System in Weibull Distribution

Size: px
Start display at page:

Download "System in Weibull Distribution"

Transcription

1 Internatonal Matheatcal Foru 4 9 no Relablty Equvalence Factors of a Seres-Parallel Syste n Webull Dstrbuton M. A. El-Dacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co Abstract The perforance of a relablty syste can be proved by dfferent ethods e.g. the relablty of one or ore coponents can be proved hot or cold redundant coponents can be added to the syste. Soetes these easures can be equvalent as they wll have the sae effect on soe perforance easure of the syste. Ths paper dscusses the relablty equvalences of a seres-parallel syste. The syste consdered here conssts of subsystes connected n parallel wth subsyste consstng of n ndependent and dentcal coponents n seres for. The falure rates of the syste coponents are functons of te wth a lfe dstrbuton of Webull dstrbuton. Three dfferent ethods are used to prove the gven syste relablty. The relablty equvalence factor s obtaned usng the relablty functon. The fractles of the orgnal and proved systes are also obtaned. Nuercal exaple s presented to nterpret how to utlze the obtaned results. Keywords: Relablty MTTF equvalence factors seres- parallel syste Webull dstrbuton. Introducton In relablty theory one way to prove the perforance of a syste s to use the redundancy ethod. There are two an such ethods:. ot duplcaton ethod: n ths case t s assued that soe of the syste coponents are duplcated n parallel.. old duplcaton ethod: n ths case t s assued that soe of the syste coponents are duplcated n parallel va a perfect swtch. Unfortunately for any dfferent reasons such as space ltaton hgh cost etc t s not always possble to prove a syste by duplcatng soe or all of ts

2 94 M. A. El-Dacese coponents. For exaple satelltes and space arcrafts have lted space whch doesn't allow coponent duplcaton. Also soe crochps are so expansve that anufacturers cannot afford to duplcate the. In such cases where duplcaton s not possble the engneer turns to another well-known ethod n relablty theory the so-called reducton ethod. In ths ethod t s assued that the falure rates of soe of the syste coponents are reduced by a factor ρ < ρ <. Now once the reducton ethod s adopted the an proble facng the engneer s to decde to what degree the falure rate should be decreased n order to prove the syste. To solve ths proble one can ake equvalence between the reducton ethod and the duplcaton ethod based on soe relablty easures. In other words the desgn of the syste proved by the reducton ethod should be equvalent to the desgn of the syste proved by one of the duplcaton ethods. The coparson of the desgns produces the so-called relablty equvalence factors []. The concept of the relablty equvalence factors was ntroduced n the report [] and appled to varous relablty systes n [] and [4]. Rade [5 6] appled ths concept for the two-coponent parallel and seres systes wth ndependent and dentcal coponents whose lfetes follow the exponental dstrbuton. Sarhan [7- ] derved the relablty equvalence factors of other ore general systes. The systes studed by Sarhan are the seres syste [7] a basc seres-parallel syste [8] a brdge network syste [9] the parallel syste [] a parallel-seres syste [] and a general seres-parallel syste []. All these systes have ndependent and dentcal exponental coponents. In ths paper we hope to dscuss ore lfe dstrbutons Webull dstrbuton for exaple. Dfferent fro the constant falure rate of exponental dstrbuton Webull dstrbuton has a te varyng falure rate. So the relablty equvalence factors should be generalzed accordngly. In the current study we consder a general seres-parallel syste and assue that all coponents are ndependent and dentcally Webull dstrbuted. Frst we coputed the relablty functon and the ean te to falure MTTF of the syste. Second we coputed the sae relablty easures when the syste s proved usng the reducton ethod. Thrd we coputed the sae easures when the syste s proved usng the hot and cold duplcaton ethods. Fnally we equate the relablty functon of the syste proved by duplcaton wth the relablty functon of the syste proved by reducton to get the survval relablty equvalence factors. These factors can be used by the engneer to decde to what degree the falure rate of soe of the syste coponents should be decreased n order to prove the perforance of the syste wthout duplcatng any coponent.. Seres parallel syste The syste consdered here conssts of subsystes connected n parallel wth subsyste consstng of n coponents n seres for. Fgure shows the dagra of a seres parallel syste. lock n lock n lock n Fgure a Seres-parallel syste.

3 Relablty equvalence factors 94 Let R t be the relablty of subsyste and r j t be the relablty of coponent j j n n subsyste =. Then n = R t r t j= The syste relablty says Rt s gven by R t = j R t Usng the syste relablty takes the followng for: n R t = r t j= j Assung that the syste coponents are ndependent and dentcal. The lfete of each coponent s Webull dstrbuted wth falure rate z t = λ t ; λ >. That s r j t = exp λt for j= n and. Thus the syste relablty becoes R t = exp n λ t Usng equaton the syste ean te to falure MTTF can be derved n the followng for: MTTF = R t dt 4. The proved systes The relablty of the syste can be proved accordng to one of the followng two dfferent ethods: - Reducton ethod. - Standby redundancy ethod: a ot standby redundancy called hot duplcaton ethod b old standby redundancy called cold duplcaton ethod. In the followng sectons we wll derve the relablty functons and the ean te to falures of the systes proved accordng to the ethods entoned above... The reducton ethod It s assued n ths ethod that the syste can be proved by reducng the falure rates of the set A of syste coponents by a factor s < s <. ere we consder that reducng the falure rate by reducng only the scale paraeter λ of the set A of syste coponents by a factor ρ. Assung that the set A conssts of k coponents; k n where n denotes the total nuber of the syste coponents. Assung that the coponents belongng to A can be dstrbuted nto the subsystes of the syste such that k coponents of the subsyste belong to the set A where k n. We denote such a A A K A k k K k set by ether A A or A k. Let R Aρ t denote the relablty functon of the syste proved by reducng the scale paraeter λ of the set A of ts coponents by a factor ρ. Let MTTF Aρ t be the ean te to falure of the syste that has the relablty functon R Aρ t. The relablty functon of coponent j n the subsyste j= n ; after reducng ts scale paraeter λ by a factor ρ s t = exp ρ λt. 5 r j ρ

