Multicriteria Choice of the NVG Optoelectronic Channel Elements

Size: px
Start display at page:

Download "Multicriteria Choice of the NVG Optoelectronic Channel Elements"

Transcription

1 БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ BULGARIAN ACADEMY O SCIENCES ПРОБЛЕМИ НА ТЕХНИЧЕСКАТА КИБЕРНЕТИКА И РОБОТИКАТА 56 PROBLEMS O ENGINEERING CYBERNETICS AND ROBOTICS 56 София 2006 Sofia Multicriteria Choice of the NVG Optoelectroic Chael Elemets Daiela Borissova Istitute of Iformatio Techologies 1113 Sofia dabor@iit.bas.bg 1. Itroductio The ight visio goggles (NVG) are gettig cheaper ad are spreadig widely i differet applicatio areas recetly. That is a cosequece of techological developmet ad mass productio. The process of the NVG desig ivolves choice of optoelectroic chael elemets (jectives image itesifier tubes IIT oculars) amog their subsets. The chose elemets must fulfill specific requiremets of the NVG optoelectroic chael ad it has to meet user's expectatios. As a result a eed for the developmet of some relevat optimizatio models exists. A sigle-criteria optimizatio model has bee developed ad tested showig good practical workability [1]. The defied jective fuctio icludes the most commo practically demaded compoets such as price weight workig rage field of view etc. To be more precise i real live modelig it should be metioed that some of the criterio compoets are icompatible ad coflictig. Usig optimizatio for more adequate describig real egieerig prlems it is atural to look for multi-criteria optimizatio prlems defiitio [2 3]. Cosiderig each criterio compoet of the formulated sigle-criterio prlem [1] as uique criterio the sigle-criterio prlem ca be trasformed to a multicriteria prlem as described i the curret paper. 2. ormulatio of quality criteria of NVG The parameters of the NVG optoelectroic chael are crucial for the quality of NVG itself. The practical expertise shows that the most importat of them are [1]: Q 1 = R the workig rage Q 2 = W the field of view Q 3 = (1/ ) the jective -umber 6 1

2 Q 4 = the jective focus rage Q 5 = AD ab jective (distortio) Q 6 = ER the eye relief Q 7 = L the weight of NVG optoelectroic chael Q 8 = P the price of NVG optoelectroic chael A multi-criteria optimizatio model of the NVG optoelectroic chael could be formulated as follows: (1) max {Q 1 Q 2 Q 3 Q 4 Q 5 Q 6 Q 7 Q 8 } subject to costraits describig the specifics of the NVG optoelectroic chael [1]: (2) y j j (3) 6 2 k 1 l z l y jw j zk k 1 k oc k oc k equality of the jective ad ocular focal legth for NVG magificatio 1? W jective field of view ocular field of view d d (4) R 0.07 a EKА ' KIITK detectio rage for a stadig ma [4] (5) (6) IIT m K x ik i 1 K y j K IIT i j IIT quality parameter jective quality parameter (7) AD y j AD j jective distortio (8) 1 y j 1 (9) y j j W l ER z k k 1 l j (10) y j W j (11) ER (12) Woc y k W k k 1 k oc jective -umber jective focus rage jective field of view eye relief ocular field of view (13) L LIIT L Lоc optoelectroic tract weight (14) P PIIT P Pоc optoelectroic tract price where x y z {0 1} are biary iteger variables for choice of the relevat elemets of the NVG optoelectroic chael [1]. The ambiet light coditio ad the target area are costats with kow umerical values:

3 a = 0.7 atmosphere trasmittace E = 0.01 lx ambiet light illumiatio K = 0.2 cotrast betwee the surveillace target ad backgroud A = 0.7 m 2 target area for a stadig ma [4] The multicriteria prlem solutio depeds o the optimizatio strategy [3]. The defied i the curret paper determiistic multicriteria oliear optimizatio model has bee solved usig two approaches by e-costraits approach ad by weighted sum approach [5 6 7]. 3. Results of usig e-costraits approach As source data for prlem formulatig the parameters of five jectives five IITs of differet geeratios ad five oculars show i tables 1 2 ad 3 were used. Table 1. IITs parameters S No IIT A/lm lp/mm M L IIT P IIT g $ 1 Ge II SHD XD XR MX-10160B Table 2. Objectives parameters No Objective W AD L P mm o deg % сm g $ 1 NVG Prilep AN/PVS-5C AN/PVS-5A NVG D-2V Table 3. Oculars parameters No Ocular oc W oc ER L оc P оc mm deg mm g $ 1 NVG Prilep NVG M M M The e-costraits approach requires oe jective to be selected for optimizatio ad the other jectives to be reformulated as costraits creatig i this way scalar subprlems to be solved as sigle-criterio prlems [5 6 7]. 6 3

4 Scalar subprlem D(R) for detectio rage: (15) max R d subject to (2)-(14) with values from Tables ad the additioal costraits for the rest of criteria from (1): (16) 35 W (17) 1 (1/ ) (18) 30 (19) AD 9 (20) 20 ER (21) L 300 (22) P The decisio of the D(R) will be a costrait for R d for all other scalar subprlems. Scalar subprlem D(W ) for jective field of view: (23) max W subject to (2)-(14) with values from Tables costraits (17)-(22) for the rest of criteria from (1) ad the additioal costrait: (24) 400 R d The D(W ) decisio will be a costrait for W for other scalar subprlems. Scalar subprlem D(1/k) for jective -umber: (25) max 1/ subject to (2)-(14) with values from Tables costraits (18)-(22) (24) for the rest of criteria from (1) ad the additioal costrait: (26) 40 W The D(1/ ) decisio will be a costrait for 1/ for other scalar subprlems. Scalar subprlem D() for jective focus rage: (27) mi subject to (2)-(14) with values from Tables costraits (19)-(22) (24) (26) for the rest of criteria from (1) ad the additioal costrait: (28) 1 (1/ ) The D() decisio will be a costrait for for other scalar subprlems. Scalar subprlem D(AD ) for jective distortio: (29) mi AD subject to (2)-(14) with values from Tables costraits (20)-(22) (24) (26) (28) for the rest of criteria from (1) ad the additioal costrait: (30) 30. The D(AD ) decisio will be a costrait for AD for other scalar subprlems. 6 4

