION OF UNCERTAIN NONLINEAR SYSTEMS PARTIAL STATE VARIABLES CONTROL TO A CLASS OF PENDULUM SYSTEMS 3 st Deceber 0 Vol 46 No 005-0 JATIT & LLS All rights reserved ISSN: 99-8645 wwwjatitorg E-ISSN: 87-395 APPLICATION OF UNCERTAIN NONLINEAR SYSTEMS PARTIAL STATE VARIABLES CONTROL TO A CLASS OF PENDULUM

More information

A.1 Algebra Review: Polynomials/Rationals. Definitions:

A.1 Algebra Review: Polynomials/Rationals. Definitions: MATH 040 Notes: Uit 0 Page 1 A.1 Algera Review: Polyomials/Ratioals Defiitios: A polyomial is a sum of polyomial terms. Polyomial terms are epressios formed y products of costats ad variales with whole

More information

Transfer Function Analysis

Transfer Function Analysis Trasfer Fuctio Aalysis Free & Forced Resposes Trasfer Fuctio Syste Stability ME375 Trasfer Fuctios - Free & Forced Resposes Ex: Let s s look at a stable first order syste: τ y + y = Ku Take LT of the I/O

More information

3. Newton s Rings. Background. Aim of the experiment. Apparatus required. Theory. Date : Newton s Rings

3. Newton s Rings. Background. Aim of the experiment. Apparatus required. Theory. Date : Newton s Rings ate : Newto s igs 3. Newto s igs Backgroud Coheret light Phase relatioship Path differece Iterferece i thi fil Newto s rig apparatus Ai of the experiet To study the foratio of Newto s rigs i the air-fil

More information

Surveying the Variance Reduction Methods

Surveying the Variance Reduction Methods Available olie at www.scizer.co Austria Joural of Matheatics ad Statistics, Vol 1, Issue 1, (2017): 10-15 ISSN 0000-0000 Surveyig the Variace Reductio Methods Arash Mirtorabi *1, Gholahossei Gholai 2 1.

More information

The driven Rayleigh-van der Pol oscillator

The driven Rayleigh-van der Pol oscillator ENOC 7, Jue 5-, 7, Budapest, Hugary The drive Rayleigh-va der Pol oscillator Reé Bartkowiak Faculty of Mechaical Egieerig ad Marie Techology, Uiversity of Rostock, Geray Suary. Sychroizatio of oscillatory

More information

DETERMINATION OF NATURAL FREQUENCY AND DAMPING RATIO

DETERMINATION OF NATURAL FREQUENCY AND DAMPING RATIO Hasa G Pasha DETERMINATION OF NATURAL FREQUENCY AND DAMPING RATIO OBJECTIVE Deterie the atural frequecy ad dapig ratio for a aluiu catilever bea, Calculate the aalytical value of the atural frequecy ad

More information

EXPERIMENT OF SIMPLE VIBRATION

EXPERIMENT OF SIMPLE VIBRATION EXPERIMENT OF SIMPLE VIBRATION. PURPOSE The purpose of the experimet is to show free vibratio ad damped vibratio o a system havig oe degree of freedom ad to ivestigate the relatioship betwee the basic

More information

Lecture 10: Bounded Linear Operators and Orthogonality in Hilbert Spaces

Lecture 10: Bounded Linear Operators and Orthogonality in Hilbert Spaces Lecture : Bouded Liear Operators ad Orthogoality i Hilbert Spaces 34 Bouded Liear Operator Let ( X, ), ( Y, ) i i be ored liear vector spaces ad { } X Y The, T is said to be bouded if a real uber c such

More information

DISTANCE BETWEEN UNCERTAIN RANDOM VARIABLES

DISTANCE BETWEEN UNCERTAIN RANDOM VARIABLES MATHEMATICAL MODELLING OF ENGINEERING PROBLEMS Vol, No, 4, pp5- http://doiorg/88/ep4 DISTANCE BETWEEN UNCERTAIN RANDOM VARIABLES Yogchao Hou* ad Weicai Peg Departet of Matheatical Scieces, Chaohu Uiversity,

