Technical Report: A Unified Framework for Analysis of Path Selection Based Decode-and-Forward (DF) Cooperation in Wireless Systems

Μέγεθος: px
Εμφάνιση ξεκινά από τη σελίδα:

Download "Technical Report: A Unified Framework for Analysis of Path Selection Based Decode-and-Forward (DF) Cooperation in Wireless Systems"

Transcript

1 Techncal Report: A Unfed Framework for Analyss of ath Selecton Based Decode-and-Forward DF Cooperaton n Wreless Systems Neeraj Varshney Student ember, IEEE and Adtya K. Jagannatham, ember, IEEE I. VALUES OF ARAETERS t AND a, {SR, SD, RD} FOR DIFFERENT FADING CHANNELS The values of parameters t and a, {SR, SD, RD} for varous fadng channels ncludng η µ and κ µ are shown n Table I. II. SILIFICATION OF THE ROBABILITY OF ERROR FOR THE EVENT ϕ IN 6 Usng the result for F γmn x = F γsr x + F γrd x F γsr xf γrd x from Eq5,, the resson for re ϕ n 6 n the man paper can be rewrtten as, re ϕ= = γsd re ϕ, γ SD F γmn f γsd γ SD dγ SD, α γsd γsd re ϕ, γ SD F γsr f γsd γ SD dγ SD + re ϕ, γ SD F γrd f γsd γ SD dγ SD α α γsd γsd re ϕ, γ SD F γsr F γrd f γsd γ SD dγ SD, α α Substtutng the ressons for F γ x, {SD, SR, RD}, f γsd x gven n, 3 respectvely n the man paper and usng re ϕ, γ SD = π dθ 3, yelds π sn π/γ SD sn θ DRAFT

2 Fadng Channel DF fβ t a Raylegh β δ δ δ Nakagam-m, m Generalzed Nakagam Nakagam-q, q Nakagam-n Webull, c Log-Normal, σ Shadowed-Rcan, b, m, Ω κ-µ dstrbuton η-µ dstrbuton Gamma-Gamma, µ, ν, η s β m s p m +n δ Γm c s β +q qδ n Γ+ c.5 b µ +κ µ κ m m β m mβ δ m Γm p, where p = +q β +n β δ 4q δ δ c/ β c bm bm+ω µ + β δ δ Γm Γm +s I q 4 β I n β m s, s >, m m s 4q δ +n β δ δ Γ + c 4.34 πσβ log βµ σ µ µ κ δ µ + πµ µ + h µ βµ Γµ H µ δ µ +, n c/ m β.5ω b F m, ; β b m+bω I µ µ +κ β δ µ h β δ I µ +η µ κ +κ β δ µ H β For format : < η <, h = +η, H 4 = η For format : < η <, h =, H η = η k= ζ k ν, µβ ν+k + k= ζ k µ, νβ µ+k where ζ k a, b = δ +n δ c c µ σ µ, µ η 4 η πab a+k η a+k snbaπk!γaγbγab+k+ f ν < µ then t gg = ν/ and t gg = ζ ν, µ f ν > µ then t gg = µ/ and t gg = ζ µ, ν TABLE I m m δ m Γm s p m Γm +q qδ n Γ+ c c δ 4.34 πσ µ σ m.5 b bm bm+ω µ +κ µ µ κ δ µ Γµ πµ µ h µ Γµ Γµ +.5δ µ, t gg a gg VALUES OF ARAETERS t AND a, {SR, SD, RD} FOR DIFFERENT FADING CHANNELS. the bound for re ϕ as, re ϕ π + π a RD a SD t RD + α t RD+ a SR a SD t SR +α t SR+ η tsd + η a SR a RD a η SD t SR +t RD +α t SR+t RD + tsr + η trd + η tsd + tsd + γ t RD+t SD + SD tsr + trd + η η γ t SR+t SD + SD sn π/γ SD sn θ sn π/γ SD sn θ γ τ SD sn π/γ SD sn θ dγ SD dγ SD dγ SD where τ = t SD + t SR + t RD +. The resson above can be smplfed usng the dentty x n µx = n!µ n 3.36-, 4 followed by gnorng the negatve term n the resultng resson to yeld the bound n 8 n the man paper as, re ϕ a SRa SD Γt SR + t SD + ζt SR + t SD + t SR + α t SR+ sn π/ t SR +t SD + η tsr + η tsd + dθ,

3 + a trd + RDa SD Γt RD + t SD + ζt RD + t SD + t RD + α t RD+ sn π/ η η tsd + t RD +t SD +. III. SILIFICATION OF THE ROBABILITY OF ERROR FOR THE EVENT ϕ IN Usng the result for f γmn x = f γsr x + f γrd x F γsr xf γrd x f γsr xf γrd x from Eq5,, the resson for re ϕ n n the man paper can be rewrtten as, re ϕ = π = π + π π sn π/γ mn γ mn = sn F γsd αγ mn f γmn γ mn dγ mn dθ, θ sn π/γ mn sn F γsd αγ mn f γsr γ mn dγ mn θ sn π/γ mn sn θ sn π/γ mn sn θ sn π/γ mn sn θ F γsd αγ mn f γrd γ mn dγ mn F γsd αγ mn F γsr γ mn f γrd γ mn dγ mn F γsd αγ mn f γsr γ mn F γrd γ mn dγ mn dθ. 3 Usng the ressons for F γ x, f γ x, {SD, SR, RD} gven n, 3 respectvely n the man paper, the above resson can be smplfed as, re ϕ π π + a SDa RD α t SD+ t SD + a SD a SR α t SD+ t SD + a SDa SR a RD α t SD+ η t SD + t SR + a SDa SR a RD α t SD+ t SD + t RD + η tsd + η η η tsd + η tsd + η tsd + η trd + tsr + tsr + trd + η γ t SD+t SR + mn γ t SD+t RD + mn tsr + trd + η sn π/γ mn sn θ sn π/γ mn sn θ dγ mn γmn τ sn π/γ mn sn dγ mn θ dγ mn γ τ mn sn π/γ mn sn θ The resson above can be further smplfed usng the dentty x n µx = n!µ n 3.36-, 4 followed by gnorng the negatve term n the resultng resson to yeld the dγ mn dθ.