5 Scalar subprlem D(ER) for eye relief: (31) max ER subject to (2)-(14) with values from Tables costraits (21) (22) (24) (26) (28) (30) for the rest of criteria from (1) ad the additioal costrait: (32) AD 7. The D(ER) decisio will be a costrait for ER for other scalar subprlems. Scalar subprlem D(L) for NVG optoelectroic chael weight: (33) mi L subject to (2)-(14) with values from Tables costraits (22) (24) (26) (28) (30) (32) for the rest of criteria from (1) ad the additioal costrait: (34) 10 ER. The D(L) decisio will be a costrait for L for other scalar subprlems. Scalar subprlem D(P) for NVG optoelectroic chael price: (35) mi P subject to (2)-(14) with values from Tables costraits (24) (26) (28) (30) (32) (34) for the rest of criteria from (1) ad the additioal costrait: (36) L 250. The results from the decisios of the scalar subprlems D(R) D(W ) D(1/ ) D() D(AD ) D(ER) D(L) D(P) are show i Table 4. Table 4. The results from scalar subprlems ad sigle-criterio optimizatio prlem D1 decisios Tasks D1 D(R) D(W ) D(1/ ) D() D(AD ) D(ER) D(L) D(P) Criteria all 1st 2d 3th 4th 5th 6th 7th 8th Chose IIT (from Table 1) Chose jective (from Table 2) Chose ocular (from Table 3) Detectig rage m ield of view deg umber Objective focus rage сm Distortio % Eye relief mm Weight g Price $ A sigle-criterio optimizatio oliear prlem defied as D1 [1]: (37) max Q = (R + W + (1/ ) AD + ER L P) subject to (2)-(14) with values from Tables ad the same boudaries (16)-(22) (24) as i a multicriteria prlem is solved ad the results of its decisio are show 5 Prlems of Egieerig Cyberetics ad Rotics

6 also i Table 4. The results for optoelectroic chael parameters from the decisios of D1 ad the last scalar subprlem D(P) are equal. The graphical presetatio of the taied detectio rage values ad the optoelectroic chael price by the decisios of the scalar subprlems D(R) D(W ) D(1/ ) D() D(AD ) D(ER) D(L) D(P) ad by decisio of the sigle-criterio prlem D1 are show i ig. 1 ad ig. 2 respectively. 700 PrlemD1 Detectig rage m Criteria ig. 1. Detectio rage values from the scalar subprlems ( ad D1 ( ) decisios 7000 Prlem D Price $ Criteria ig. 2. Price values from the scalar subprlems ( ) ad D1 ( ) decisios 4. Results of usig weighted sum approach Oe of the widely used for the multicriteria prlems solvig is the weighted sum approach. The prefereces of the decisio-maker are take ito accout by choosig differet weights for the differet jectives [5 6 7]. Usually the jective fuctios are of differet magitudes ad should be ormalized first. The ormalizatio is doe solvig maximizatio ad miimizatio siglecriterio prlems for each of the criteria discardig the rest of the criteria. The taied maximum ad miimum values for each criterio of the formulated i the curret paper multicriteria prlem are show i Table

7 Table 5. The maximum ad miimum values for each criterio R W Criterio 1/ AD ER L P m deg cm % cm g $ Max / Mi / The values from the Table 5 are used to defie a ormalized sigle-jective fuctio: R Rmi (38) max{k 1 Rmax Rmi W W + k 2 max W W mi mi (1/ ) (1/ ) mi + k 3 (1/ ) max (1/ ) mi + max max AD AD ER ER mi + k 4 + k max 5 max mi + k 6 mi AD AD ERmax ERmi Pmax P + k 8 }. Pmax Pmi L L max +k 7 Lmax Lmi The weighted sum approach trasforms multiple criteria to a sigle-criterio defied as a sum of ormalized criteria with proper weight coefficiets k i where k 1. our sets of the weight coefficiets k i have bee chose for usig i i weighted sum approach as show i Table 6. Table 6. The sets of the weight coefficiets Set k 1 k 2 k 3 k 4 k 5 k 6 k 7 k 8 (1) (2) (3) (4) The decisios of the correspodig trasformed sigle-criterio prlems for each set of weighted coefficiets are show i table 7. Table 7. The results of the multicriteria prlem usig four sets of weighted coefficiets Parameter D(1) D(2) D(3) D(4) Chose IIT from Table Chose jective from Table Chose ocular from Table Detectig rage m ield of view deg umber ocus rage cm Distortio % Eye relief mm Weight g Price $

8 5. Coclusio Modelig of the NVG optoelectroic chael for the goal of the optimal choice of its elemets could be doe usig sigle-criterio ad multicriteria optimizatio models. Multicriteria models are closer to the practical requiremets for NVG but are more difficult to solve. The result taied by usig the e-costraits approach suggests that a equivalet sigle-criterio trasformed prlem where a sum of the multiple criteria forms a sigle criterio could be used for solvig the origial multicriteria prlem i this particular specific case. Usig the weighted sum approach demads good kowledge about the specifics of the prlems ad multiple tries for adjustig of the weighted coefficiets to get acceptable results. R e f e r e c e s 1. B o r i s s o v a D. I. M o u s t a k e r o v. A Optimal Choice Method of the Elemets for NVG s Optoelectroics Tract. IIT/WP-214B B a l a z s M. E. G. T. P a r k s P. J. C l a r k s o. Optimizatio i Idustry What Does Idustry Really Need?. Optimizatio i Idustry 2002 No A d e r s s o J. Multijective Optimizatio i Egieerig Desig. Likopig Studies i Sciece ad Techology. Dissertatios. No p B o r i s s o v a D. Aalytical Calculatio of Night Visio Goggles Workig Rage. Cyberetics ad Iformatio Techologies Vol No K l a m r o t h K. J. T i d S. Z u s t. Iteger Programmig Duality i Multiple Objective Programmig. Joural of Glal Optimizatio A d e r s s o J. A Survey of Multijective Optimizatio i Egieerig Desig. Techical Report LiTH-IKP-R Departmet of Mechaical Egieerig Likopig Uiversity Likopig Swede 2000 p V a s s i l e v a M. Classificatio-Orieted Iteractive Methods Algorithms ad a System for Solvig of Liear ad Iteger Prlems of the Multi-Criteria Optimizatio. Post-Doctoral Thesis. Istitute of Iformatio Techologies Bulgaria Academy of Scieces Многокритериальный выбор элементов для оптико-электронного канала очков ночного видения Даниела Борисова Институт информационных технологий 1113 София dabor@iit.bas.bg (Р е з ю м е) Описана многокритериальная оптимизационная модель для выбора элементов оптико-электронного канала очков ночного видения. Показаны решения соответствующих многокритериальных задач через методов е-ограничения и тегловых сум и сделаны выводы для практического применения. 6 8

Markov Decision Processes

Markov Decision Processes Markov Decisio Processes Defiitios; Statioary policies; Value improvemet algorithm, Policy improvemet algorithm, ad liear programmig for discouted cost ad average cost criteria. Markov Decisio Processes

More information

IP Reference guide for integer programming formulations.

