Outline. M/M/1 Queue (infinite buffer) M/M/1/N (finite buffer) Networks of M/M/1 Queues M/G/1 Priority Queue
|
|
|
- Ῥαχήλ Βαρουξής
- 6 χρόνια πριν
- Προβολές:
Transcript
1 Queueig Aalysis
2 Outlie M/M/ Queue (ifiite buffer M/M//N (fiite buffer M/M// (Erlag s B forula M/M/ (Erlag s C forula Networks of M/M/ Queues M/G/ Priority Queue
3 M/M/ M: Markovia/Meoryless Arrival process is Poisso Departure process is Expoetial Sigle Server Ifiite buffer for waitig custoers server Poisso arrivals with rate queue Expoetial service with rate μ
4 Poisso Process Arrival process, Δt is a very sall segeted tie ad is the average arrival rate P arrival i t, t+δt Δt P o arrival i t, t+δt -Δt P ore tha arrivals i t, t+δt Joit or split Poisso process is also Poisso process
5 Markov Property Meoryless: P (T>t + t T>t P (T> t P(X(t + x + X(t x, P(X(t - x -. X(t x P(X(t + x + X(t x The future is idepedet of the past!
6 M/M/ queueig odel State trasitio diagra - t -(+μ t -(+μ t -(+μ t -(+μ t -(+μ t -(+μ t μ t μ t μ t μ t μ t μ t μ t μ t t t t t t t t t
7 M/M/: balace equatios Equilibriu or steady state aalysis: P + μ t P t P μ P P μ P P μ P > 3.. P - μ P P /μ P P P /μ P P P 3 /μ P 3 P.. P /μ P - P /μ is called utilizatio factor or traffic itesity < or <μ <> Syste is stable!
8 M/M/: fid P P P p P (,,, Geoetric distributio!
9 Little s law The log ter average uber of custoers i a queueig syste is EN ET, where ET is the average tie a custoer speds i the syste, is the average arrival rate of custoers.
10 M/M/: syste perforace The average uber of custoers i the queueig syste EN The average waitig tie i the queueig syste (usig Little s Law E T E N μ μ
11 M/M/: queue perforace The average uber of custoers i the queue E Nq The average waitig tie i the queue (or usig Little s Law E T q E T E Ts ( μ μ
12 M/M//N queueig syste (fiite buffer (-P B Queue Server N P B N: The syste ca hold at ost N custoers (icludig the oe i service
13 N B N N N P P p p N p p + +, 3 N- N- N t t t t t t t μ t μ t μ t μ t μ t μ t μ t - t -(+μ t -(+μ t -(+μ t -(+μ t -μ t -(+μ t Blockig probability: the probability that the syste is full M/M//N : blockig probability
14 M/M// queueig odel (-P B 3 P B Servers - t -(+μ t -(+μ t -(+3μ t μ t μ t 3μ t 4μ t (-μ t -(+(- μ t -(+(-μ t (- μ t μ t -μ t t t t t t t t
15 M/M//: blockig probability,,,, - μ μ, Blockig probability P B (fid all servers are busy Erlag s B forula B i P P P p p i P (! (! (!! ( ( μ μ μ μ μ
16 M/M/ queueig odel: parallel servers with a ifiite queue Queue 3 Servers Perforace etric: the probability that a arrival has to wait i the queue (P Q
17 M/M/: state trasitio diagra - t -(+μ t -(+μ t -(+3μ t -(+(- μ t -(+μ t μ t μ t 3μ t 4μ t (-μ t μ t μ t -(+ μ t μ t t t t t t t t t μ( μ, μ, >
18 M/M/: fid P! ( ( p p! p p μ!(! ( + p P
19 M/M/:PQ All the servers i this syste are busy Erlag s C forula + Q!(! (!(!( P p P
20 Networks of M/M/ queues L M/M/ queues for a syste, ad i ad μi are Poisso arrival ad departure rates of a queue, Qi. The average uber of custoers i each M/M/ queue(ode is E Ni i i μi i i
21 The total uber of custoers i the syste The average delay per packet (little s law L i i i i L i Ni E N E μ S k k L i i i i N E T E γ μ, is the average arrival rate of the custoers eterig the syste
22 M/G/ queueig odel Poisso arrivals with rate Arbitrary service tie (ay distributio EX/μ first oet (of service tie EX Var(X+E X secod oet
23 M/G/: syste perforace The average uber of custoers i the queueig syste The average waitig tie i the syste ( μ + X E N E ( μ + + X E E T E T T E q s
24 M/G/: queue perforace The average uber of custoers i the queue The average waitig tie i the queue ( X E N E q ( X E T E q
25 Priority queueig (M/G/ queue Two priority classes case: delay sesitive ad best effort Type packets are give service priority i that service will ever begi o Type packets if a Type packet is waitig If Type packet is beig served ad a Type packet arrives, the service of the Type packet is cotiued util copletio (there is ot pre-eptio
26 The average delay per Type packet is give by E T + μ E T q + μ ie T ( The average delay per Type packet is give by E T + μ E T q + μ i i si ( ( ie T si
Στοιχεία Θεωρίας Αναµονής (queueing theory) ίκτυα Επικοινωνιών: Στοιχεία Θεωρίας Αναµονής -- N. Μήτρου
Στοιχεία Θεωίας Αναµονής (queueig theory) ίκτυα Επικοινωνιών: Στοιχεία Θεωίας Αναµονής -- N. Μήτου Θεωία Αναµονής Βασικό µαθηµατικό εγαείο για την ανάυση της επίδοσης και το σχεδιασµό δικτύων, αφού η ζήτηση
Queueing Theory I. Summary. Little s Law Queueing System Notation Stationary Analysis of Elementary Queueing Systems. M/M/1 M/M/m M/M/1/K
Queueing Theory I Suary Little s Law Queueing Syste Notation Stationary Analysis of Eleentary Queueing Systes M/M/ M/M/ M/M// Little s Law a(t): the process that counts the nuber of arrivals up to t. d(t):
Tired Waiting in Queues? Then get in line now to learn more about Queuing!