4 bound n n the man paper as, re ϕ a SRa SD Γt SR + t SD + ζt SR + t SD + α t SD+ t SD + sn π/ t SR +t SD + η + a RDa SD Γt RD + t SD + ζt RD + t SD + α t SD+ t SD + sn π/ t RD +t SD + tsr + η η tsd + trd + η tsd +. 4 IV. IO-OSTBC BASED COOERATION WITH ATH SELECTION The ressons for the SER and dversty order n the IO-OSTBC based cooperatve system can be readly obtaned by substtutng Ns N Ns R c m d m SD SD a SD =, t N s N d m SD! δsd SD = N s N d m SD, Ns N Ns R c m r m SR SR a SR =, t SR = N s N r m SR, N s N r m SR! and δ SR Nr R c m Nr N RD d m RD, a RD = trd = N r N d m RD, N r N d m RD! δ RD n equatons 4, 5 gven n the man paper respectvely as, e Θ Ns N ζn s N d m SD +N s N r m SR r m SR η η NsNd m SD sn π/ NsN dm SD +N sn rm SR ΓN s N r m SR +N s N d m SD N s N r m SR α N sn r + αnsndmsd m SR N s N d m SD + Θ Nr N ζn s N d m SD +N r N d m RD d m RD η η Ns N d m SD sn π/ N sn d m SD +N r N d m RD ΓN r N d m RD +N s N d m SD + αnsndmsd, 5 N r N d m RD α N rn d m RD N s N d m SD d ath,ostbc =N s N d m SD + mn{n s N r m SR, N r N d m RD }, 6 where Θ = a SD a SR = N sn d m SD!N sn rm SR! Θ = a SD a RD = N s N d m SD!N r N d m RD! N s R c m SD δ SD N s R c m SD δsd Ns N d m SD Ns N d m SD N s R c m SR δsr Nr N d m N r R c m RD RD. δrd Ns N r m SR and Further, the optmal power for ths system can be obtaned by usng the polynomal equaton gven below C t SR+ C t RD+ =, 7

5 where C and C are gven as, C = ζn sn d m SD +N r N d m RD ΓN s N d m SD +N r N d m RD N r N d m RD η N rn d m RD sn π/ NrN dm RD Nr R c m Nr N RD d m RD, N r N d m RD! δ RD C = ζn sn d m SD + N s N r m SR ΓN s N d m SD + N s N r m SR N s N r m SR η N sn r m SR sn π/ N sn r m SR Ns N Ns R c m r m SR SR. N s N r m SR! δ SR V. GENERALIZED ANALYSIS FOR JOINT TRANSIT-RECEIVE ANTENNA AND ATH SELECTION JTRAS and Smlar to the IO-OSTBC based cooperaton, usng the values a SD = N sn d m SD /δsd m SDN s N d Γm SD + N sn d m SD!, t SD = m SD N d N s, a SR = N sn r m SR /δsr m SRN s N r Γm SR + NsNr m SR!, t SR = m SR N s N r, a RD = N rn d m RD /δrd m RDN r N d Γm RD + N rn d m RD!, t RD = m RD N d N r, derved n the man paper for the JTRAS based system, the closed form ressons for the asymptotc SER and dversty order n JTRAS based cooperaton are gven by, e Θ ζn s N d m SD +N s N r m SR sn π/ NsN dm SD +N sn rm SR ΓN s N r m SR +N s N d m SD η + Θ ζn s N d m SD +N r N d m RD sn π/ NsN dm SD +N rn d m RD ΓN r N d m RD +N s N d m SD NsNrm SR η Ns N d m SD N s N r m SR α NsNrm SR η + αn sn d m SD N s N d m SD Nr N d m RD η NsNd m SD N r N d m RD α N rn d m RD + αnsndmsd N s N d m SD, 8 d ath,jtras =N s N d m SD + mn{n s N r m SR, N r N d m RD }, 9

6 Ns where Θ = a SD a SR = N rn d m SD /δsd m SD NsN dm SR /δsr m SR N snr Γm SD + N sn d and Θ m SD!Γm SR + NsNr m SR! = a SD a RD = N s N r Nd m SD/δSD m SD N sn dmrd /δrd m RD N rn d Γm SD + N sn d m SD!Γm RD + N rn d. oreover, the optmal power for the JTRAS m RD! system can be obtaned by usng the equaton 7, where C and C are defned as, C = ζn sn d m SD +N r N d m RD ΓN s N d m SD +N r N d m RD N r N d m RD η NrN dm RD sn π/ N rn d m RD N r N d m RD /δrd m RDN r N d Γm RD + NrN d m RD!, C = ζn sn d m SD + N s N r m SR ΓN s N d m SD + N s N r m SR N s N r m SR η NsNrm SR sn π/ N sn r m SR N s N r m SR /δsr m SRN s N r Γm SR + NsNr m SR!. VI. ADDITIONAL SIULATION RESULTS In order to demonstrate the system performance for hgher order SK modulaton schemes, we consder a path selecton based SISO system n whch each lnk erence Nakagam-m fadng wth severty parameters m SR = m RD =, m SD = and average channel gans δsr =, δ SD = δ RD =.. From Fg., t can be observed that the monte-carlo results obtaned for the hgher order SK modulaton closely match wth the asymptotc SER approxmaton n 4 gven n man paper, whch clearly valdates that the analytcal framework developed n ths work s applcable for a general -SK modulaton. It can also be noted that the system performance sgnfcantly degrades as the order or the number of constellaton ponts ncreases. However, the system acheves the dentcal dversty order of t SD +mn{t SR +t RD }+ = m SD +mn{m SR, m RD } = 3 for each modulaton scheme. 6SK SER 3 4SK or QSK 8SK 4 5 SISO, =.773, =.87 Optmal SISO, =.5, =.5 Equal Asymptotc Bound Optmal, Analytcal Asymptotc Bound Equal, Analytcal SNRdB Fg.. SER erformance of path selecton based SISO system correspondng to the transmsson of QSK or 4-SK, 8-SK, and 6-SK modulated symbols.

7 On the other hand, Fg shows that the value of cooperaton threshold α also affects the system performance. It can be clearly seen n Fg. that the end-to-end system performance sgnfcantly mproves as the cooperaton threshold α ncreases. Therefore, one can note that n addton to power allocaton, the value of cooperaton threshold α also plays a key role, whch can also be optmzed to enhance the end-to-end performance of the path selecton scheme. SER 3 4 α=.,.5, 5 SISO, =.5, =.5 Equal Asymptotc Bound Equal, Analytcal SNRdB Fg.. SER erformance of path selecton based SISO system for dfferent values of cooperaton threshold α. REFERENCES. D. Yacoub, The κ-µ dstrbuton and the η-µ dstrbuton, IEEE Antennas and ropagaton agazne, vol. 49, no., pp. 68 8, 7. N. Varshney, V. Krshna, and A. Jagannatham, Capacty analyss for path selecton based DF IO-STBC cooperatve wreless systems, IEEE Communcatons Letters, vol. 8, no., pp , 4. 3 K. R. Lu, Cooperatve communcatons and networkng. Cambrdge Unversty ress, 9. 4 A. Jeffrey and D. Zwllnger, Table of ntegrals, seres, and products. Access Onlne va Elsever, 7.