IP Reference guide for integer programming formulations. IP Referece guide for iteger programmig formulatios. by James B. Orli for 15.053 ad 15.058 This documet is iteded as a compact (or relatively compact) guide to the formulatio of iteger programs. For more

More information

OPTIMIZED SOLUTION OF PRESSURE VESSEL DESIGN USING GEOMETRIC PROGRAMMING

OPTIMIZED SOLUTION OF PRESSURE VESSEL DESIGN USING GEOMETRIC PROGRAMMING OPTIMIZED SOLUTION OF PRESSURE VESSEL DESIGN USING GEOMETRIC PROGRAMMING S.H. NASSERI, Z. ALIZADEH AND F. TALESHIAN ABSTRACT. Geometric programmig is a methodology for solvig algebraic oliear optimizatio

More information

Numerical Conformal Mapping via a Fredholm Integral Equation using Fourier Method ABSTRACT INTRODUCTION

Numerical Conformal Mapping via a Fredholm Integral Equation using Fourier Method ABSTRACT INTRODUCTION alaysia Joural of athematical Scieces 3(1): 83-93 (9) umerical Coformal appig via a Fredholm Itegral Equatio usig Fourier ethod 1 Ali Hassa ohamed urid ad Teh Yua Yig 1, Departmet of athematics, Faculty

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

Support vector machine revisited

Support vector machine revisited 6.867 Machie learig, lecture 8 (Jaakkola) 1 Lecture topics: Support vector machie ad kerels Kerel optimizatio, selectio Support vector machie revisited Our task here is to first tur the support vector

More information

Optimization Methods: Linear Programming Applications Assignment Problem 1. Module 4 Lecture Notes 3. Assignment Problem

Optimization Methods: Linear Programming Applications Assignment Problem 1. Module 4 Lecture Notes 3. Assignment Problem Optimizatio Methods: Liear Programmig Applicatios Assigmet Problem Itroductio Module 4 Lecture Notes 3 Assigmet Problem I the previous lecture, we discussed about oe of the bech mark problems called trasportatio

More information

1.225J J (ESD 205) Transportation Flow Systems

1.225J J (ESD 205) Transportation Flow Systems .5J J (ESD 5 Trasportatio Flow Systems Lecture 6 Itroductio to Optimizatio Pro. Ismail Chabii ad Pro. Amedeo R. Odoi Lecture 6 Outlie Mathematical programs (MPs Formulatio o shortest path problems as MPs

More information

Scalarizing Problems of Multiobjective Linear Integer Programming

Scalarizing Problems of Multiobjective Linear Integer Programming БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ BULGARIAN ACADEMY OF SCIENCES ПРОБЛЕМИ НА ТЕХНИЧЕСКАТА КИБЕРНЕТИКА И РОБОТИКАТА 50 PROBLEMS OF ENGINEERING CYBERNETICS AND ROBOTICS 50 София 2000 Sofia Scalarizing Problems

More information

Scheduling under Uncertainty using MILP Sensitivity Analysis

Scheduling under Uncertainty using MILP Sensitivity Analysis Schedulig uder Ucertaity usig MILP Sesitivity Aalysis M. Ierapetritou ad Zheya Jia Departmet of Chemical & Biochemical Egieerig Rutgers, the State Uiversity of New Jersey Piscataway, NJ Abstract The aim

More information

Definitions and Theorems. where x are the decision variables. c, b, and a are constant coefficients.

Definitions and Theorems. where x are the decision variables. c, b, and a are constant coefficients. Defiitios ad Theorems Remember the scalar form of the liear programmig problem, Miimize, Subject to, f(x) = c i x i a 1i x i = b 1 a mi x i = b m x i 0 i = 1,2,, where x are the decisio variables. c, b,

More information

Solution of Differential Equation from the Transform Technique

Solution of Differential Equation from the Transform Technique Iteratioal Joural of Computatioal Sciece ad Mathematics ISSN 0974-3189 Volume 3, Number 1 (2011), pp 121-125 Iteratioal Research Publicatio House http://wwwirphousecom Solutio of Differetial Equatio from

More information

subject to A 1 x + A 2 y b x j 0, j = 1,,n 1 y j = 0 or 1, j = 1,,n 2

subject to A 1 x + A 2 y b x j 0, j = 1,,n 1 y j = 0 or 1, j = 1,,n 2 Additioal Brach ad Boud Algorithms 0-1 Mixed-Iteger Liear Programmig The brach ad boud algorithm described i the previous sectios ca be used to solve virtually all optimizatio problems cotaiig iteger variables,

More information

The multi capacitated clustering problem

The multi capacitated clustering problem The multi capacitated clusterig problem Bruo de Aayde Prata 1 Federal Uiversity of Ceará, Brazil Abstract Clusterig problems are combiatorial optimizatio problems wi several idustrial applicatios. The

More information

SELECTION OF DRILL FOR DRILLING WITH HIGH PRESSURE COOLANT USING ENTROPY AND COPRAS MCDM METHOD

SELECTION OF DRILL FOR DRILLING WITH HIGH PRESSURE COOLANT USING ENTROPY AND COPRAS MCDM METHOD U.P.B. Sci. Bull., Series D, Vol. 79, Iss. 4, 2017 ISSN 1454-2358 SELECTION OF DRILL FOR DRILLING WITH HIGH PRESSURE COOLANT USING ENTROPY AND COPRAS MCDM METHOD Jelea STANOJKOVIĆ 1, Miroslav RADOVANOVIĆ

More information

ROLL CUTTING PROBLEMS UNDER STOCHASTIC DEMAND

ROLL CUTTING PROBLEMS UNDER STOCHASTIC DEMAND Pacific-Asia Joural of Mathematics, Volume 5, No., Jauary-Jue 20 ROLL CUTTING PROBLEMS UNDER STOCHASTIC DEMAND SHAKEEL JAVAID, Z. H. BAKHSHI & M. M. KHALID ABSTRACT: I this paper, the roll cuttig problem

More information

DECOMPOSITION METHOD FOR SOLVING A SYSTEM OF THIRD-ORDER BOUNDARY VALUE PROBLEMS. Park Road, Islamabad, Pakistan