4 944 M. A. El-Dacese Thus R Aρ t can be derved as follows: That s R k n k A ρ t = rj ρ t rj t j= j= A ρ R t = exp [ n + k ρ ] λt 6 Usng equaton 6 MTTF Aρ t can be derved n the followng for: A t = RA ρ t MTTF ρ dt 7.. The hot duplcaton ethod Assung that n the hot duplcaton ethod each coponent of the set s proved by assung a hot duplcaton of another dentcal one. Suppose that the set conssts of h coponents h n. Thus the set can be wrtten as a unon of dsjont subsets such that the subset contans those coponents belongng to the subsyste ;. That s h n and h = K We denote such a set by ether or. Let r j t denote the relablty functon of the coponent j n the subsyste j= n and. when t s proved accordng to hot duplcaton ethod. Thus t = exp λt exp λt. 8 r j h h h Let R t and MTTF t denotes respectvely the relablty functon and ean te to falure of the desgn obtaned by provng the coponents belongng to the set accordng to the hot duplcaton ethod. Thus the functon R t can be derved as follows: R t = = h n h rj t rj j= j= t K h h [ exp λ t ] exp n λt 9 Usng 9 MTTF t can be derved n the followng for:.. The cold duplcaton ethod MTTF t = R t dt In the cold duplcaton ethod t s assued that each coponent of the set s connected wth an dentcal coponent va a perfect swtch. Assue that conssts of c coponents c n. Thus the set can be wrtten as a unon of dsjont subsets such that the subset contans those coponents belongng to the subsyste ;. That s = c = = c c n. We denote such a set by ether K c c c or K c Let r t j denote the relablty functon of the coponent j n the subsyste ; j= n and when t s proved accordng to cold duplcaton ethod. Thus.

5 Relablty equvalence factors 945 r j t = + λt exp λt Let R t and MTTF t denotes respectvely the relablty functon and ean te to falure of the desgn obtaned by provng the coponents belongng to the set accordng to the cold duplcaton ethod. Thus the functon R t can be derved as follows: R t = = c n c rj t j= j= r t j c + λ t exp n λt Usng MTTF t can be derved n the followng for: MTTF t = R t dt 4. Relablty equvalence factors Now we gve the defnton of relablty equvalence factor: A relablty equvalence factor s a factor by whch a characterstc of coponents of a syste desgn has to be ultpled n order to reach equalty of a characterstc of ths desgn and a dfferent desgn regarded as a standard [8]. As enton above the relablty equvalence factor s defned as the factor by whch the falure rates of soe of the syste s coponents should be reduced n order to reach equalty of the relablty of another better syste. Dfferent fro the constant falure rate of exponental dstrbuton the falure rate of Webull dstrbuton s te varyng accordngly the ethod used to obtan the relablty equvalence factors n the case of usng Webull dstrbuton s dfferent than the ethod used n the exponental case. For convenence of calculaton whle te varyng falure rate s reduced by factor s we consder that the scale paraeter of Webull dstrbuton reduced fro λ to ρλ only. Fro the falure rate of Webull dstrbuton z t = λ t we know s z t = ρλ t 4 Obvously s wll ncrease as ρ ncreases and they fall n nterval also. In what follows we wll present how to calculate ρ only and we obtan s by takng ρ n equaton 4. Next we present soe of relablty equvalence factors of the proved seres-parallel syste studed here. 4.. ot relablty equvalence factor The hot relablty equvalence factor say s A α s defned as that factor by whch the falure rate of the set A coponents should be reduced so that one could obtan a desgn of the syste coponents wth a relablty functon that equals the relablty functon of a desgn obtaned fro the orgnal syste by assung hot duplcatons of the set coponents. As entoned before the falure rate reduced by s s equal to the scale A α

6 946 M. A. El-Dacese paraeter reduced fro λ to ρ A α λ. That s ρ A α s the soluton of the followng syste of two equatons R A ρ t = α R t = α 5 Therefore fro equatons 6 9 and 5 ρ A α s the soluton of the followng non-lnear syste of equatons wth respect to x = exp λ t and ρ for a gven α n + k ρ α = x 6 h n α = x x 7 As t sees the above syste of non-lnear equatons has no closed-for soluton. So a nuercal technque ethod s requred to get the soluton of such a syste. So we have ρ = ρa α. ence the hot relablty equvalence factor s A α s obtaned fro equaton old relablty equvalence factor The cold relablty equvalence factor say s A α s defned as that factor by whch the falure rate of the set A coponents should be reduced so that one could obtan a desgn of the syste coponents wth a relablty functon that equals the relablty functon of a desgn obtaned fro the orgnal syste by assung cold duplcatons of the set coponents. As entoned before the falure rate reduced by sa α s equal to the scale paraeter reduced fro λ to ρ A α λ. That s ρ A α s the soluton of the followng syste of two equatons R A ρ t = α R t = α 8 Therefore fro equatons 6 and 8 ρ A α s the soluton of the followng non-lnear syste of equatons wth respect to x = exp λ t and ρ for a gven α n + k ρ α = x 9 c n α = + ln/ x x As t sees the above syste of non-lnear equatons has no closed-for soluton. So a nuercal technque ethod s requred to get the soluton of such a syste. So we have ρ = ρa α. ence the cold relablty equvalence factor s A α s obtaned fro equaton α-fractles In ths secton we deduce the α-fractles of the orgnal desgn and the proved desgns whch are a popular easure of relablty n echancal ndustry. D Let L α be the α-fractle of the orgnal syste. Let L α be the α- fractle of the desgn obtaned by provng the set coponents accordng to hot D = or cold D = duplcaton ethod. The α-fractle of a syste havng relablty functon Rt say L α s defned

7 Relablty equvalence factors 947 as the soluton of the followng equaton wth respect to L: R L α/ λ = α Usng equatons and one can obtan L of the orgnal syste by solvng the followng equaton wth respect to L: α = exp n L Also the α-fractle of the proved syste that has the relablty functon R D t D say L α can be obtaned by solvng the followng equaton wth respect to L: R D L α/ λ = α D = Thus accordng to 9 and one can fnd L α by solvng the followng equaton wth respect to L: h α = exp L exp n L 4 Fnally usng and one can copute L α by solvng the followng equaton wth respect to L: c = + L α exp n L 5 Equatons 4 and 5 have no closed-for solutons n L so a nuercal technque ethod s needed to get the values of α-fractles. 6. A nuercal results Soe nuercal results are gven n ths secton to llustrate how to nterpret the theoretcal results prevously obtaned. In the followng exaple we assue a seres-parallel syste wth n =5 = n = n = and =. The coponents are ndependent and dentcal. For such syste ρ D A A α ; D= for dfferent sets A A = A A = when α =. are coputed. Tables and gve ρ A α and ρ A α respectvely. Notce that negatve value of ρ D A α eans that t s not possble to reduce the falure rate of the set A coponents n order to prove the desgn of syste to be equvalent wth that desgn of the syste whch can be obtaned by provng the set coponents accordng to the redundancy ethods. Table gves the α-fractles of the orgnal syste for α =.. Table 4 gves the α-fractles of the systes proved accordng to hot and cold duplcaton ethods for α =..