α & β spatial orbitals in

α & β spatial orbitals in The atrx Hartree-Fock equatons The most common method of solvng the Hartree-Fock equatons f the spatal btals s to expand them n terms of known functons, { χ µ } µ= consder the spn-unrestrcted case. We

Διαβάστε περισσότερα

Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών. ΗΥ-570: Στατιστική Επεξεργασία Σήµατος. ιδάσκων : Α. Μουχτάρης. εύτερη Σειρά Ασκήσεων.

Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών. ΗΥ-570: Στατιστική Επεξεργασία Σήµατος. ιδάσκων : Α. Μουχτάρης. εύτερη Σειρά Ασκήσεων. Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 2015 ιδάσκων : Α. Μουχτάρης εύτερη Σειρά Ασκήσεων Λύσεις Ασκηση 1. 1. Consder the gven expresson for R 1/2 : R 1/2

Διαβάστε περισσότερα

EE512: Error Control Coding

EE512: Error Control Coding EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3

Διαβάστε περισσότερα

One and two particle density matrices for single determinant HF wavefunctions. (1) = φ 2. )β(1) ( ) ) + β(1)β * β. (1)ρ RHF

One and two particle density matrices for single determinant HF wavefunctions. (1) = φ 2. )β(1) ( ) ) + β(1)β * β. (1)ρ RHF One and two partcle densty matrces for sngle determnant HF wavefunctons One partcle densty matrx Gven the Hartree-Fock wavefuncton ψ (,,3,!, = Âϕ (ϕ (ϕ (3!ϕ ( 3 The electronc energy s ψ H ψ = ϕ ( f ( ϕ

Διαβάστε περισσότερα

5 Haar, R. Haar,. Antonads 994, Dogaru & Carn Kerkyacharan & Pcard 996. : Haar. Haar, y r x f rt xβ r + ε r x β r + mr k β r k ψ kx + ε r x, r,.. x [,

5 Haar, R. Haar,. Antonads 994, Dogaru & Carn Kerkyacharan & Pcard 996. : Haar. Haar, y r x f rt xβ r + ε r x β r + mr k β r k ψ kx + ε r x, r,.. x [, 4 Chnese Journal of Appled Probablty and Statstcs Vol.6 No. Apr. Haar,, 6,, 34 E-,,, 34 Haar.., D-, A- Q-,. :, Haar,. : O.6..,..,.. Herzberg & Traves 994, Oyet & Wens, Oyet Tan & Herzberg 6, 7. Haar Haar.,

Διαβάστε περισσότερα

Multi-dimensional Central Limit Theorem

Multi-dimensional Central Limit Theorem Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t ();

Διαβάστε περισσότερα

Multi-dimensional Central Limit Theorem

Multi-dimensional Central Limit Theorem Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t tme

Διαβάστε περισσότερα

Generalized Fibonacci-Like Polynomial and its. Determinantal Identities

Generalized Fibonacci-Like Polynomial and its. Determinantal Identities Int. J. Contemp. Math. Scences, Vol. 7, 01, no. 9, 1415-140 Generalzed Fbonacc-Le Polynomal and ts Determnantal Identtes V. K. Gupta 1, Yashwant K. Panwar and Ompraash Shwal 3 1 Department of Mathematcs,

Διαβάστε περισσότερα

Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee

Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee Appendi to On the stability of a compressible aisymmetric rotating flow in a pipe By Z. Rusak & J. H. Lee Journal of Fluid Mechanics, vol. 5 4, pp. 5 4 This material has not been copy-edited or typeset

Διαβάστε περισσότερα

Second Order RLC Filters

Second Order RLC Filters ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor

Διαβάστε περισσότερα

ΠΤΥΧΙΑΚΗ/ ΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ

ΠΤΥΧΙΑΚΗ/ ΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ ΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΣΧΟΛΗ ΘΕΤΙΚΩΝ ΕΠΙΣΤΗΜΩΝ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ ΠΤΥΧΙΑΚΗ/ ΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ «ΚΛΑ ΕΜΑ ΟΜΑ ΑΣ ΚΑΤΑ ΠΕΡΙΠΤΩΣΗ ΜΕΣΩ ΤΑΞΙΝΟΜΗΣΗΣ ΠΟΛΛΑΠΛΩΝ ΕΤΙΚΕΤΩΝ» (Instance-Based Ensemble

Διαβάστε περισσότερα

Power allocation under per-antenna power constraints in multiuser MIMO systems

Power allocation under per-antenna power constraints in multiuser MIMO systems 33 0 Vol.33 No. 0 0 0 Journal on Councatons October 0 do:0.3969/.ssn.000-436x.0.0.009 IO 009 IO IO N94 A 000-436X(0)0-007-06 Power allocaton under er-antenna ower constrants n ultuser IO systes HAN Sheng-qan,

Διαβάστε περισσότερα

Other Test Constructions: Likelihood Ratio & Bayes Tests

Other Test Constructions: Likelihood Ratio & Bayes Tests Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :

Διαβάστε περισσότερα

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =

Διαβάστε περισσότερα

2 Composition. Invertible Mappings

2 Composition. Invertible Mappings Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,

Διαβάστε περισσότερα

Math 6 SL Probability Distributions Practice Test Mark Scheme

Math 6 SL Probability Distributions Practice Test Mark Scheme Math 6 SL Probability Distributions Practice Test Mark Scheme. (a) Note: Award A for vertical line to right of mean, A for shading to right of their vertical line. AA N (b) evidence of recognizing symmetry

Διαβάστε περισσότερα

Approximation of distance between locations on earth given by latitude and longitude

Approximation of distance between locations on earth given by latitude and longitude Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth

Διαβάστε περισσότερα

Concomitants of Dual Generalized Order Statistics from Bivariate Burr III Distribution

Concomitants of Dual Generalized Order Statistics from Bivariate Burr III Distribution Journal of Statstcal Theory and Applcatons, Vol. 4, No. 3 September 5, 4-56 Concomtants of Dual Generalzed Order Statstcs from Bvarate Burr III Dstrbuton Haseeb Athar, Nayabuddn and Zuber Akhter Department

Διαβάστε περισσότερα

8.1 The Nature of Heteroskedasticity 8.2 Using the Least Squares Estimator 8.3 The Generalized Least Squares Estimator 8.