DECOMPOSITION METHOD FOR SOLVING A SYSTEM OF THIRD-ORDER BOUNDARY VALUE PROBLEMS. Park Road, Islamabad, Pakistan Mathematical ad Computatioal Applicatios, Vol. 9, No. 3, pp. 30-40, 04 DECOMPOSITION METHOD FOR SOLVING A SYSTEM OF THIRD-ORDER BOUNDARY VALUE PROBLEMS Muhammad Aslam Noor, Khalida Iayat Noor ad Asif Waheed

More information

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series

More information

Linear Programming and the Simplex Method

Linear Programming and the Simplex Method Liear Programmig ad the Simplex ethod Abstract This article is a itroductio to Liear Programmig ad usig Simplex method for solvig LP problems i primal form. What is Liear Programmig? Liear Programmig is

More information

Determine the Optimal Solution for Linear Programming with Interval Coefficients

Determine the Optimal Solution for Linear Programming with Interval Coefficients IOP Coferece Series: Materials Sciece ad Egieerig PAPER OPEN ACCESS Determie the Optimal Solutio for Liear Programmig with Iterval Coefficiets To cite this article: E R Wula et al 2018 IOP Cof. Ser.: Mater.

More information

An Interactive Reference Direction Algorithm of the Convex Nonlinear Integer Multiobjective Programming

An Interactive Reference Direction Algorithm of the Convex Nonlinear Integer Multiobjective Programming БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ. BULGARIAN ACADEMY OF SCIENCES ПРОБЛЕМИ НА ТЕХНИЧЕСКАТА КИБЕРНЕТИКА И РОБОТИКАТА, 48 PROBLEMS OF ENGINEERING CYBERNETICS AND ROBOTICS, 48 София. 1999. Sofia An Interactive

More information

Numerical Solutions of Second Order Boundary Value Problems by Galerkin Residual Method on Using Legendre Polynomials

Numerical Solutions of Second Order Boundary Value Problems by Galerkin Residual Method on Using Legendre Polynomials IOSR Joural of Mathematics (IOSR-JM) e-issn: 78-578, p-issn: 319-765X. Volume 11, Issue 6 Ver. IV (Nov. - Dec. 15), PP 1-11 www.iosrjourals.org Numerical Solutios of Secod Order Boudary Value Problems

More information

ANALYSIS OF DAMPING EFFECT ON BEAM VIBRATION

ANALYSIS OF DAMPING EFFECT ON BEAM VIBRATION Molecular ad Quatum Acoustics vol. 7, (6) 79 ANALYSIS OF DAMPING EFFECT ON BEAM VIBRATION Jerzy FILIPIAK 1, Lech SOLARZ, Korad ZUBKO 1 Istitute of Electroic ad Cotrol Systems, Techical Uiversity of Czestochowa,

More information

The Growth of Functions. Theoretical Supplement

The Growth of Functions. Theoretical Supplement The Growth of Fuctios Theoretical Supplemet The Triagle Iequality The triagle iequality is a algebraic tool that is ofte useful i maipulatig absolute values of fuctios. The triagle iequality says that

More information

M.Jayalakshmi and P. Pandian Department of Mathematics, School of Advanced Sciences, VIT University, Vellore-14, India.

M.Jayalakshmi and P. Pandian Department of Mathematics, School of Advanced Sciences, VIT University, Vellore-14, India. M.Jayalakshmi, P. Padia / Iteratioal Joural of Egieerig Research ad Applicatios (IJERA) ISSN: 48-96 www.iera.com Vol., Issue 4, July-August 0, pp.47-54 A New Method for Fidig a Optimal Fuzzy Solutio For

More information

Research on real time compensation of thermal errors of CNC lathe based on linear regression theory Qiu Yongliang

Research on real time compensation of thermal errors of CNC lathe based on linear regression theory Qiu Yongliang d Iteratioal Coferece o Machiery, Materials Egieerig, Chemical Egieerig ad Biotechology (MMECEB 015) Research o real time compesatio of thermal errors of CNC lathe based o liear regressio theory Qiu Yogliag

More information

Product Mix Problem with Radom Return and Preference of Production Quantity. Osaka University Japan

Product Mix Problem with Radom Return and Preference of Production Quantity. Osaka University Japan Product Mix Problem with Radom Retur ad Preferece of Productio Quatity Hiroaki Ishii Osaka Uiversity Japa We call such fiace or idustrial assets allocatio problems portfolio selectio problems, ad various

More information

Chapter 9: Numerical Differentiation

Chapter 9: Numerical Differentiation 178 Chapter 9: Numerical Differetiatio Numerical Differetiatio Formulatio of equatios for physical problems ofte ivolve derivatives (rate-of-chage quatities, such as velocity ad acceleratio). Numerical

More information

An Interactive Reference Direction Algorithm of Nonlinear Integer Multiobjective Programming*

An Interactive Reference Direction Algorithm of Nonlinear Integer Multiobjective Programming* БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ. BULGARIAN ACADEMY OF SCIENCES ПРОБЛЕМИ НА ТЕХНИЧЕСКАТА КИБЕРНЕТИКА И РОБОТИКАТА, 47 PROBLEMS OF ENGINEERING CYBERNETICS AND ROBOTICS, 47 София. 1998. Sofia An Interactive

More information

Introduction of Expectation-Maximization Algorithm, Cross-Entropy Method and Genetic Algorithm

Introduction of Expectation-Maximization Algorithm, Cross-Entropy Method and Genetic Algorithm Itroductio of Expectatio-Maximizatio Algorithm, Cross-Etropy Method ad Geetic Algorithm Wireless Iformatio Trasmissio System Lab. Istitute of Commuicatios Egieerig Natioal Su Yat-se Uiversity 2012/07/23

More information

Lecture 2 Clustering Part II

Lecture 2 Clustering Part II COMS 4995: Usupervised Learig (Summer 8) May 24, 208 Lecture 2 Clusterig Part II Istructor: Nakul Verma Scribes: Jie Li, Yadi Rozov Today, we will be talkig about the hardess results for k-meas. More specifically,

More information

Machine Learning Theory Tübingen University, WS 2016/2017 Lecture 11

Machine Learning Theory Tübingen University, WS 2016/2017 Lecture 11 Machie Learig Theory Tübige Uiversity, WS 06/07 Lecture Tolstikhi Ilya Abstract We will itroduce the otio of reproducig kerels ad associated Reproducig Kerel Hilbert Spaces (RKHS). We will cosider couple

More information

Optimization Methods MIT 2.098/6.255/ Final exam

Optimization Methods MIT 2.098/6.255/ Final exam Optimizatio Methods MIT 2.098/6.255/15.093 Fial exam Date Give: December 19th, 2006 P1. [30 pts] Classify the followig statemets as true or false. All aswers must be well-justified, either through a short