8 948 M. A. El-Dacese Table α ρ A α A A A A A A A A A A A

9 Relablty equvalence factors 949 Table α ρ A α A. A A A A A A A A A A Table The α-fractles α L α. α L

10 95 M. A. El-Dacese D Table 4 The α-fractles α L α L L Fgure the relablty functons of the orgnal and soe odfed systes. Fgure shows the relablty functons of the orgnal syste and of the systes odfed by provng the sets and 5 of coponents accordng to hot and cold duplcaton ethods. Fro fgure we fnd that: a. ot duplcaton of the set coponents gves an proved desgn wth the lowest relablty functon aong all of those proved desgns whch can be obtaned by provng any other set of coponents accordng to ether the hot or cold duplcaton ethods. b. old duplcaton of the set 5 coponents gves an proved desgn wth a hghest relablty functon aong all of those proved desgns whch can be obtaned by provng any other set of coponents accordng to ether the hot or cold duplcaton ethods. c. Iprovng coponents of the set accordng to the hot cold duplcaton ethod ncreases the te at whch the syste relablty s.4 fro. te easure to.9.. d. Iprovng coponents of the set accordng to the hot cold duplcaton 5 ethod ncreases the te at whch the syste relablty s.4 fro. te easure to.87.4.

11 Relablty equvalence factors oncluson In ths paper we dscussed the relablty equvalence of a seres-parallel syste wth dentcal and ndependent coponents. It s assued that the coponents of the syste had a te varyng falure rates. Three ways naely the reducton hold duplcaton and cold duplcaton ethods are used to prove the syste relablty. A relablty equvalence factor was derved. A nuercal exaple s used to llustrate how the results obtaned can be appled. In the future we hope that we wll be able to study the relablty equvalence of ore coplcated systes wth ndependent and dentcal or non dentcal coponents. Also we hope that we can deterne the optal nuber of coponents to duplcate n the duplcaton ethods and the optal nuber of coponents whose falure rate s to be reduced n the reducton ethod. References [] Sarhan A.M. Tadj L. Al-khedhar A. and A. Mustafa Equvalence Factors of a Parallel-Seres Syste Appled Scences [] Rade L. Relablty Equvalence Studes n Statstcal Qualty ontrol and Relablty 989- Matheatcal Statstcs halers Unversty of Technology. [] Rade L. Relablty Systes of -state oponents Studes n Statstcal Qualty ontrol and Relablty 99- Matheatcal Statstcs halers Unversty of Technology. [4] Rade L. Perforance Measures for Relablty Systes wth a old Standby wth a Rando Swtch Studes n Statstcal Qualty ontrol and Relablty 99 halers Unversty of Technology. [5] Rade L. Relablty Equvalence Mcroelectroncs & Relablty No [6] Rade L. Relablty Survval Equvalence" Mcroelectroncs & Relablty No [7] Sarhan A.M. Relablty Equvalence of Independent and Non-dentcal oponents Seres Systes Relablty Engneerng & Syste Safety 67 No. 9-. [8] Sarhan A.M. Relablty Equvalence wth a asc Seres-Parallel Syste Appled Matheatcs & oputaton No. 5-. [9] Sarhan A.M. Relablty Equvalence Factors of a rdge Network Syste Internatonal Journal of Relablty & Applcatons No [] Sarhan A.M. Relablty Equvalence Factors of a Parallel Syste Relablty Engneerng & Syste Safety 87 No [] Sarhan A.M. Relablty equvalence factors of a general seres-parallel syste Relablty Engneerng & Syste Safety 94 No Receved: October 8

Applied Mathematics Letters

Applied Mathematics Letters Appled Matheatcs Letters 2 (2) 46 5 Contents lsts avalable at ScenceDrect Appled Matheatcs Letters journal hoepage: wwwelseverco/locate/al Calculaton of coeffcents of a cardnal B-splne Gradr V Mlovanovć

More information

Excess Error, Approximation Error, and Estimation Error

Excess Error, Approximation Error, and Estimation Error E0 370 Statstcal Learnng Theory Lecture 10 Sep 15, 011 Excess Error, Approxaton Error, and Estaton Error Lecturer: Shvan Agarwal Scrbe: Shvan Agarwal 1 Introducton So far, we have consdered the fnte saple

More information

XII.3 The EM (Expectation-Maximization) Algorithm

XII.3 The EM (Expectation-Maximization) Algorithm XII.3 The EM (Expectaton-Maxzaton) Algorth Toshnor Munaata 3/7/06 The EM algorth s a technque to deal wth varous types of ncoplete data or hdden varables. It can be appled to a wde range of learnng probles

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

Our focus will be on linear systems. A system is linear if it obeys the principle of superposition and homogenity, i.e.

Our focus will be on linear systems. A system is linear if it obeys the principle of superposition and homogenity, i.e. SSTEM MODELLIN In order to solve a control syste proble, the descrptons of the syste and ts coponents ust be put nto a for sutable for analyss and evaluaton. The followng ethods can be used to odel physcal

More information

Reliability estimation in Pareto-I distribution based on progressively type II censored sample with binomial removals

Reliability estimation in Pareto-I distribution based on progressively type II censored sample with binomial removals Journal of Scentfc esearch Developent (): 08-3 05 Avalable onlne at wwwjsradorg ISSN 5-7569 05 JSAD elablty estaton n Pareto-I dstrbuton based on progressvely type II censored saple wth bnoal reovals Ilhan

More information

Statistical analysis of Accelerated life testing under Weibull distribution based on fuzzy theory

Statistical analysis of Accelerated life testing under Weibull distribution based on fuzzy theory Statstcal analyss of Accelerated lfe testng under Webull dstrbuton based on fuzzy theory Han Xu, Scence & Technology on Relablty & Envronental Engneerng Laboratory, School of Relablty and Syste Engneerng,

More information

Several generation methods of multinomial distributed random number Tian Lei 1, a,linxihe 1,b,Zhigang Zhang 1,c

Several generation methods of multinomial distributed random number Tian Lei 1, a,linxihe 1,b,Zhigang Zhang 1,c Internatonal Conference on Appled Scence and Engneerng Innovaton (ASEI 205) Several generaton ethods of ultnoal dstrbuted rando nuber Tan Le, a,lnhe,b,zhgang Zhang,c School of Matheatcs and Physcs, USTB,

More information

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family

Using T.O.M to Estimate Parameter of distributions that have not Single Exponential Family IOSR Journal of Mathematcs IOSR-JM) ISSN: 2278-5728. Volume 3, Issue 3 Sep-Oct. 202), PP 44-48 www.osrjournals.org Usng T.O.M to Estmate Parameter of dstrbutons that have not Sngle Exponental Famly Jubran

More information

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

PROBABILITY AND STATISTICS Vol. III - Analysis of Variance and Analysis of Covariance - V. Nollau ANALYSIS OF VARIANCE AND ANALYSIS OF COVARIANCE