8.1 The Nature of Heteroskedasticity 8.2 Using the Least Squares Estimator 8.3 The Generalized Least Squares Estimator 8. 8.1 The Nature of Heteroskedastcty 8. Usng the Least Squares Estmator 8.3 The Generalzed Least Squares Estmator 8.4 Detectng Heteroskedastcty E( y) = β+β 1 x e = y E( y ) = y β β x 1 y = β+β x + e 1 Fgure

Διαβάστε περισσότερα

A Sequential Experimental Design based on Bayesian Statistics for Online Automatic Tuning. Reiji SUDA,

A Sequential Experimental Design based on Bayesian Statistics for Online Automatic Tuning. Reiji SUDA, Bayes, Bayes mult-armed bandt problem Bayes A Sequental Expermental Desgn based on Bayesan Statstcs for Onlne Automatc Tunng Re SUDA, Ths paper proposes to use Bayesan statstcs for software automatc tunng

Διαβάστε περισσότερα

ST5224: Advanced Statistical Theory II

ST5224: Advanced Statistical Theory II ST5224: Advanced Statistical Theory II 2014/2015: Semester II Tutorial 7 1. Let X be a sample from a population P and consider testing hypotheses H 0 : P = P 0 versus H 1 : P = P 1, where P j is a known

Διαβάστε περισσότερα

Figure A.2: MPC and MPCP Age Profiles (estimating ρ, ρ = 2, φ = 0.03)..

Figure A.2: MPC and MPCP Age Profiles (estimating ρ, ρ = 2, φ = 0.03).. Supplemental Material (not for publication) Persistent vs. Permanent Income Shocks in the Buffer-Stock Model Jeppe Druedahl Thomas H. Jørgensen May, A Additional Figures and Tables Figure A.: Wealth and

Διαβάστε περισσότερα

A Class of Orthohomological Triangles

A Class of Orthohomological Triangles A Class of Orthohomologcal Trangles Prof. Claudu Coandă Natonal College Carol I Craova Romana. Prof. Florentn Smarandache Unversty of New Mexco Gallup USA Prof. Ion Pătraşcu Natonal College Fraţ Buzeşt

Διαβάστε περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr (T t N n) Pr (max (X 1,..., X N ) t N n) Pr (max

Διαβάστε περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr T t N n) Pr max X 1,..., X N ) t N n) Pr max

Διαβάστε περισσότερα

ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ

ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΓΕΝΙΚΕΣ ΠΑΡΑΤΗΡΗΣΕΙΣ ΕΠΙΔΡΑΣΗ Μ.Β ΣΤΙΣ ΙΔΙΟΤΗΤΕΣ ΠΟΛΥΜΕΡΩΝ ΜΑΘΗΜΑΤΙΚΗ ΠΕΡΙΓΡΑΦΗ ΤΗΣ ΚΑΤΑΝΟΜΗΣ ΜΟΡΙΑΚΟΥ ΒΑΡΟΥΣ ΣΥΝΑΡΤΗΣΗ ΠΙΘΑΝΟΤΗΤΟΣ (ΔΙΑΦΟΡΙΚΗ) Probablty Densty Functon

Διαβάστε περισσότερα

Math221: HW# 1 solutions

Math221: HW# 1 solutions Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin

Διαβάστε περισσότερα

Derivation for Input of Factor Graph Representation

Derivation for Input of Factor Graph Representation Dervaton for Input of actor Graph Representaton Sum-Product Prmal Based on the orgnal LP formulaton b x θ x + b θ,x, s.t., b, b,, N, x \ b x = b we defne V as the node set allocated to the th core. { V

Διαβάστε περισσότερα

6.1. Dirac Equation. Hamiltonian. Dirac Eq.

6.1. Dirac Equation. Hamiltonian. Dirac Eq. 6.1. Dirac Equation Ref: M.Kaku, Quantum Field Theory, Oxford Univ Press (1993) η μν = η μν = diag(1, -1, -1, -1) p 0 = p 0 p = p i = -p i p μ p μ = p 0 p 0 + p i p i = E c 2 - p 2 = (m c) 2 H = c p 2

Διαβάστε περισσότερα

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ting Zhang Stanford May 11, 2001 Stanford, 5/11/2001 1 Outline Ordinal Classification Ordinal Addition Ordinal Multiplication Ordinal

Διαβάστε περισσότερα

ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ

ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΓΕΝΙΚΕΣ ΠΑΡΑΤΗΡΗΣΕΙΣ ΕΠΙ ΡΑΣΗ Μ.Β ΣΤΙΣ Ι ΙΟΤΗΤΕΣ ΠΟΛΥΜΕΡΩΝ ΜΑΘΗΜΑΤΙΚΗ ΠΕΡΙΓΡΑΦΗ ΤΗΣ ΚΑΤΑΝΟΜΗΣ ΜΟΡΙΑΚΟΥ ΒΑΡΟΥΣ ΣΥΝΑΡΤΗΣΗ ΠΙΘΑΝΟΤΗΤΟΣ ( ΙΑΦΟΡΙΚΗ) Probablty Densty Functon

Διαβάστε περισσότερα

Proposal of Terminal Self Location Estimation Method to Consider Wireless Sensor Network Environment

Proposal of Terminal Self Location Estimation Method to Consider Wireless Sensor Network Environment 1 2 2 GPS (SOM) Proposal of Termnal Self Locaton Estmaton Method to Consder Wreless Sensor Network Envronment Shohe OHNO, 1 Naotosh ADACHI 2 and Yasuhsa TAKIZAWA 2 Recently, large scale wreless sensor

Διαβάστε περισσότερα

ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ

ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΕΛΕΝΑ ΦΛΟΚΑ Επίκουρος Καθηγήτρια Τµήµα Φυσικής, Τοµέας Φυσικής Περιβάλλοντος- Μετεωρολογίας ΓΕΝΙΚΟΙ ΟΡΙΣΜΟΙ Πληθυσµός Σύνολο ατόµων ή αντικειµένων στα οποία αναφέρονται

Διαβάστε περισσότερα

Vol. 34 ( 2014 ) No. 4. J. of Math. (PRC) : A : (2014) Frank-Wolfe [7],. Frank-Wolfe, ( ).

Vol. 34 ( 2014 ) No. 4. J. of Math. (PRC) : A : (2014) Frank-Wolfe [7],. Frank-Wolfe, ( ). Vol. 4 ( 214 ) No. 4 J. of Math. (PRC) 1,2, 1 (1., 472) (2., 714) :.,.,,,..,. : ; ; ; MR(21) : 9B2 : : A : 255-7797(214)4-759-7 1,,,,, [1 ].,, [4 6],, Frank-Wolfe, Frank-Wolfe [7],.,,.,,,., UE,, UE. O-D,,,,,

Διαβάστε περισσότερα

Duals of the QCQP and SDP Sparse SVM. Antoni B. Chan, Nuno Vasconcelos, and Gert R. G. Lanckriet

Duals of the QCQP and SDP Sparse SVM. Antoni B. Chan, Nuno Vasconcelos, and Gert R. G. Lanckriet Duals of the QCQP and SDP Sparse SVM Anton B. Chan, Nuno Vasconcelos, and Gert R. G. Lanckret SVCL-TR 007-0 v Aprl 007 Duals of the QCQP and SDP Sparse SVM Anton B. Chan, Nuno Vasconcelos, and Gert R.