More information

Research Article A New Second-Order Iteration Method for Solving Nonlinear Equations

Research Article A New Second-Order Iteration Method for Solving Nonlinear Equations Abstract ad Applied Aalysis Volume 2013, Article ID 487062, 4 pages http://dx.doi.org/10.1155/2013/487062 Research Article A New Secod-Order Iteratio Method for Solvig Noliear Equatios Shi Mi Kag, 1 Arif

More information

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables S S symmetry Article Possibility/Necessity-Based Probabilistic Expectatio Models for Liear Programmig Problems with Discrete Fuzzy Radom Variables Hideki Katagiri 1, *, Kosuke Kato 2 ad Takeshi Uo 3 1

More information

Sliding Mode Indicator Model s at Thermal Control System for Furnace

Sliding Mode Indicator Model s at Thermal Control System for Furnace Proceedigs of the 7th World Cogress The Iteratioal Federatio of Automatic Cotrol Slidig Mode Idicator Model s at Thermal Cotrol System for Furace Varda Mkrttchia*, Sargis Simoya**, Aa Khachaturova***,

More information

OPTIMAL PIECEWISE UNIFORM VECTOR QUANTIZATION OF THE MEMORYLESS LAPLACIAN SOURCE

OPTIMAL PIECEWISE UNIFORM VECTOR QUANTIZATION OF THE MEMORYLESS LAPLACIAN SOURCE Joural of ELECTRICAL EGIEERIG, VOL. 56, O. 7-8, 2005, 200 204 OPTIMAL PIECEWISE UIFORM VECTOR QUATIZATIO OF THE MEMORYLESS LAPLACIA SOURCE Zora H. Perić Veljo Lj. Staović Alesadra Z. Jovaović Srdja M.

More information

THE TRANSFORMATION MATRIX OF CHEBYSHEV IV BERNSTEIN POLYNOMIAL BASES

THE TRANSFORMATION MATRIX OF CHEBYSHEV IV BERNSTEIN POLYNOMIAL BASES Joural of Mathematical Aalysis ISSN: 17-341, URL: http://iliriascom/ma Volume 7 Issue 4(16, Pages 13-19 THE TRANSFORMATION MATRIX OF CHEBYSHEV IV BERNSTEIN POLYNOMIAL BASES ABEDALLAH RABABAH, AYMAN AL

More information

Discrete Orthogonal Moment Features Using Chebyshev Polynomials

Discrete Orthogonal Moment Features Using Chebyshev Polynomials Discrete Orthogoal Momet Features Usig Chebyshev Polyomials R. Mukuda, 1 S.H.Og ad P.A. Lee 3 1 Faculty of Iformatio Sciece ad Techology, Multimedia Uiversity 75450 Malacca, Malaysia. Istitute of Mathematical

More information

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities Polyomials with Ratioal Roots that Differ by a No-zero Costat Philip Gibbs The problem of fidig two polyomials P(x) ad Q(x) of a give degree i a sigle variable x that have all ratioal roots ad differ by

More information

Binary codes from graphs on triples and permutation decoding

Binary codes from graphs on triples and permutation decoding Biary codes from graphs o triples ad permutatio decodig J. D. Key Departmet of Mathematical Scieces Clemso Uiversity Clemso SC 29634 U.S.A. J. Moori ad B. G. Rodrigues School of Mathematics Statistics

More information

POSSIBILISTIC OPTIMIZATION WITH APPLICATION TO PORTFOLIO SELECTION

POSSIBILISTIC OPTIMIZATION WITH APPLICATION TO PORTFOLIO SELECTION THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume, Number /, pp 88 9 POSSIBILISTIC OPTIMIZATION WITH APPLICATION TO PORTFOLIO SELECTION Costi-Cipria POPESCU,

More information

CSE 527, Additional notes on MLE & EM

CSE 527, Additional notes on MLE & EM CSE 57 Lecture Notes: MLE & EM CSE 57, Additioal otes o MLE & EM Based o earlier otes by C. Grat & M. Narasimha Itroductio Last lecture we bega a examiatio of model based clusterig. This lecture will be

More information

The Choquet Integral with Respect to Fuzzy-Valued Set Functions

The Choquet Integral with Respect to Fuzzy-Valued Set Functions The Choquet Itegral with Respect to Fuzzy-Valued Set Fuctios Weiwei Zhag Abstract The Choquet itegral with respect to real-valued oadditive set fuctios, such as siged efficiecy measures, has bee used i

More information

Machine Learning Regression I Hamid R. Rabiee [Slides are based on Bishop Book] Spring

Machine Learning Regression I Hamid R. Rabiee [Slides are based on Bishop Book] Spring Machie Learig Regressio I Hamid R. Rabiee [Slides are based o Bishop Book] Sprig 015 http://ce.sharif.edu/courses/93-94//ce717-1 Liear Regressio Liear regressio: ivolves a respose variable ad a sigle predictor

More information

Computer Aided Synthesis of Interacting Processes Models*

Computer Aided Synthesis of Interacting Processes Models* БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ. BULGARIAN ACADEMY OF SCIENCES ПРОБЛЕМИ НА ТЕХНИЧЕСКАТА КИБЕРНЕТИКА И РОБОТИКАТА, 51 PROBLEMS OF ENGINEERING CYBERNETICS AND ROBOTICS, 51 София. 2001. Sofia Computer Aided

More information

Linear Support Vector Machines

Linear Support Vector Machines Liear Support Vector Machies David S. Roseberg The Support Vector Machie For a liear support vector machie (SVM), we use the hypothesis space of affie fuctios F = { f(x) = w T x + b w R d, b R } ad evaluate

More information

Monte Carlo Optimization to Solve a Two-Dimensional Inverse Heat Conduction Problem

Monte Carlo Optimization to Solve a Two-Dimensional Inverse Heat Conduction Problem Australia Joural of Basic Applied Scieces, 5(): 097-05, 0 ISSN 99-878 Mote Carlo Optimizatio to Solve a Two-Dimesioal Iverse Heat Coductio Problem M Ebrahimi Departmet of Mathematics, Karaj Brach, Islamic

More information

NANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS AO-LEVEL MATHEMATICS

NANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS AO-LEVEL MATHEMATICS NANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS AO-LEVEL MATHEMATICS STRUCTURE OF EXAMINATION PAPER. There will be oe 2-hour paper cosistig of 4 questios.