More information

Numerical Methods in Fourier Series Applications

Numerical Methods in Fourier Series Applications Numerical Methods i Fourier Series Applicatios Recall that the basic relatios i usig the Trigoometric Fourier Series represetatio were give by f ( x) a o ( a x cos b x si ) () where the Fourier coefficiets

More information

New Simple Methods of Tuning Three-Term Controllers for Dead-Time Processes

New Simple Methods of Tuning Three-Term Controllers for Dead-Time Processes New Siple Methods of Tuig Three-Ter Cotrollers for Dead-Tie Processes.G.ARVANTS Departet of Natural Resources Maageet ad Agricultural Egieerig Agricultural Uiversity of Athes era Odos 75, Botaikos 8 55,

More information

School of Mechanical Engineering Purdue University. ME375 Transfer Functions - 1

School of Mechanical Engineering Purdue University. ME375 Transfer Functions - 1 Trasfer Fuctio Aalysis Free & Forced Resposes Trasfer Fuctio Syste Stability ME375 Trasfer Fuctios - 1 Free & Forced Resposes Ex: Let s look at a stable first order syste: y y Ku Take LT of the I/O odel

More information

CALCULATION OF FIBONACCI VECTORS

CALCULATION OF FIBONACCI VECTORS CALCULATION OF FIBONACCI VECTORS Stuart D. Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA email: saderso@ithaca.edu ad Dai Novak Departmet of Mathematics, Ithaca College

More information

Answer Key, Problem Set 1, Written

Answer Key, Problem Set 1, Written Cheistry 1 Mies, Sprig, 018 Aswer Key, Proble Set 1, Writte 1. 14.3;. 14.34 (add part (e): Estiate / calculate the iitial rate of the reactio); 3. NT1; 4. NT; 5. 14.37; 6. 14.39; 7. 14.41; 8. NT3; 9. 14.46;

More information

Lebesgue Constant Minimizing Bivariate Barycentric Rational Interpolation

Lebesgue Constant Minimizing Bivariate Barycentric Rational Interpolation Appl. Math. If. Sci. 8, No. 1, 187-192 (2014) 187 Applied Matheatics & Iforatio Scieces A Iteratioal Joural http://dx.doi.org/10.12785/ais/080123 Lebesgue Costat Miiizig Bivariate Barycetric Ratioal Iterpolatio

More information

ENGI 4421 Probability and Statistics Faculty of Engineering and Applied Science Problem Set 1 Solutions Descriptive Statistics. None at all!

ENGI 4421 Probability and Statistics Faculty of Engineering and Applied Science Problem Set 1 Solutions Descriptive Statistics. None at all! ENGI 44 Probability ad Statistics Faculty of Egieerig ad Applied Sciece Problem Set Solutios Descriptive Statistics. If, i the set of values {,, 3, 4, 5, 6, 7 } a error causes the value 5 to be replaced

More information

Mixture models (cont d)

Mixture models (cont d) 6.867 Machie learig, lecture 5 (Jaakkola) Lecture topics: Differet types of ixture odels (cot d) Estiatig ixtures: the EM algorith Mixture odels (cot d) Basic ixture odel Mixture odels try to capture ad

More information

A NOTE TO SHOW HOW AN ALTERNATIVE SPHERICAL MODE NORMALIZATION SIMPLIFIES THE RELATIONSHIP BETWEEN TRANSMITTING AND RECEIVING CHARACTERISTICS

A NOTE TO SHOW HOW AN ALTERNATIVE SPHERICAL MODE NORMALIZATION SIMPLIFIES THE RELATIONSHIP BETWEEN TRANSMITTING AND RECEIVING CHARACTERISTICS A NOTE TO SHOW HOW AN ALTERNATIVE SPHERICAL MODE NORMALIZATION SIMPLIFIES THE RELATIONSHIP BETWEEN TRANSMITTING AND RECEIVING CHARACTERISTICS Dore W. Hess MI Techologies 1125 Satellite Blvd., Suite 100