Διαβάστε περισσότερα

LECTURE 4 : ARMA PROCESSES

LECTURE 4 : ARMA PROCESSES LECTURE 4 : ARMA PROCESSES Movng-Average Processes The MA(q) process, s defned by (53) y(t) =µ ε(t)+µ 1 ε(t 1) + +µ q ε(t q) =µ(l)ε(t), where µ(l) =µ +µ 1 L+ +µ q L q and where ε(t) s whte nose An MA model

Διαβάστε περισσότερα

Homework 3 Solutions

Homework 3 Solutions Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For

Διαβάστε περισσότερα

Finite Field Problems: Solutions

Finite Field Problems: Solutions Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The

Διαβάστε περισσότερα

5.4 The Poisson Distribution.

5.4 The Poisson Distribution. The worst thing you can do about a situation is nothing. Sr. O Shea Jackson 5.4 The Poisson Distribution. Description of the Poisson Distribution Discrete probability distribution. The random variable

Διαβάστε περισσότερα

Variance of Trait in an Inbred Population. Variance of Trait in an Inbred Population

Variance of Trait in an Inbred Population. Variance of Trait in an Inbred Population Varance of Trat n an Inbred Populaton Varance of Trat n an Inbred Populaton Varance of Trat n an Inbred Populaton Revew of Mean Trat Value n Inbred Populatons We showed n the last lecture that for a populaton

Διαβάστε περισσότερα

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ. Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο The time integral of a force is referred to as impulse, is determined by and is obtained from: Newton s 2 nd Law of motion states that the action

Διαβάστε περισσότερα

Constant Elasticity of Substitution in Applied General Equilibrium

Constant Elasticity of Substitution in Applied General Equilibrium Constant Elastct of Substtuton n Appled General Equlbru The choce of nput levels that nze the cost of producton for an set of nput prces and a fed level of producton can be epressed as n sty.. f Ltng for

Διαβάστε περισσότερα

Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------

Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- ----------------- Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin

Διαβάστε περισσότερα

Symplecticity of the Störmer-Verlet algorithm for coupling between the shallow water equations and horizontal vehicle motion

Symplecticity of the Störmer-Verlet algorithm for coupling between the shallow water equations and horizontal vehicle motion Symplectcty of the Störmer-Verlet algorthm for couplng between the shallow water equatons and horzontal vehcle moton by H. Alem Ardakan & T. J. Brdges Department of Mathematcs, Unversty of Surrey, Guldford

Διαβάστε περισσότερα

Neutralino contributions to Dark Matter, LHC and future Linear Collider searches

Neutralino contributions to Dark Matter, LHC and future Linear Collider searches Neutralno contrbutons to Dark Matter, LHC and future Lnear Collder searches G.J. Gounars Unversty of Thessalonk, Collaboraton wth J. Layssac, P.I. Porfyrads, F.M. Renard and wth Th. Dakonds for the γz

Διαβάστε περισσότερα

1 Complete Set of Grassmann States

1 Complete Set of Grassmann States Physcs 610 Homework 8 Solutons 1 Complete Set of Grassmann States For Θ, Θ, Θ, Θ each ndependent n-member sets of Grassmann varables, and usng the summaton conventon ΘΘ Θ Θ Θ Θ, prove the dentty e ΘΘ dθ

Διαβάστε περισσότερα

CHAPTER 101 FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD

CHAPTER 101 FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD CHAPTER FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD EXERCISE 36 Page 66. Determine the Fourier series for the periodic function: f(x), when x +, when x which is periodic outside this rge of period.

Διαβάστε περισσότερα

8.324 Relativistic Quantum Field Theory II

8.324 Relativistic Quantum Field Theory II Lecture 8.3 Relatvstc Quantum Feld Theory II Fall 00 8.3 Relatvstc Quantum Feld Theory II MIT OpenCourseWare Lecture Notes Hon Lu, Fall 00 Lecture 5.: RENORMALIZATION GROUP FLOW Consder the bare acton

Διαβάστε περισσότερα

MathCity.org Merging man and maths

MathCity.org Merging man and maths MathCity.org Merging man and maths Exercise 10. (s) Page Textbook of Algebra and Trigonometry for Class XI Available online @, Version:.0 Question # 1 Find the values of sin, and tan when: 1 π (i) (ii)

Διαβάστε περισσότερα

Every set of first-order formulas is equivalent to an independent set

Every set of first-order formulas is equivalent to an independent set Every set of first-order formulas is equivalent to an independent set May 6, 2008 Abstract A set of first-order formulas, whatever the cardinality of the set of symbols, is equivalent to an independent

Διαβάστε περισσότερα

Supplementary Materials for Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection

Supplementary Materials for Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. XX, NO. X, XXXX XXXX Supplementary Materials for Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation

Διαβάστε περισσότερα

The Simply Typed Lambda Calculus

The Simply Typed Lambda Calculus Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and

Διαβάστε περισσότερα

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013 Notes on Average Scattering imes and Hall Factors Jesse Maassen and Mar Lundstrom Purdue University November 5, 13 I. Introduction 1 II. Solution of the BE 1 III. Exercises: Woring out average scattering

Διαβάστε περισσότερα

6.3 Forecasting ARMA processes

6.3 Forecasting ARMA processes 122 CHAPTER 6. ARMA MODELS 6.3 Forecasting ARMA processes The purpose of forecasting is to predict future values of a TS based on the data collected to the present. In this section we will discuss a linear

Διαβάστε περισσότερα

Generalized Linear Model [GLM]

Generalized Linear Model [GLM] Generalzed Lnear Model [GLM]. ก. ก Emal: nkom@kku.ac.th A Lttle Hstory Multple lnear regresson normal dstrbuton & dentty lnk (Legendre, Guass: early 19th century). ANOVA normal dstrbuton & dentty lnk (Fsher:

Διαβάστε περισσότερα

Overview. Transition Semantics. Configurations and the transition relation. Executions and computation

Overview. Transition Semantics. Configurations and the transition relation. Executions and computation Overview Transition Semantics Configurations and the transition relation Executions and computation Inference rules for small-step structural operational semantics for the simple imperative language Transition