More information

PARETO-OPTIMAL SOLUTION OF A SCHEDULING PROBLEM ON A SINGLE MACHINE WITH PERIODIC MAINTENANCE AND NON-PRE-EMPTIVE JOBS

PARETO-OPTIMAL SOLUTION OF A SCHEDULING PROBLEM ON A SINGLE MACHINE WITH PERIODIC MAINTENANCE AND NON-PRE-EMPTIVE JOBS Proceedigs of the Iteratioal Coferece o Mechaical Egieerig 2007 (ICME2007) 2-3 December 2007, Dhaka, Bagladesh ICME07-AM-6 PARETO-OPTIMAL SOLUTION OF A SCHEDULING PROBLEM ON A SINGLE MACHINE WITH PERIODIC

More information

TEAM FORMATION. Outline. QFD in Team Formation. Quality Function Deployment (QFD) Basic Planning Matrices

TEAM FORMATION. Outline. QFD in Team Formation. Quality Function Deployment (QFD) Basic Planning Matrices TEAM FORMATION Adrew Kusiak Seamas Ceter Iowa City, Iowa - Tel: - Fax: - adrew-kusiak@uiowa.edu http://www.icae.uiowa.edu/~akusiak Outlie Itroductio The quality fuctio deploymet methodology The aalytical

More information

Properties of Fuzzy Length on Fuzzy Set

Properties of Fuzzy Length on Fuzzy Set Ope Access Library Joural 206, Volume 3, e3068 ISSN Olie: 2333-972 ISSN Prit: 2333-9705 Properties of Fuzzy Legth o Fuzzy Set Jehad R Kider, Jaafar Imra Mousa Departmet of Mathematics ad Computer Applicatios,

More information

CSE 1400 Applied Discrete Mathematics Number Theory and Proofs

CSE 1400 Applied Discrete Mathematics Number Theory and Proofs CSE 1400 Applied Discrete Mathematics Number Theory ad Proofs Departmet of Computer Scieces College of Egieerig Florida Tech Sprig 01 Problems for Number Theory Backgroud Number theory is the brach of

More information

A Planning Approach of Engineering Characteristics Based on QFD-TRIZ Integrated

A Planning Approach of Engineering Characteristics Based on QFD-TRIZ Integrated A Plaig Approach of Egieerig Characteristics Based o QFD-TRIZ Itegrated Shag Liu, Dogya Shi,, Yig Zhag College Mechaical ad Electrical Egieerig, Harbi Egieerig Uiversity, Harbi 5, Chia Postdoctoral Research

More information

Math 5311 Problem Set #5 Solutions

Math 5311 Problem Set #5 Solutions Math 5311 Problem Set #5 Solutios March 9, 009 Problem 1 O&S 11.1.3 Part (a) Solve with boudary coditios u = 1 0 x < L/ 1 L/ < x L u (0) = u (L) = 0. Let s refer to [0, L/) as regio 1 ad (L/, L] as regio.

More information

μ are complex parameters. Other

μ are complex parameters. Other A New Numerical Itegrator for the Solutio of Iitial Value Problems i Ordiary Differetial Equatios. J. Suday * ad M.R. Odekule Departmet of Mathematical Scieces, Adamawa State Uiversity, Mubi, Nigeria.

More information

Oblivious Transfer using Elliptic Curves

Oblivious Transfer using Elliptic Curves Oblivious Trasfer usig Elliptic Curves bhishek Parakh Louisiaa State Uiversity, ato Rouge, L May 4, 006 bstract: This paper proposes a algorithm for oblivious trasfer usig elliptic curves lso, we preset

More information

Shannon Entropy Applied to the Productivity of Organizations. Why Big Organizations Can Seem Stupid

Shannon Entropy Applied to the Productivity of Organizations. Why Big Organizations Can Seem Stupid The Aalytic Solutios Group, LLC Shao Etropy Applied to the Productivity of Orgaizatios Why Big Orgaizatios Ca Seem Stupid Dr. Rich Jaow November 4, 2003 New Jersey Istitute of Techology, Departmet of Physics

More information

The target reliability and design working life

The target reliability and design working life Safety ad Security Egieerig IV 161 The target reliability ad desig workig life M. Holický Kloker Istitute, CTU i Prague, Czech Republic Abstract Desig workig life ad target reliability levels recommeded

More information

Recursive Algorithm for Generating Partitions of an Integer. 1 Preliminary

Recursive Algorithm for Generating Partitions of an Integer. 1 Preliminary Recursive Algorithm for Geeratig Partitios of a Iteger Sug-Hyuk Cha Computer Sciece Departmet, Pace Uiversity 1 Pace Plaza, New York, NY 10038 USA scha@pace.edu Abstract. This article first reviews the

More information

A Study on Fuzzy Complex Linear. Programming Problems

A Study on Fuzzy Complex Linear. Programming Problems It. J. Cotemp. Math. Scieces, Vol. 7, 212, o. 19, 897-98 A Study o Fuzzy Complex Liear Programmig Problems Youess, E. A. (1) ad Mekawy, I. M. (2) (1) Departmet of Mathematics, Faculty of Sciece Tata Uiversity,

More information

Dynamical stability and parametrical vibrations of the laminated plates with complex shape

Dynamical stability and parametrical vibrations of the laminated plates with complex shape (3) 75 88 Dyamical stability ad parametrical vibratios of the lamiated plates with comple shape Abstract The problem of oliear vibratios ad stability aalysis for the symmetric lamiated plates with comple

More information

Subject: Differential Equations & Mathematical Modeling-III

Subject: Differential Equations & Mathematical Modeling-III Power Series Solutios of Differetial Equatios about Sigular poits Subject: Differetial Equatios & Mathematical Modelig-III Lesso: Power series solutios of differetial equatios about Sigular poits Lesso

More information

Interval Intuitionistic Trapezoidal Fuzzy Prioritized Aggregating Operators and their Application to Multiple Attribute Decision Making

Interval Intuitionistic Trapezoidal Fuzzy Prioritized Aggregating Operators and their Application to Multiple Attribute Decision Making Iterval Ituitioistic Trapezoidal Fuzzy Prioritized Aggregatig Operators ad their Applicatio to Multiple Attribute Decisio Makig Xia-Pig Jiag Chogqig Uiversity of Arts ad Scieces Chia cqmaagemet@163.com

More information

Chapter 7. Support Vector Machine

Chapter 7. Support Vector Machine Chapter 7 Support Vector Machie able of Cotet Margi ad support vectors SVM formulatio Slack variables ad hige loss SVM for multiple class SVM ith Kerels Relevace Vector Machie Support Vector Machie (SVM)