PROBABILITY AND STATISTICS Vol. III - Analysis of Variance and Analysis of Covariance - V. Nollau ANALYSIS OF VARIANCE AND ANALYSIS OF COVARIANCE ANALYSIS OF VARIANCE AND ANALYSIS OF COVARIANCE V. Nollau Insttute of Matheatcal Stochastcs, Techncal Unversty of Dresden, Gerany Keywords: Analyss of varance, least squares ethod, odels wth fxed effects,

More information

Study of the possibility of eliminating the Gibbs paradox within the framework of classical thermodynamics *

Study of the possibility of eliminating the Gibbs paradox within the framework of classical thermodynamics * tudy of the possblty of elnatng the Gbbs paradox wthn the fraework of classcal therodynacs * V. Ihnatovych Departent of Phlosophy, Natonal echncal Unversty of Ukrane Kyv Polytechnc Insttute, Kyv, Ukrane

More information

Slobodan Lakić. Communicated by R. Van Keer

Slobodan Lakić. Communicated by R. Van Keer Serdca Math. J. 21 (1995), 335-344 AN ITERATIVE METHOD FOR THE MATRIX PRINCIPAL n-th ROOT Slobodan Lakć Councated by R. Van Keer In ths paper we gve an teratve ethod to copute the prncpal n-th root and

More information

COS 511: Theoretical Machine Learning

COS 511: Theoretical Machine Learning COS 5: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture #0 Scrbe: José Sões Ferrera March 06, 203 In the last lecture the concept of Radeacher coplexty was ntroduced, wth the goal of showng that

More information

Designing Fuzzy Time Series Model Using Generalized Wang s Method and Its application to Forecasting Interest Rate of Bank Indonesia Certificate

Designing Fuzzy Time Series Model Using Generalized Wang s Method and Its application to Forecasting Interest Rate of Bank Indonesia Certificate The Frst Internatonal Senar on Scence and Technology, Islac Unversty of Indonesa, 4-5 January 009. Desgnng Fuzzy Te Seres odel Usng Generalzed Wang s ethod and Its applcaton to Forecastng Interest Rate

More information

ABSTRACT

ABSTRACT RELIABILITY AND SENSITIVITY ANALYSIS OF THE K-OUT-OF-N:G WARM STANDBY PARALLEL REPAIRABLE SYSTEM WITH REPLACEMENT AT COMMON-CAUSE FAILURE USING MARKOV MODEL M. A. El-Damcese 1 and N. H. El-Sodany 2 1 Mathematcs

More information

On Pfaff s solution of the Pfaff problem

On Pfaff s solution of the Pfaff problem Zur Pfaff scen Lösung des Pfaff scen Probles Mat. Ann. 7 (880) 53-530. On Pfaff s soluton of te Pfaff proble By A. MAYER n Lepzg Translated by D. H. Delpenc Te way tat Pfaff adopted for te ntegraton of

More information

The optimal delay of the second test is therefore approximately 210 hours earlier than =2.

The optimal delay of the second test is therefore approximately 210 hours earlier than =2. THE IEC 61508 FORMULAS 223 The optmal delay of the second test s therefore approxmately 210 hours earler than =2. 8.4 The IEC 61508 Formulas IEC 61508-6 provdes approxmaton formulas for the PF for smple

More information

International Journal of Mathematical Archive-9(3), 2018, Available online through ISSN

International Journal of Mathematical Archive-9(3), 2018, Available online through   ISSN Internatonal Journal of Matheatcal Archve-9(3), 208, 20-24 Avalable onlne through www.ja.nfo ISSN 2229 5046 CONSTRUCTION OF BALANCED INCOMPLETE BLOCK DESIGNS T. SHEKAR GOUD, JAGAN MOHAN RAO M AND N.CH.

More information

What is LP? LP is an optimization technique that allocates limited resources among competing activities in the best possible manner.

What is LP? LP is an optimization technique that allocates limited resources among competing activities in the best possible manner. (C) 998 Gerald B Sheblé, all rghts reserved Lnear Prograng Introducton Contents I. What s LP? II. LP Theor III. The Splex Method IV. Refneents to the Splex Method What s LP? LP s an optzaton technque that

More information

Integral Transforms and Dual Integral Equations to Solve Heat Equation with Mixed Conditions

Integral Transforms and Dual Integral Equations to Solve Heat Equation with Mixed Conditions Int J Open Probles Copt Math, Vol 7, No 4, Deceber 214 ISSN 1998-6262; Copyrght ICSS Publcaton, 214 www-csrsorg Integral Transfors and Dual Integral Equatons to Solve Heat Equaton wth Mxed Condtons Naser

More information

Estimation of Reliability in Multicomponent Stress-Strength Based on Generalized Rayleigh Distribution

Estimation of Reliability in Multicomponent Stress-Strength Based on Generalized Rayleigh Distribution Journal of Modern Appled Statstcal Methods Volue 13 Issue 1 Artcle 4 5-1-014 Estaton of Relablty n Multcoponent Stress-Strength Based on Generalzed Raylegh Dstrbuton Gadde Srnvasa Rao Unversty of Dodoa,

More information

1 Definition of Rademacher Complexity

1 Definition of Rademacher Complexity COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture #9 Scrbe: Josh Chen March 5, 2013 We ve spent the past few classes provng bounds on the generalzaton error of PAClearnng algorths for the

More information

PARAMETER ESTIMATION IN WEIBULL DISTRIBUTION ON PROGRESSIVELY TYPE- II CENSORED SAMPLE WITH BETA-BINOMIAL REMOVALS

PARAMETER ESTIMATION IN WEIBULL DISTRIBUTION ON PROGRESSIVELY TYPE- II CENSORED SAMPLE WITH BETA-BINOMIAL REMOVALS Econoy & Busness ISSN 1314-7242, Volue 10, 2016 PARAMETER ESTIMATION IN WEIBULL DISTRIBUTION ON PROGRESSIVELY TYPE- II CENSORED SAMPLE WITH BETA-BINOMIAL REMOVALS Ilhan Usta, Hanef Gezer Departent of Statstcs,

More information

,..., k N. , k 2. ,..., k i. The derivative with respect to temperature T is calculated by using the chain rule: & ( (5) dj j dt = "J j. k i.