Διαβάστε περισσότερα

Problem Set 3: Solutions

Problem Set 3: Solutions CMPSCI 69GG Applied Information Theory Fall 006 Problem Set 3: Solutions. [Cover and Thomas 7.] a Define the following notation, C I p xx; Y max X; Y C I p xx; Ỹ max I X; Ỹ We would like to show that C

Διαβάστε περισσότερα

CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS

CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS EXERCISE 01 Page 545 1. Use matrices to solve: 3x + 4y x + 5y + 7 3x + 4y x + 5y 7 Hence, 3 4 x 0 5 y 7 The inverse of 3 4 5 is: 1 5 4 1 5 4 15 8 3

Διαβάστε περισσότερα

1 String with massive end-points

1 String with massive end-points 1 String with massive end-points Πρόβλημα 5.11:Θεωρείστε μια χορδή μήκους, τάσης T, με δύο σημειακά σωματίδια στα άκρα της, το ένα μάζας m, και το άλλο μάζας m. α) Μελετώντας την κίνηση των άκρων βρείτε

Διαβάστε περισσότερα

Partial Trace and Partial Transpose

Partial Trace and Partial Transpose Partial Trace and Partial Transpose by José Luis Gómez-Muñoz http://homepage.cem.itesm.mx/lgomez/quantum/ jose.luis.gomez@itesm.mx This document is based on suggestions by Anirban Das Introduction This

Διαβάστε περισσότερα

Example Sheet 3 Solutions

Example Sheet 3 Solutions Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note

Διαβάστε περισσότερα

Noriyasu MASUMOTO, Waseda University, Okubo, Shinjuku, Tokyo , Japan Hiroshi YAMAKAWA, Waseda University

Noriyasu MASUMOTO, Waseda University, Okubo, Shinjuku, Tokyo , Japan Hiroshi YAMAKAWA, Waseda University A Study on Predctve Control Usng a Short-Term Predcton Method Based on Chaos Theory (Predctve Control of Nonlnear Systems Usng Plural Predcted Dsturbance Values) Noryasu MASUMOTO, Waseda Unversty, 3-4-1

Διαβάστε περισσότερα

Potential Dividers. 46 minutes. 46 marks. Page 1 of 11

Potential Dividers. 46 minutes. 46 marks. Page 1 of 11 Potential Dividers 46 minutes 46 marks Page 1 of 11 Q1. In the circuit shown in the figure below, the battery, of negligible internal resistance, has an emf of 30 V. The pd across the lamp is 6.0 V and

Διαβάστε περισσότερα

Solution Series 9. i=1 x i and i=1 x i.

Solution Series 9. i=1 x i and i=1 x i. Lecturer: Prof. Dr. Mete SONER Coordinator: Yilin WANG Solution Series 9 Q1. Let α, β >, the p.d.f. of a beta distribution with parameters α and β is { Γ(α+β) Γ(α)Γ(β) f(x α, β) xα 1 (1 x) β 1 for < x

Διαβάστε περισσότερα

DESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.

DESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0. DESIGN OF MACHINERY SOLUTION MANUAL -7-1! PROBLEM -7 Statement: Design a double-dwell cam to move a follower from to 25 6, dwell for 12, fall 25 and dwell for the remader The total cycle must take 4 sec

Διαβάστε περισσότερα

[1], [2] - (Danfoss, Rexroth, Char-Lynn. [3, 4, 5]), .. [6]. [7]

[1], [2] - (Danfoss, Rexroth, Char-Lynn. [3, 4, 5]), .. [6]. [7] OTROL. COISSION OF OTORIZATION AND ENERGETICS IN AGRICULTURE 0, Vol. 6, No. 5, 87 98 -,,, 008,.,., e-mal: mosgv@ukr.net. -,... -. :, -,. [],,.,,.., []. - (Danoss, Rexroth, Char-Lynn. [,, 5]),. -,.. [6]..,

Διαβάστε περισσότερα

derivation of the Laplacian from rectangular to spherical coordinates

derivation of the Laplacian from rectangular to spherical coordinates derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used

Διαβάστε περισσότερα

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8  questions or comments to Dan Fetter 1 Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test

Διαβάστε περισσότερα

Second Order Partial Differential Equations

Second Order Partial Differential Equations Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y

Διαβάστε περισσότερα

Non polynomial spline solutions for special linear tenth-order boundary value problems

Non polynomial spline solutions for special linear tenth-order boundary value problems ISSN 746-7233 England UK World Journal of Modellng and Smulaton Vol. 7 20 No. pp. 40-5 Non polynomal splne solutons for specal lnear tenth-order boundary value problems J. Rashdna R. Jallan 2 K. Farajeyan

Διαβάστε περισσότερα

Written Examination. Antennas and Propagation (AA ) April 26, 2017.

Written Examination. Antennas and Propagation (AA ) April 26, 2017. Written Examination Antennas and Propagation (AA. 6-7) April 6, 7. Problem ( points) Let us consider a wire antenna as in Fig. characterized by a z-oriented linear filamentary current I(z) = I cos(kz)ẑ

Διαβάστε περισσότερα

Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay

Joint Spectrum Sensing and Resource Allocation for OFDM-based Transmission with a Cognitive Relay Jont Spectrum Sensng and Resource Allocaton for OFDM-based Transmsson wth a Cogntve Relay S. Eman Mahmood 1 K.P. Subbalakshm 1 R. Chandramoul 1 Bahman Abolhassan 1 Department of Electrcal and Computer

Διαβάστε περισσότερα

Problem Set 9 Solutions. θ + 1. θ 2 + cotθ ( ) sinθ e iφ is an eigenfunction of the ˆ L 2 operator. / θ 2. φ 2. sin 2 θ φ 2. ( ) = e iφ. = e iφ cosθ.

Problem Set 9 Solutions. θ + 1. θ 2 + cotθ ( ) sinθ e iφ is an eigenfunction of the ˆ L 2 operator. / θ 2. φ 2. sin 2 θ φ 2. ( ) = e iφ. = e iφ cosθ. Chemistry 362 Dr Jean M Standard Problem Set 9 Solutions The ˆ L 2 operator is defined as Verify that the angular wavefunction Y θ,φ) Also verify that the eigenvalue is given by 2! 2 & L ˆ 2! 2 2 θ 2 +

Διαβάστε περισσότερα

Durbin-Levinson recursive method

Durbin-Levinson recursive method Durbin-Levinson recursive method A recursive method for computing ϕ n is useful because it avoids inverting large matrices; when new data are acquired, one can update predictions, instead of starting again

Διαβάστε περισσότερα

4.6 Autoregressive Moving Average Model ARMA(1,1)

4.6 Autoregressive Moving Average Model ARMA(1,1) 84 CHAPTER 4. STATIONARY TS MODELS 4.6 Autoregressive Moving Average Model ARMA(,) This section is an introduction to a wide class of models ARMA(p,q) which we will consider in more detail later in this