More information

Preponderantly increasing/decreasing data in regression analysis

Preponderantly increasing/decreasing data in regression analysis Croatia Operatioal Research Review 269 CRORR 7(2016), 269 276 Prepoderatly icreasig/decreasig data i regressio aalysis Darija Marković 1, 1 Departmet of Mathematics, J. J. Strossmayer Uiversity of Osijek,

More information

Recursive Algorithms. Recurrences. Recursive Algorithms Analysis

Recursive Algorithms. Recurrences. Recursive Algorithms Analysis Recursive Algorithms Recurreces Computer Sciece & Egieerig 35: Discrete Mathematics Christopher M Bourke cbourke@cseuledu A recursive algorithm is oe i which objects are defied i terms of other objects

More information

Polynomial Functions and Their Graphs

Polynomial Functions and Their Graphs Polyomial Fuctios ad Their Graphs I this sectio we begi the study of fuctios defied by polyomial expressios. Polyomial ad ratioal fuctios are the most commo fuctios used to model data, ad are used extesively

More information

Double Stage Shrinkage Estimator of Two Parameters. Generalized Exponential Distribution

Double Stage Shrinkage Estimator of Two Parameters. Generalized Exponential Distribution Iteratioal Mathematical Forum, Vol., 3, o. 3, 3-53 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.9/imf.3.335 Double Stage Shrikage Estimator of Two Parameters Geeralized Expoetial Distributio Alaa M.

More information

2.004 Dynamics and Control II Spring 2008

2.004 Dynamics and Control II Spring 2008 MIT OpeCourseWare http://ocw.mit.edu 2.004 Dyamics ad Cotrol II Sprig 2008 For iformatio about citig these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Massachusetts Istitute of Techology

More information

Poincaré Problem for Nonlinear Elliptic Equations of Second Order in Unbounded Domains

Poincaré Problem for Nonlinear Elliptic Equations of Second Order in Unbounded Domains Advaces i Pure Mathematics 23 3 72-77 http://dxdoiorg/4236/apm233a24 Published Olie Jauary 23 (http://wwwscirporg/oural/apm) Poicaré Problem for Noliear Elliptic Equatios of Secod Order i Ubouded Domais

More information

Fall 2013 MTH431/531 Real analysis Section Notes

Fall 2013 MTH431/531 Real analysis Section Notes Fall 013 MTH431/531 Real aalysis Sectio 8.1-8. Notes Yi Su 013.11.1 1. Defiitio of uiform covergece. We look at a sequece of fuctios f (x) ad study the coverget property. Notice we have two parameters

More information

R is a scalar defined as follows:

R is a scalar defined as follows: Math 8. Notes o Dot Product, Cross Product, Plaes, Area, ad Volumes This lecture focuses primarily o the dot product ad its may applicatios, especially i the measuremet of agles ad scalar projectio ad

More information

Modeling and Estimation of a Bivariate Pareto Distribution using the Principle of Maximum Entropy

Modeling and Estimation of a Bivariate Pareto Distribution using the Principle of Maximum Entropy Sri Laka Joural of Applied Statistics, Vol (5-3) Modelig ad Estimatio of a Bivariate Pareto Distributio usig the Priciple of Maximum Etropy Jagathath Krisha K.M. * Ecoomics Research Divisio, CSIR-Cetral

More information

An Intuitionistic fuzzy count and cardinality of Intuitionistic fuzzy sets

An Intuitionistic fuzzy count and cardinality of Intuitionistic fuzzy sets Malaya Joural of Matematik 4(1)(2013) 123 133 A Ituitioistic fuzzy cout ad cardiality of Ituitioistic fuzzy sets B. K. Tripathy a, S. P. Jea b ad S. K. Ghosh c, a School of Computig Scieces ad Egieerig,

More information

Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm

Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm Joural of ad Eergy Egieerig, 05, 3, 43-437 Published Olie April 05 i SciRes. http://www.scirp.org/joural/jpee http://dx.doi.org/0.436/jpee.05.34058 Study o Coal Cosumptio Curve Fittig of the Thermal Based

More information

A NEW APPROACH TO SOLVE AN UNBALANCED ASSIGNMENT PROBLEM

A NEW APPROACH TO SOLVE AN UNBALANCED ASSIGNMENT PROBLEM A NEW APPROACH TO SOLVE AN UNBALANCED ASSIGNMENT PROBLEM *Kore B. G. Departmet Of Statistics, Balwat College, VITA - 415 311, Dist.: Sagli (M. S.). Idia *Author for Correspodece ABSTRACT I this paper I

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

PAijpam.eu ON TENSOR PRODUCT DECOMPOSITION

PAijpam.eu ON TENSOR PRODUCT DECOMPOSITION Iteratioal Joural of Pure ad Applied Mathematics Volume 103 No 3 2015, 537-545 ISSN: 1311-8080 (prited versio); ISSN: 1314-3395 (o-lie versio) url: http://wwwijpameu doi: http://dxdoiorg/1012732/ijpamv103i314

More information

FLOWSHOP SCHEDULING USING A NETWORK APPROACH

FLOWSHOP SCHEDULING USING A NETWORK APPROACH ,*, A. M. H. Oladeide 1,*, A. I. Momodu 2 ad C. A. Oladeide 3 1, 2, 3DEPARTMENT OF PRODUCTION ENGINEERING, FACULTY OF ENGINEERING, UNIVERSITY OF BENIN, NIGERIA. E-mail addresses: 1 moladeide@uibe.edu,

More information

A statistical method to determine sample size to estimate characteristic value of soil parameters

A statistical method to determine sample size to estimate characteristic value of soil parameters A statistical method to determie sample size to estimate characteristic value of soil parameters Y. Hojo, B. Setiawa 2 ad M. Suzuki 3 Abstract Sample size is a importat factor to be cosidered i determiig

More information

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement Practical Spectral Aaysis (cotiue) (from Boaz Porat s book) Frequecy Measuremet Oe of the most importat applicatios of the DFT is the measuremet of frequecies of periodic sigals (eg., siusoidal sigals),

More information

An Algebraic Elimination Method for the Linear Complementarity Problem

An Algebraic Elimination Method for the Linear Complementarity Problem Volume-3, Issue-5, October-2013 ISSN No: 2250-0758 Iteratioal Joural of Egieerig ad Maagemet Research Available at: wwwijemret Page Number: 51-55 A Algebraic Elimiatio Method for the Liear Complemetarity

More information

Research Article Some E-J Generalized Hausdorff Matrices Not of Type M

Research Article Some E-J Generalized Hausdorff Matrices Not of Type M Abstract ad Applied Aalysis Volume 2011, Article ID 527360, 5 pages doi:10.1155/2011/527360 Research Article Some E-J Geeralized Hausdorff Matrices Not of Type M T. Selmaogullari, 1 E. Savaş, 2 ad B. E.