,..., k N. , k 2. ,..., k i. The derivative with respect to temperature T is calculated by using the chain rule: & ( (5) dj j dt = J j. k i. Suppleentary Materal Dervaton of Eq. 1a. Assue j s a functon of the rate constants for the N coponent reactons: j j (k 1,,..., k,..., k N ( The dervatve wth respect to teperature T s calculated by usng

More information

Minimization of l 2 -Norm of the KSOR Operator

Minimization of l 2 -Norm of the KSOR Operator ournal of Matheatcs and Statstcs 8 (): 6-70, 0 ISSN 59-36 0 Scence Publcatons do:0.38/jssp.0.6.70 Publshed Onlne 8 () 0 (http://www.thescpub.co/jss.toc) Mnzaton of l -Nor of the KSOR Operator Youssef,

More information

Chapter 13. Gas Mixtures. Study Guide in PowerPoint. Thermodynamics: An Engineering Approach, 5th edition by Yunus A. Çengel and Michael A.

Chapter 13. Gas Mixtures. Study Guide in PowerPoint. Thermodynamics: An Engineering Approach, 5th edition by Yunus A. Çengel and Michael A. Chapter 3 Gas Mxtures Study Gude n PowerPont to accopany Therodynacs: An Engneerng Approach, 5th edton by Yunus A. Çengel and Mchael A. Boles The dscussons n ths chapter are restrcted to nonreactve deal-gas

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

More information

Solutions for Homework #9

Solutions for Homework #9 Solutons for Hoewor #9 PROBEM. (P. 3 on page 379 n the note) Consder a sprng ounted rgd bar of total ass and length, to whch an addtonal ass s luped at the rghtost end. he syste has no dapng. Fnd the natural

More information

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 )

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 ) Kangweon-Kyungk Math. Jour. 4 1996), No. 1, pp. 7 16 AN ITERATIVE ROW-ACTION METHOD FOR MULTICOMMODITY TRANSPORTATION PROBLEMS Yong Joon Ryang Abstract. The optmzaton problems wth quadratc constrants often

More information

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests

Simulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests Smulated of the Cramér-von Mses Goodness-of-Ft Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth

More information

Numerical Solution of Ordinary Differential Equations

Numerical Solution of Ordinary Differential Equations Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples

More information

BAYESIAN CURVE FITTING USING PIECEWISE POLYNOMIALS. Dariusz Biskup

BAYESIAN CURVE FITTING USING PIECEWISE POLYNOMIALS. Dariusz Biskup BAYESIAN CURVE FITTING USING PIECEWISE POLYNOMIALS Darusz Bskup 1. Introducton The paper presents a nonparaetrc procedure for estaton of an unknown functon f n the regresson odel y = f x + ε = N. (1) (

More information

Revision: December 13, E Main Suite D Pullman, WA (509) Voice and Fax

Revision: December 13, E Main Suite D Pullman, WA (509) Voice and Fax .9.1: AC power analyss Reson: Deceber 13, 010 15 E Man Sute D Pullan, WA 99163 (509 334 6306 Voce and Fax Oerew n chapter.9.0, we ntroduced soe basc quanttes relate to delery of power usng snusodal sgnals.

More information

The Non-equidistant New Information Optimizing MGM(1,n) Based on a Step by Step Optimum Constructing Background Value

The Non-equidistant New Information Optimizing MGM(1,n) Based on a Step by Step Optimum Constructing Background Value Appl. Math. Inf. Sc. 6 No. 3 745-750 (0) 745 Appled Matheatcs & Inforaton Scences An Internatonal Journal The Non-equdstant New Inforaton Optzng MGM(n) Based on a Step by Step Optu Constructng Background

More information

Estimation in Step-stress Partially Accelerated Life Test for Exponentiated Pareto Distribution under Progressive Censoring with Random Removal

Estimation in Step-stress Partially Accelerated Life Test for Exponentiated Pareto Distribution under Progressive Censoring with Random Removal Journal of Advances n Matheatcs and Coputer Scence 5(): -6, 07; Artcle no.jamcs.3469 Prevously known as Brtsh Journal of Matheatcs & Coputer Scence ISSN: 3-085 Estaton n Step-stress Partally Accelerated

More information

Denote the function derivatives f(x) in given points. x a b. Using relationships (1.2), polynomials (1.1) are written in the form

Denote the function derivatives f(x) in given points. x a b. Using relationships (1.2), polynomials (1.1) are written in the form SET OF METHODS FO SOUTION THE AUHY POBEM FO STIFF SYSTEMS OF ODINAY DIFFEENTIA EUATIONS AF atypov and YuV Nulchev Insttute of Theoretcal and Appled Mechancs SB AS 639 Novosbrs ussa Introducton A constructon

More information

ISSN X Reliability of linear and circular consecutive-kout-of-n systems with shock model

ISSN X Reliability of linear and circular consecutive-kout-of-n systems with shock model Afrka Statstka Vol. 101, 2015, pages 795 805. DOI: http://dx.do.org/10.16929/as/2015.795.70 Afrka Statstka ISSN 2316-090X Relablty of lnear and crcular consecutve-kout-of-n systems wth shock model Besma

More information

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method

Comparison of the Population Variance Estimators. of 2-Parameter Exponential Distribution Based on. Multiple Criteria Decision Making Method Appled Mathematcal Scences, Vol. 7, 0, no. 47, 07-0 HIARI Ltd, www.m-hkar.com Comparson of the Populaton Varance Estmators of -Parameter Exponental Dstrbuton Based on Multple Crtera Decson Makng Method

More information

Case Study of Cascade Reliability with weibull Distribution

Case Study of Cascade Reliability with weibull Distribution ISSN: 77-3754 ISO 900:008 Certfed Internatonal Journal of Engneerng and Innovatve Technology (IJEIT) Volume, Issue 6, June 0 Case Study of Cascade Relablty wth webull Dstrbuton Dr.T.Shyam Sundar Abstract

More information

Solving Fuzzy Linear Programming Problem With Fuzzy Relational Equation Constraint

Solving Fuzzy Linear Programming Problem With Fuzzy Relational Equation Constraint Intern. J. Fuzz Maeatcal Archve Vol., 0, -0 ISSN: 0 (P, 0 0 (onlne Publshed on 0 Septeber 0 www.researchasc.org Internatonal Journal of Solvng Fuzz Lnear Prograng Proble W Fuzz Relatonal Equaton Constrant

More information

1.3 Hence, calculate a formula for the force required to break the bond (i.e. the maximum value of F)

1.3 Hence, calculate a formula for the force required to break the bond (i.e. the maximum value of F) EN40: Dynacs and Vbratons Hoework 4: Work, Energy and Lnear Moentu Due Frday March 6 th School of Engneerng Brown Unversty 1. The Rydberg potental s a sple odel of atoc nteractons. It specfes the potental

More information

Quantum Particle Motion in Physical Space

Quantum Particle Motion in Physical Space Adv. Studes Theor. Phys., Vol. 8, 014, no. 1, 7-34 HIKARI Ltd, www.-hkar.co http://dx.do.org/10.1988/astp.014.311136 Quantu Partcle Moton n Physcal Space A. Yu. Saarn Dept. of Physcs, Saara State Techncal