Διαβάστε περισσότερα

2 Lagrangian and Green functions in d dimensions

2 Lagrangian and Green functions in d dimensions Renormalzaton of φ scalar feld theory December 6 Pdf fle generated on February 7, 8. TODO Examne ε n the two-pont functon cf Sterman. Lagrangan and Green functons n d dmensons In these notes, we ll use

Διαβάστε περισσότερα

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007 Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Αν κάπου κάνετε κάποιες υποθέσεις να αναφερθούν στη σχετική ερώτηση. Όλα τα αρχεία που αναφέρονται στα προβλήματα βρίσκονται στον ίδιο φάκελο με το εκτελέσιμο

Διαβάστε περισσότερα

ΤΕΧΝΟΛΟΓΙΚΟ ΕΚΠΑΙΔΕΥΤΙΚΟ ΙΔΡΥΜΑ ΚΡΗΤΗΣ ΣΧΟΛΗ ΔΙΟΙΚΗΣΗΣ ΚΑΙ ΟΙΚΟΝΟΜΙΑΣ ΤΜΗΜΑ ΛΟΓΙΣΤΙΚΗΣ ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ

ΤΕΧΝΟΛΟΓΙΚΟ ΕΚΠΑΙΔΕΥΤΙΚΟ ΙΔΡΥΜΑ ΚΡΗΤΗΣ ΣΧΟΛΗ ΔΙΟΙΚΗΣΗΣ ΚΑΙ ΟΙΚΟΝΟΜΙΑΣ ΤΜΗΜΑ ΛΟΓΙΣΤΙΚΗΣ ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ ΤΕΧΝΟΛΟΓΙΚΟ ΕΚΠΑΙΔΕΥΤΙΚΟ ΙΔΡΥΜΑ ΚΡΗΤΗΣ ΣΧΟΛΗ ΔΙΟΙΚΗΣΗΣ ΚΑΙ ΟΙΚΟΝΟΜΙΑΣ ΤΜΗΜΑ ΛΟΓΙΣΤΙΚΗΣ ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ ΛΟΓΙΣΤΙΚΗ ΚΑΙ ΦΟΡΟΛΟΓΙΑ Ο.Ε. ΕΙΣΗΓΗΤΡΙΑ ΚΑΘΗΓΗΤΡΙΑ: κ. ΟΥΡΑΝΟΥ ΕΡΜΙΟΝΗ ΣΠΟΥΔΑΣΤΡΙΕΣ: ΔΕΜΕΤΖΟΥ ΑΓΛΑΪΑ

Διαβάστε περισσότερα

ΓΕΩΠΟΝΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΤΜΗΜΑ ΑΓΡΟΤΙΚΗΣ ΟΙΚΟΝΟΜΙΑΣ & ΑΝΑΠΤΥΞΗΣ

ΓΕΩΠΟΝΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΤΜΗΜΑ ΑΓΡΟΤΙΚΗΣ ΟΙΚΟΝΟΜΙΑΣ & ΑΝΑΠΤΥΞΗΣ ΓΕΩΠΟΝΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΤΜΗΜΑ ΑΓΡΟΤΙΚΗΣ ΟΙΚΟΝΟΜΙΑΣ & ΑΝΑΠΤΥΞΗΣ Πρόγραμμα Μεταπτυχιακών Σπουδών «Ολοκληρωμένη Ανάπτυξη & Διαχείριση Αγροτικού Χώρου» ΜΕΤΑΠΤΥΧΙΑΚΗ ΔΙΑΤΡΙΒΗ «Η συμβολή των Τοπικών Προϊόντων

Διαβάστε περισσότερα

CAPM. VaR Value at Risk. VaR. RAROC Risk-Adjusted Return on Capital

CAPM. VaR Value at Risk. VaR. RAROC Risk-Adjusted Return on Capital C RAM 3002 C RAROC Rsk-Adjusted Return on Captal C C RAM Rsk-Adjusted erformance Measure C RAM RAM Bootstrap RAM C RAROC RAM Bootstrap F830.9 A CAM 2 CAM 3 Value at Rsk RAROC Rsk-Adjusted Return on Captal

Διαβάστε περισσότερα

Statistical Inference I Locally most powerful tests

Statistical Inference I Locally most powerful tests Statistical Inference I Locally most powerful tests Shirsendu Mukherjee Department of Statistics, Asutosh College, Kolkata, India. shirsendu st@yahoo.co.in So far we have treated the testing of one-sided

Διαβάστε περισσότερα

C.S. 430 Assignment 6, Sample Solutions

C.S. 430 Assignment 6, Sample Solutions C.S. 430 Assignment 6, Sample Solutions Paul Liu November 15, 2007 Note that these are sample solutions only; in many cases there were many acceptable answers. 1 Reynolds Problem 10.1 1.1 Normal-order

Διαβάστε περισσότερα

SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018

SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018 Journal of rogressive Research in Mathematics(JRM) ISSN: 2395-028 SCITECH Volume 3, Issue 2 RESEARCH ORGANISATION ublished online: March 29, 208 Journal of rogressive Research in Mathematics www.scitecresearch.com/journals

Διαβάστε περισσότερα

Study on Re-adhesion control by monitoring excessive angular momentum in electric railway traction

Study on Re-adhesion control by monitoring excessive angular momentum in electric railway traction () () Study on e-adhesion control by monitoring excessive angular momentum in electric railway traction Takafumi Hara, Student Member, Takafumi Koseki, Member, Yutaka Tsukinokizawa, Non-member Abstract

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

Areas and Lengths in Polar Coordinates Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the

Διαβάστε περισσότερα

An Inventory of Continuous Distributions

An Inventory of Continuous Distributions Appendi A An Inventory of Continuous Distributions A.1 Introduction The incomplete gamma function is given by Also, define Γ(α; ) = 1 with = G(α; ) = Z 0 Z 0 Z t α 1 e t dt, α > 0, >0 t α 1 e t dt, α >

Διαβάστε περισσότερα

Elements of Information Theory

Elements of Information Theory Elements of Information Theory Model of Digital Communications System A Logarithmic Measure for Information Mutual Information Units of Information Self-Information News... Example Information Measure

Διαβάστε περισσότερα

Aerodynamics & Aeroelasticity: Eigenvalue analysis

Aerodynamics & Aeroelasticity: Eigenvalue analysis Εθνικό Μετσόβιο Πολυτεχνείο Natonal Techncal Unversty of Athens Aerodynamcs & Aeroelastcty: Egenvalue analyss Σπύρος Βουτσινάς / Spyros Voutsnas Άδεια Χρήσης Το παρόν εκπαιδευτικό υλικό υπόκειται σε άδειες