More information

Linear Algebra Issues in Wireless Communications

Linear Algebra Issues in Wireless Communications Rome-Moscow school of Matrix Methods ad Applied Liear Algebra August 0 September 18, 016 Liear Algebra Issues i Wireless Commuicatios Russia Research Ceter [vladimir.lyashev@huawei.com] About me ead of

More information

Introduction to Optimization Techniques. How to Solve Equations

Introduction to Optimization Techniques. How to Solve Equations Itroductio to Optimizatio Techiques How to Solve Equatios Iterative Methods of Optimizatio Iterative methods of optimizatio Solutio of the oliear equatios resultig form a optimizatio problem is usually

More information

Using Spreadsheets as a Computational Tool in Teaching Mechanical. Engineering

Using Spreadsheets as a Computational Tool in Teaching Mechanical. Engineering Proceedigs of the th WSEAS Iteratioal Coferece o COMPUTERS, Vouliagmei, Athes, Greece, July 3-5, 6 (pp35-3) Usig Spreadsheets as a Computatioal Tool i Teachig Mechaical Egieerig AHMADI-BROOGHANI, ZAHRA

More information

Pneumohydraulic Amplifier with Mechanical Deviation of the Flow

Pneumohydraulic Amplifier with Mechanical Deviation of the Flow БЪЛГАРСКА АКАДЕМИЯ НА НАУКИТЕ. BULGARIAN ACADEMY OF SCIENCES ПРОБЛЕМИ НА ТЕХНИЧЕСКАТА КИБЕРНЕТИКА И РОБОТИКАТА, 49 PROBLEMS OF ENGINEERING CYBERNETICS AND ROBOTICS, 49 София. 2000. Sofia Pneumohydraulic

More information

First, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So,

First, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So, 0 2. OLS Part II The OLS residuals are orthogoal to the regressors. If the model icludes a itercept, the orthogoality of the residuals ad regressors gives rise to three results, which have limited practical

More information

ON POINTWISE BINOMIAL APPROXIMATION

ON POINTWISE BINOMIAL APPROXIMATION Iteratioal Joural of Pure ad Applied Mathematics Volume 71 No. 1 2011, 57-66 ON POINTWISE BINOMIAL APPROXIMATION BY w-functions K. Teerapabolar 1, P. Wogkasem 2 Departmet of Mathematics Faculty of Sciece

More information

Research Article Robust Linear Programming with Norm Uncertainty

Research Article Robust Linear Programming with Norm Uncertainty Joural of Applied Mathematics Article ID 209239 7 pages http://dx.doi.org/0.55/204/209239 Research Article Robust Liear Programmig with Norm Ucertaity Lei Wag ad Hog Luo School of Ecoomic Mathematics Southwester

More information

Lecture 3. Digital Signal Processing. Chapter 3. z-transforms. Mikael Swartling Nedelko Grbic Bengt Mandersson. rev. 2016

Lecture 3. Digital Signal Processing. Chapter 3. z-transforms. Mikael Swartling Nedelko Grbic Bengt Mandersson. rev. 2016 Lecture 3 Digital Sigal Processig Chapter 3 z-trasforms Mikael Swartlig Nedelko Grbic Begt Madersso rev. 06 Departmet of Electrical ad Iformatio Techology Lud Uiversity z-trasforms We defie the z-trasform

More information

DETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS.

DETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS. ICSV4 Cairs Australia 9- July 7 DTRMINATION OF MCHANICAL PROPRTIS OF A NON- UNIFORM BAM USING TH MASURMNT OF TH XCITD LONGITUDINAL LASTIC VIBRATIONS Pavel Aokhi ad Vladimir Gordo Departmet of the mathematics

More information

ECON 3150/4150, Spring term Lecture 3

ECON 3150/4150, Spring term Lecture 3 Itroductio Fidig the best fit by regressio Residuals ad R-sq Regressio ad causality Summary ad ext step ECON 3150/4150, Sprig term 2014. Lecture 3 Ragar Nymoe Uiversity of Oslo 21 Jauary 2014 1 / 30 Itroductio

More information

Daniel Lee Muhammad Naeem Chingyu Hsu

Daniel Lee Muhammad Naeem Chingyu Hsu omplexity Aalysis of Optimal Statioary all Admissio Policy ad Fixed Set Partitioig Policy for OVSF-DMA ellular Systems Daiel Lee Muhammad Naeem higyu Hsu Backgroud Presetatio Outlie System Model all Admissio

More information

Graphical solutions of 2-variable problems Polyhedra and convex sets. Recall: piecewise linear convex functions

Graphical solutions of 2-variable problems Polyhedra and convex sets. Recall: piecewise linear convex functions Recap, ad outlie of Lecture 3 Last time: Formal defiitios of LP compoets ad solutios Ifeasible ad ubouded LPs Covex (ad cocave) fuctios A fuctio f : is called covex if x, y,ad λ [0, 1], f (λx +(1 λ)y)

More information

Lectures on Stochastic System Analysis and Bayesian Updating

Lectures on Stochastic System Analysis and Bayesian Updating Lectures o Stochastic System Aalysis ad Bayesia Updatig Jue 29-July 13 2005 James L. Beck, Califoria Istitute of Techology Jiaye Chig, Natioal Taiwa Uiversity of Sciece & Techology Siu-Kui (Iva) Au, Nayag

More information

Taylor polynomial solution of difference equation with constant coefficients via time scales calculus

Taylor polynomial solution of difference equation with constant coefficients via time scales calculus TMSCI 3, o 3, 129-135 (2015) 129 ew Treds i Mathematical Scieces http://wwwtmscicom Taylor polyomial solutio of differece equatio with costat coefficiets via time scales calculus Veysel Fuat Hatipoglu

More information

Approximating the ruin probability of finite-time surplus process with Adaptive Moving Total Exponential Least Square

Approximating the ruin probability of finite-time surplus process with Adaptive Moving Total Exponential Least Square WSEAS TRANSACTONS o BUSNESS ad ECONOMCS S. Khotama, S. Boothiem, W. Klogdee Approimatig the rui probability of fiite-time surplus process with Adaptive Movig Total Epoetial Least Square S. KHOTAMA, S.

More information

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y Questio (a) A square matrix A= A is called positive defiite if the quadratic form waw > 0 for every o-zero vector w [Note: Here (.) deotes the traspose of a matrix or a vector]. Let 0 A = 0 = show that:

More information