More information

1. Statement of the problem

1. Statement of the problem Volue 14, 010 15 ON THE ITERATIVE SOUTION OF A SYSTEM OF DISCRETE TIMOSHENKO EQUATIONS Peradze J. and Tsklaur Z. I. Javakhshvl Tbls State Uversty,, Uversty St., Tbls 0186, Georga Georgan Techcal Uversty,

More information

Gadjah Mada University, Indonesia. Yogyakarta State University, Indonesia Karangmalang Yogyakarta 55281

Gadjah Mada University, Indonesia. Yogyakarta State University, Indonesia Karangmalang Yogyakarta 55281 Reducng Fuzzy Relatons of Fuzzy Te Seres odel Usng QR Factorzaton ethod and Its Applcaton to Forecastng Interest Rate of Bank Indonesa Certfcate Agus aan Abad Subanar Wdodo 3 Sasubar Saleh 4 Ph.D Student

More information

Three Algorithms for Flexible Flow-shop Scheduling

Three Algorithms for Flexible Flow-shop Scheduling Aercan Journal of Appled Scences 4 (): 887-895 2007 ISSN 546-9239 2007 Scence Publcatons Three Algorths for Flexble Flow-shop Schedulng Tzung-Pe Hong, 2 Pe-Yng Huang, 3 Gwoboa Horng and 3 Chan-Lon Wang

More information

1 Review From Last Time

1 Review From Last Time COS 5: Foundatons of Machne Learnng Rob Schapre Lecture #8 Scrbe: Monrul I Sharf Aprl 0, 2003 Revew Fro Last Te Last te, we were talkng about how to odel dstrbutons, and we had ths setup: Gven - exaples

More information

Introducing Entropy Distributions

Introducing Entropy Distributions Graubner, Schdt & Proske: Proceedngs of the 6 th Internatonal Probablstc Workshop, Darstadt 8 Introducng Entropy Dstrbutons Noel van Erp & Peter van Gelder Structural Hydraulc Engneerng and Probablstc

More information

Statistical inference for generalized Pareto distribution based on progressive Type-II censored data with random removals

Statistical inference for generalized Pareto distribution based on progressive Type-II censored data with random removals Internatonal Journal of Scentfc World, 2 1) 2014) 1-9 c Scence Publshng Corporaton www.scencepubco.com/ndex.php/ijsw do: 10.14419/jsw.v21.1780 Research Paper Statstcal nference for generalzed Pareto dstrbuton

More information

AN ANALYSIS OF A FRACTAL KINETICS CURVE OF SAVAGEAU

AN ANALYSIS OF A FRACTAL KINETICS CURVE OF SAVAGEAU AN ANALYI OF A FRACTAL KINETIC CURE OF AAGEAU by John Maloney and Jack Hedel Departent of Matheatcs Unversty of Nebraska at Oaha Oaha, Nebraska 688 Eal addresses: aloney@unoaha.edu, jhedel@unoaha.edu Runnng

More information

A new Approach for Solving Linear Ordinary Differential Equations

A new Approach for Solving Linear Ordinary Differential Equations , ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of

More information

Chapter 12 Lyes KADEM [Thermodynamics II] 2007

Chapter 12 Lyes KADEM [Thermodynamics II] 2007 Chapter 2 Lyes KDEM [Therodynacs II] 2007 Gas Mxtures In ths chapter we wll develop ethods for deternng therodynac propertes of a xture n order to apply the frst law to systes nvolvng xtures. Ths wll be

More information

Calculation of time complexity (3%)

Calculation of time complexity (3%) Problem 1. (30%) Calculaton of tme complexty (3%) Gven n ctes, usng exhaust search to see every result takes O(n!). Calculaton of tme needed to solve the problem (2%) 40 ctes:40! dfferent tours 40 add

More information

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur

Module 2. Random Processes. Version 2 ECE IIT, Kharagpur Module Random Processes Lesson 6 Functons of Random Varables After readng ths lesson, ou wll learn about cdf of functon of a random varable. Formula for determnng the pdf of a random varable. Let, X be

More information

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS BOUNDEDNESS OF THE IESZ TANSFOM WITH MATIX A WEIGHTS Introducton Let L = L ( n, be the functon space wth norm (ˆ f L = f(x C dx d < For a d d matrx valued functon W : wth W (x postve sem-defnte for all

More information

Interactive Bi-Level Multi-Objective Integer. Non-linear Programming Problem

Interactive Bi-Level Multi-Objective Integer. Non-linear Programming Problem Appled Mathematcal Scences Vol 5 0 no 65 3 33 Interactve B-Level Mult-Objectve Integer Non-lnear Programmng Problem O E Emam Department of Informaton Systems aculty of Computer Scence and nformaton Helwan

More information

The Parity of the Number of Irreducible Factors for Some Pentanomials

The Parity of the Number of Irreducible Factors for Some Pentanomials The Party of the Nuber of Irreducble Factors for Soe Pentanoals Wolfra Koepf 1, Ryul K 1 Departent of Matheatcs Unversty of Kassel, Kassel, F. R. Gerany Faculty of Matheatcs and Mechancs K Il Sung Unversty,

More information

Chapter One Mixture of Ideal Gases

Chapter One Mixture of Ideal Gases herodynacs II AA Chapter One Mxture of Ideal Gases. Coposton of a Gas Mxture: Mass and Mole Fractons o deterne the propertes of a xture, we need to now the coposton of the xture as well as the propertes

More information

Solution Thermodynamics

Solution Thermodynamics Soluton hermodynamcs usng Wagner Notaton by Stanley. Howard Department of aterals and etallurgcal Engneerng South Dakota School of nes and echnology Rapd Cty, SD 57701 January 7, 001 Soluton hermodynamcs

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

BAYESIAN AND NON BAYESIAN ESTIMATION OF ERLANG DISTRIBUTION UNDER PROGRESSIVE CENSORING

BAYESIAN AND NON BAYESIAN ESTIMATION OF ERLANG DISTRIBUTION UNDER PROGRESSIVE CENSORING www.arpapress.co/volues/volissue3/ijrras 3_8.pdf BAYESIAN AND NON BAYESIAN ESTIMATION OF ERLANG DISTRIBUTION UNDER PROGRESSIVE CENSORING R.A. Bakoban Departent of Statstcs, Scences Faculty for Grls, Kng