Διαβάστε περισσότερα

Matrices and Determinants

Matrices and Determinants Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z

Διαβάστε περισσότερα

ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems

ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems ES440/ES911: CFD Chapter 5. Solution of Linear Equation Systems Dr Yongmann M. Chung http://www.eng.warwick.ac.uk/staff/ymc/es440.html Y.M.Chung@warwick.ac.uk School of Engineering & Centre for Scientific

Διαβάστε περισσότερα

Appendix S1 1. ( z) α βc. dβ β δ β

Appendix S1 1. ( z) α βc. dβ β δ β Appendix S1 1 Proof of Lemma 1. Taking first and second partial derivatives of the expected profit function, as expressed in Eq. (7), with respect to l: Π Π ( z, λ, l) l θ + s ( s + h ) g ( t) dt λ Ω(

Διαβάστε περισσότερα

Queensland University of Technology Transport Data Analysis and Modeling Methodologies

Queensland University of Technology Transport Data Analysis and Modeling Methodologies Queensland University of Technology Transport Data Analysis and Modeling Methodologies Lab Session #7 Example 5.2 (with 3SLS Extensions) Seemingly Unrelated Regression Estimation and 3SLS A survey of 206

Διαβάστε περισσότερα

Lecture 34 Bootstrap confidence intervals

Lecture 34 Bootstrap confidence intervals Lecture 34 Bootstrap confidence intervals Confidence Intervals θ: an unknown parameter of interest We want to find limits θ and θ such that Gt = P nˆθ θ t If G 1 1 α is known, then P θ θ = P θ θ = 1 α

Διαβάστε περισσότερα

Mean bond enthalpy Standard enthalpy of formation Bond N H N N N N H O O O

Mean bond enthalpy Standard enthalpy of formation Bond N H N N N N H O O O Q1. (a) Explain the meaning of the terms mean bond enthalpy and standard enthalpy of formation. Mean bond enthalpy... Standard enthalpy of formation... (5) (b) Some mean bond enthalpies are given below.

Διαβάστε περισσότερα

ΜΕΛΕΤΗ ΤΗΣ ΜΑΚΡΟΧΡΟΝΙΑΣ ΠΑΡΑΜΟΡΦΩΣΗΣ ΤΟΥ ΦΡΑΓΜΑΤΟΣ ΚΡΕΜΑΣΤΩΝ ΜΕ ΒΑΣΗ ΑΝΑΛΥΣΗ ΓΕΩΔΑΙΤΙΚΩΝ ΔΕΔΟΜΕΝΩΝ ΚΑΙ ΜΕΤΑΒΟΛΩΝ ΣΤΑΘΜΗΣ ΤΑΜΙΕΥΤΗΡΑ

ΜΕΛΕΤΗ ΤΗΣ ΜΑΚΡΟΧΡΟΝΙΑΣ ΠΑΡΑΜΟΡΦΩΣΗΣ ΤΟΥ ΦΡΑΓΜΑΤΟΣ ΚΡΕΜΑΣΤΩΝ ΜΕ ΒΑΣΗ ΑΝΑΛΥΣΗ ΓΕΩΔΑΙΤΙΚΩΝ ΔΕΔΟΜΕΝΩΝ ΚΑΙ ΜΕΤΑΒΟΛΩΝ ΣΤΑΘΜΗΣ ΤΑΜΙΕΥΤΗΡΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΠΑΤΡΩΝ ΠΟΛΥΤΕΧΝΙΚΗ ΣΧΟΛΗ ΤΜΗΜΑ ΠΟΛΙΤΙΚΩΝ ΜΗΧΑΝΙΚΩΝ ΜΕΛΕΤΗ ΤΗΣ ΜΑΚΡΟΧΡΟΝΙΑΣ ΠΑΡΑΜΟΡΦΩΣΗΣ ΤΟΥ ΦΡΑΓΜΑΤΟΣ ΚΡΕΜΑΣΤΩΝ ΜΕ ΒΑΣΗ ΑΝΑΛΥΣΗ ΓΕΩΔΑΙΤΙΚΩΝ ΔΕΔΟΜΕΝΩΝ ΚΑΙ ΜΕΤΑΒΟΛΩΝ ΣΤΑΘΜΗΣ ΤΑΜΙΕΥΤΗΡΑ ΔΙΔΑΚΤΟΡΙΚΗ

Διαβάστε περισσότερα

Partial Differential Equations in Biology The boundary element method. March 26, 2013

Partial Differential Equations in Biology The boundary element method. March 26, 2013 The boundary element method March 26, 203 Introduction and notation The problem: u = f in D R d u = ϕ in Γ D u n = g on Γ N, where D = Γ D Γ N, Γ D Γ N = (possibly, Γ D = [Neumann problem] or Γ N = [Dirichlet

Διαβάστε περισσότερα

Tridiagonal matrices. Gérard MEURANT. October, 2008

Tridiagonal matrices. Gérard MEURANT. October, 2008 Tridiagonal matrices Gérard MEURANT October, 2008 1 Similarity 2 Cholesy factorizations 3 Eigenvalues 4 Inverse Similarity Let α 1 ω 1 β 1 α 2 ω 2 T =......... β 2 α 1 ω 1 β 1 α and β i ω i, i = 1,...,

Διαβάστε περισσότερα

DuPont Suva 95 Refrigerant

DuPont Suva 95 Refrigerant Technical Information T-95 ENG DuPont Suva refrigerants Thermodynamic Properties of DuPont Suva 95 Refrigerant (R-508B) The DuPont Oval Logo, The miracles of science, and Suva, are trademarks or registered

Διαβάστε περισσότερα

On Integrability Conditions of Derivation Equations in a Subspace of Asymmetric Affine Connection Space

On Integrability Conditions of Derivation Equations in a Subspace of Asymmetric Affine Connection Space Flomat 9:0 (05), 4 47 DOI 0.98/FI504Z ublshed by Faculty of Scences and Mathematcs, Unversty of Nš, Serba valable at: htt://www.mf.n.ac.rs/flomat On Integrablty Condtons of Dervaton Equatons n a Subsace

Διαβάστε περισσότερα

A summation formula ramified with hypergeometric function and involving recurrence relation

A summation formula ramified with hypergeometric function and involving recurrence relation South Asian Journal of Mathematics 017, Vol. 7 ( 1): 1 4 www.sajm-online.com ISSN 51-151 RESEARCH ARTICLE A summation formula ramified with hypergeometric function and involving recurrence relation Salahuddin

Διαβάστε περισσότερα