More information

GROUPOID CARDINALITY AND EGYPTIAN FRACTIONS

GROUPOID CARDINALITY AND EGYPTIAN FRACTIONS GROUPOID CARDINALITY AND EGYPTIAN FRACTIONS JULIA E. BERGNER AND CHRISTOPHER D. WALKER Abstract. I this paper we show that two very ew questios about the cardiality of groupoids reduce to very old questios

More information

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering CEE 5 Autum 005 Ucertaity Cocepts for Geotechical Egieerig Basic Termiology Set A set is a collectio of (mutually exclusive) objects or evets. The sample space is the (collectively exhaustive) collectio

More information

A Tabu Search Method for Finding Minimal Multi-Homogeneous Bézout Number

A Tabu Search Method for Finding Minimal Multi-Homogeneous Bézout Number Joural of Matheatics ad Statistics 6 (): 105-109, 010 ISSN 1549-3644 010 Sciece Publicatios A Tabu Search Method for Fidig Miial Multi-Hoogeeous Bézout Nuber Hassa M.S. Bawazir ad Ali Abd Raha Departet

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

3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials

3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials Math 60 www.timetodare.com 3. Properties of Divisio 3.3 Zeros of Polyomials 3.4 Complex ad Ratioal Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered

More information

A Method to Calculate the True Stress and True Strain for Tensile Test of Plastic

A Method to Calculate the True Stress and True Strain for Tensile Test of Plastic Ke Egieerig Materials Vols. 74-76 (4) pp. 77-8 olie at http://www.scietific.et 4 Tras Tech Publicatios, Switzerlad Method to Calculate the True Stress ad True Strai for Tesile Test of Plastic X. W. Du,

More information

2. F ; =(,1)F,1; +F,1;,1 is satised by thestirlig ubers of the rst kid ([1], p. 824). 3. F ; = F,1; + F,1;,1 is satised by the Stirlig ubers of the se

2. F ; =(,1)F,1; +F,1;,1 is satised by thestirlig ubers of the rst kid ([1], p. 824). 3. F ; = F,1; + F,1;,1 is satised by the Stirlig ubers of the se O First-Order Two-Diesioal Liear Hoogeeous Partial Dierece Equatios G. Neil Have y Ditri A. Gusev z Abstract Aalysis of algoriths occasioally requires solvig of rst-order two-diesioal liear hoogeeous partial

More information

Response Variable denoted by y it is the variable that is to be predicted measure of the outcome of an experiment also called the dependent variable

Response Variable denoted by y it is the variable that is to be predicted measure of the outcome of an experiment also called the dependent variable Statistics Chapter 4 Correlatio ad Regressio If we have two (or more) variables we are usually iterested i the relatioship betwee the variables. Associatio betwee Variables Two variables are associated

More information

Stream Ciphers (contd.) Debdeep Mukhopadhyay

Stream Ciphers (contd.) Debdeep Mukhopadhyay Strea Ciphers (cotd.) Debdeep Mukhopadhyay Assistat Professor Departet of Coputer Sciece ad Egieerig Idia Istitute of Techology Kharagpur IDIA -7232 Objectives iear Coplexity Berlekap Massey Algorith ow

More information

Principle Of Superposition

Principle Of Superposition ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give

More information

COMP 2804 Solutions Assignment 1

COMP 2804 Solutions Assignment 1 COMP 2804 Solutios Assiget 1 Questio 1: O the first page of your assiget, write your ae ad studet uber Solutio: Nae: Jaes Bod Studet uber: 007 Questio 2: I Tic-Tac-Toe, we are give a 3 3 grid, cosistig

More information

( ) = p and P( i = b) = q.

( ) = p and P( i = b) = q. MATH 540 Radom Walks Part 1 A radom walk X is special stochastic process that measures the height (or value) of a particle that radomly moves upward or dowward certai fixed amouts o each uit icremet of

More information