More information

Time and Space Complexity Reduction of a Cryptanalysis Algorithm

Time and Space Complexity Reduction of a Cryptanalysis Algorithm Te and Space Coplexty Reducton of a Cryptanalyss Algorth Mohaad Ghasezadeh Electrcal and Coputer Engneerng Departent, Yazd Unversty, Yazd, Iran.ghasezadeh@yazdun.ac.r Receved: /4/6; Accepted: /5/4 Pages:

More information

Finite Vector Space Representations Ross Bannister Data Assimilation Research Centre, Reading, UK Last updated: 2nd August 2003

Finite Vector Space Representations Ross Bannister Data Assimilation Research Centre, Reading, UK Last updated: 2nd August 2003 Fnte Vector Space epresentatons oss Bannster Data Asslaton esearch Centre, eadng, UK ast updated: 2nd August 2003 Contents What s a lnear vector space?......... 1 About ths docuent............ 2 1. Orthogonal

More information

FUZZY FINITE ELEMENT METHOD

FUZZY FINITE ELEMENT METHOD FUZZY FINITE ELEMENT METHOD RELIABILITY TRUCTURE ANALYI UING PROBABILITY 3.. Maxmum Normal tress Internal force s the shear force, V has a magntude equal to the load P and bendng moment, M. Bendng moments

More information

On the number of regions in an m-dimensional space cut by n hyperplanes

On the number of regions in an m-dimensional space cut by n hyperplanes 6 On the nuber of regons n an -densonal space cut by n hyperplanes Chungwu Ho and Seth Zeran Abstract In ths note we provde a unfor approach for the nuber of bounded regons cut by n hyperplanes n general

More information

halftoning Journal of Electronic Imaging, vol. 11, no. 4, Oct Je-Ho Lee and Jan P. Allebach

halftoning Journal of Electronic Imaging, vol. 11, no. 4, Oct Je-Ho Lee and Jan P. Allebach olorant-based drect bnary search» halftonng Journal of Electronc Iagng, vol., no. 4, Oct. 22 Je-Ho Lee and Jan P. Allebach School of Electrcal Engneerng & oputer Scence Kyungpook Natonal Unversty Abstract

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fttng of Data Davd Eberly Geoetrc Tools, LLC http://www.geoetrctools.co/ Copyrght c 1998-2014. All Rghts Reserved. Created: July 15, 1999 Last Modfed: February 9, 2008 Contents 1 Lnear Fttng

More information

An Optimal Bound for Sum of Square Roots of Special Type of Integers

An Optimal Bound for Sum of Square Roots of Special Type of Integers The Sxth Internatonal Syposu on Operatons Research and Its Applcatons ISORA 06 Xnang, Chna, August 8 12, 2006 Copyrght 2006 ORSC & APORC pp. 206 211 An Optal Bound for Su of Square Roots of Specal Type

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

The lower and upper bounds on Perron root of nonnegative irreducible matrices

The lower and upper bounds on Perron root of nonnegative irreducible matrices Journal of Computatonal Appled Mathematcs 217 (2008) 259 267 wwwelsevercom/locate/cam The lower upper bounds on Perron root of nonnegatve rreducble matrces Guang-Xn Huang a,, Feng Yn b,keguo a a College

More information

Parameters Estimation of the Modified Weibull Distribution Based on Type I Censored Samples

Parameters Estimation of the Modified Weibull Distribution Based on Type I Censored Samples Appled Mathematcal Scences, Vol. 5, 011, no. 59, 899-917 Parameters Estmaton of the Modfed Webull Dstrbuton Based on Type I Censored Samples Soufane Gasm École Supereure des Scences et Technques de Tuns

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also

More information

Chapter 8 Indicator Variables

Chapter 8 Indicator Variables Chapter 8 Indcator Varables In general, e explanatory varables n any regresson analyss are assumed to be quanttatve n nature. For example, e varables lke temperature, dstance, age etc. are quanttatve n

More information

Elastic Collisions. Definition: two point masses on which no external forces act collide without losing any energy.

Elastic Collisions. Definition: two point masses on which no external forces act collide without losing any energy. Elastc Collsons Defnton: to pont asses on hch no external forces act collde thout losng any energy v Prerequstes: θ θ collsons n one denson conservaton of oentu and energy occurs frequently n everyday

More information

Generalized Linear Methods

Generalized Linear Methods Generalzed Lnear Methods 1 Introducton In the Ensemble Methods the general dea s that usng a combnaton of several weak learner one could make a better learner. More formally, assume that we have a set

More information

LINEAR REGRESSION ANALYSIS. MODULE VIII Lecture Indicator Variables

LINEAR REGRESSION ANALYSIS. MODULE VIII Lecture Indicator Variables LINEAR REGRESSION ANALYSIS MODULE VIII Lecture - 7 Indcator Varables Dr. Shalabh Department of Maematcs and Statstcs Indan Insttute of Technology Kanpur Indcator varables versus quanttatve explanatory

More information

Special Relativity and Riemannian Geometry. Department of Mathematical Sciences

Special Relativity and Riemannian Geometry. Department of Mathematical Sciences Tutoral Letter 06//018 Specal Relatvty and Reannan Geoetry APM3713 Seester Departent of Matheatcal Scences IMPORTANT INFORMATION: Ths tutoral letter contans the solutons to Assgnent 06. BAR CODE Learn

More information

FUZZY MODEL FOR FORECASTING INTEREST RATE OF BANK INDONESIA CERTIFICATE

FUZZY MODEL FOR FORECASTING INTEREST RATE OF BANK INDONESIA CERTIFICATE he 3 rd Internatonal Conference on Quanttatve ethods ISBN 979-989 Used n Econoc and Busness. June 6-8, 00 FUZZY ODEL FOR FORECASING INERES RAE OF BANK INDONESIA CERIFICAE Agus aan Abad, Subanar, Wdodo

More information

arxiv: v2 [math.co] 3 Sep 2017

arxiv: v2 [math.co] 3 Sep 2017 On the Approxate Asyptotc Statstcal Independence of the Peranents of 0- Matrces arxv:705.0868v2 ath.co 3 Sep 207 Paul Federbush Departent of Matheatcs Unversty of Mchgan Ann Arbor, MI, 4809-043 Septeber

More information

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed (2) 4 48 Irregular vbratons n mult-mass dscrete-contnuous systems torsonally deformed Abstract In the paper rregular vbratons of dscrete-contnuous systems consstng of an arbtrary number rgd bodes connected

More information

Solving Fractional Nonlinear Fredholm Integro-differential Equations via Hybrid of Rationalized Haar Functions

Solving Fractional Nonlinear Fredholm Integro-differential Equations via Hybrid of Rationalized Haar Functions ISSN 746-7659 England UK Journal of Informaton and Computng Scence Vol. 9 No. 3 4 pp. 69-8 Solvng Fractonal Nonlnear Fredholm Integro-dfferental Equatons va Hybrd of Ratonalzed Haar Functons Yadollah Ordokhan

More information

Approximate Technique for Solving Class of Fractional Variational Problems

Approximate Technique for Solving Class of Fractional Variational Problems Appled Matheatcs, 5, 6, 837-846 Publshed Onlne May 5 n ScRes. http://www.scrp.org/journal/a http://dx.do.org/.436/a.5.6578 Approxate Technque for Solvng Class of Fractonal Varatonal Probles Ead M. Soloua,,

More information

Gradient Descent Learning and Backpropagation

Gradient Descent Learning and Backpropagation Artfcal Neural Networks (art 2) Chrstan Jacob Gradent Descent Learnng and Backpropagaton CSC 533 Wnter 200 Learnng by Gradent Descent Defnton of the Learnng roble Let us start wth the sple case of lnear

More information

Estimation: Part 2. Chapter GREG estimation

Estimation: Part 2. Chapter GREG estimation Chapter 9 Estmaton: Part 2 9. GREG estmaton In Chapter 8, we have seen that the regresson estmator s an effcent estmator when there s a lnear relatonshp between y and x. In ths chapter, we generalzed the

More information

ON THE NUMBER OF PRIMITIVE PYTHAGOREAN QUINTUPLES

ON THE NUMBER OF PRIMITIVE PYTHAGOREAN QUINTUPLES Journal of Algebra, Nuber Theory: Advances and Applcatons Volue 3, Nuber, 05, Pages 3-8 ON THE NUMBER OF PRIMITIVE PYTHAGOREAN QUINTUPLES Feldstrasse 45 CH-8004, Zürch Swtzerland e-al: whurlann@bluewn.ch

More information

Multipoint Analysis for Sibling Pairs. Biostatistics 666 Lecture 18

Multipoint Analysis for Sibling Pairs. Biostatistics 666 Lecture 18 Multpont Analyss for Sblng ars Bostatstcs 666 Lecture 8 revously Lnkage analyss wth pars of ndvduals Non-paraetrc BS Methods Maxu Lkelhood BD Based Method ossble Trangle Constrant AS Methods Covered So

More information

Credit Card Pricing and Impact of Adverse Selection

Credit Card Pricing and Impact of Adverse Selection Credt Card Prcng and Impact of Adverse Selecton Bo Huang and Lyn C. Thomas Unversty of Southampton Contents Background Aucton model of credt card solctaton - Errors n probablty of beng Good - Errors n

More information

A Hybrid Variational Iteration Method for Blasius Equation

A Hybrid Variational Iteration Method for Blasius Equation Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method

More information

Homework Notes Week 7

Homework Notes Week 7 Homework Notes Week 7 Math 4 Sprng 4 #4 (a Complete the proof n example 5 that s an nner product (the Frobenus nner product on M n n (F In the example propertes (a and (d have already been verfed so we

More information

EXACT TRAVELLING WAVE SOLUTIONS FOR THREE NONLINEAR EVOLUTION EQUATIONS BY A BERNOULLI SUB-ODE METHOD

EXACT TRAVELLING WAVE SOLUTIONS FOR THREE NONLINEAR EVOLUTION EQUATIONS BY A BERNOULLI SUB-ODE METHOD www.arpapress.co/volues/vol16issue/ijrras_16 10.pdf EXACT TRAVELLING WAVE SOLUTIONS FOR THREE NONLINEAR EVOLUTION EQUATIONS BY A BERNOULLI SUB-ODE METHOD Chengbo Tan & Qnghua Feng * School of Scence, Shandong

More information

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1 C/CS/Phy9 Problem Set 3 Solutons Out: Oct, 8 Suppose you have two qubts n some arbtrary entangled state ψ You apply the teleportaton protocol to each of the qubts separately What s the resultng state obtaned

More information

Xiangwen Li. March 8th and March 13th, 2001

Xiangwen Li. March 8th and March 13th, 2001 CS49I Approxaton Algorths The Vertex-Cover Proble Lecture Notes Xangwen L March 8th and March 3th, 00 Absolute Approxaton Gven an optzaton proble P, an algorth A s an approxaton algorth for P f, for an

More information

The Minimum Universal Cost Flow in an Infeasible Flow Network

The Minimum Universal Cost Flow in an Infeasible Flow Network Journal of Scences, Islamc Republc of Iran 17(2): 175-180 (2006) Unversty of Tehran, ISSN 1016-1104 http://jscencesutacr The Mnmum Unversal Cost Flow n an Infeasble Flow Network H Saleh Fathabad * M Bagheran

More information

Exercises of Chapter 2

Exercises of Chapter 2 Exercses of Chapter Chuang-Cheh Ln Department of Computer Scence and Informaton Engneerng, Natonal Chung Cheng Unversty, Mng-Hsung, Chay 61, Tawan. Exercse.6. Suppose that we ndependently roll two standard

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

P exp(tx) = 1 + t 2k M 2k. k N

P exp(tx) = 1 + t 2k M 2k. k N 1. Subgaussan tals Defnton. Say that a random varable X has a subgaussan dstrbuton wth scale factor σ< f P exp(tx) exp(σ 2 t 2 /2) for all real t. For example, f X s dstrbuted N(,σ 2 ) then t s subgaussan.

More information

Lecture 16 Statistical Analysis in Biomaterials Research (Part II)

Lecture 16 Statistical Analysis in Biomaterials Research (Part II) 3.051J/0.340J 1 Lecture 16 Statstcal Analyss n Bomaterals Research (Part II) C. F Dstrbuton Allows comparson of varablty of behavor between populatons usng test of hypothess: σ x = σ x amed for Brtsh statstcan

More information

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration

Managing Capacity Through Reward Programs. on-line companion page. Byung-Do Kim Seoul National University College of Business Administration Managng Caacty Through eward Programs on-lne comanon age Byung-Do Km Seoul Natonal Unversty College of Busness Admnstraton Mengze Sh Unversty of Toronto otman School of Management Toronto ON M5S E6 Canada

More information

= m 1. sin π( ai z ) )

= m 1. sin π( ai z ) ) EXACT COVERING SYSTEMS AND THE GAUSS-LEGENDRE MULTIPLICATION FORMULA FOR THE GAMMA FUNCTION John Beeee Unversty of Alaska Anchorage July 0 199 The Gauss-Legendre ultplcaton forula for the gaa functon s

More information

Differentiating Gaussian Processes

Differentiating Gaussian Processes Dfferentatng Gaussan Processes Andrew McHutchon Aprl 17, 013 1 Frst Order Dervatve of the Posteror Mean The posteror mean of a GP s gven by, f = x, X KX, X 1 y x, X α 1 Only the x, X term depends on the

More information