Tired Waitig i Queues? The get i lie ow to lear more about Queuig! Some Begiig Notatio Let = the umber of objects i the system s = the umber of servers = mea arrival rate (arrivals per uit of time with
SUPERPOSITION, MEASUREMENT, NORMALIZATION, EXPECTATION VALUES. Reading: QM course packet Ch 5 up to 5.6
SUPERPOSITION, MEASUREMENT, NORMALIZATION, EXPECTATION VALUES Readig: QM course packet Ch 5 up to 5. 1 ϕ (x) = E = π m( a) =1,,3,4,5 for xa (x) = πx si L L * = πx L si L.5 ϕ' -.5 z 1 (x) = L si
Μοντέλα Αναμονής σε Δίκτυα Επικοινωνιών. Ανάλυση Ουρών. Λάζαρος Μεράκος Τμήμα Πληροφορικής &Τηλεπικοινωνιών Πανεπιστήμιο Αθηνών
Μοντέλα Αναμονής σε Δίκτυα Επικοινωνιών Ανάλυση Ουρών Λάζαρος Μεράκος Τμήμα Πληροφορικής &Τηλεπικοινωνιών Πανεπιστήμιο Αθηνών Μενού 1. Εισαγωγή 2. Θεώρημα του Little 3. Σύστημα M/M/1 System 4. Συστήματα
IIT JEE (2013) (Trigonomtery 1) Solutions
L.K. Gupta (Mathematic Classes) www.pioeermathematics.com MOBILE: 985577, 677 (+) PAPER B IIT JEE (0) (Trigoomtery ) Solutios TOWARDS IIT JEE IS NOT A JOURNEY, IT S A BATTLE, ONLY THE TOUGHEST WILL SURVIVE
Μοντέλα Συστημάτων Αναμονής σε Δίκτυα Επικοινωνιών
Δίκτυα Επικοινωνιών ΙΙ Τμήμα Πληροφορικής και Τηλεπικοινωνιών Εθνικό & Καποδιστριακό Πανεπιστήμιο Αθηνών Μοντέλα Συστημάτων Αναμονής σε Δίκτυα Επικοινωνιών Διδάσκων: Λάζαρος Μεράκος Δίκτυα Επικοινωνιών
Εισαγωγή στην θεωρία ουρών.
Εισαγωγή στην θεωρία ουρών. Εισαγωγή στη Θεωρία Ουρών/Queuing Theory. Από τα πιο ισχυρά μαθηματικά εργαλεία για την εκτέλεση ποσοτικών αναλύσεων. Αρχικά αναπτύχθηκε για ανάλυση της στατιστικής συμπεριφοράς
α β
6. Eerg, Mometum coefficiets for differet velocit distributios Rehbock obtaied ) For Liear Velocit Distributio α + ε Vmax { } Vmax ε β +, i which ε v V o Give: α + ε > ε ( α ) Liear velocit distributio
Solve the difference equation
Solve the differece equatio Solutio: y + 3 3y + + y 0 give tat y 0 4, y 0 ad y 8. Let Z{y()} F() Taig Z-trasform o both sides i (), we get y + 3 3y + + y 0 () Z y + 3 3y + + y Z 0 Z y + 3 3Z y + + Z y
1. For each of the following power series, find the interval of convergence and the radius of convergence:
Math 6 Practice Problems Solutios Power Series ad Taylor Series 1. For each of the followig power series, fid the iterval of covergece ad the radius of covergece: (a ( 1 x Notice that = ( 1 +1 ( x +1.
L.K.Gupta (Mathematic Classes) www.pioeermathematics.com MOBILE: 985577, 4677 + {JEE Mai 04} Sept 0 Name: Batch (Day) Phoe No. IT IS NOT ENOUGH TO HAVE A GOOD MIND, THE MAIN THING IS TO USE IT WELL Marks:
Δίκτυα Επικοινωνιών ΙΙ. Ενότητα 2: Μοντέλα Συστηµάτων Αναµονής σε Δίκτυα Επικοινωνιών
Δίκτυα Επικοινωνιών ΙΙ Ενότητα 2: Μοντέλα Συστηµάτων Αναµονής σε Δίκτυα Επικοινωνιών Διδάσκων: Λάζαρος Μεράκος Τµήµα Πληροφορικής και Τηλεπικοινωνιών Εθνικό & Καποδιστριακό Πανεπιστήµιο Αθηνών Δίκτυα Επικοινωνιών
Ψηφιακή Επεξεργασία Εικόνας
ΠΑΝΕΠΙΣΤΗΜΙΟ ΙΩΑΝΝΙΝΩΝ ΑΝΟΙΚΤΑ ΑΚΑΔΗΜΑΪΚΑ ΜΑΘΗΜΑΤΑ Ψηφιακή Επεξεργασία Εικόνας Φιλτράρισμα στο πεδίο των συχνοτήτων Διδάσκων : Αναπληρωτής Καθηγητής Νίκου Χριστόφορος Άδειες Χρήσης Το παρόν εκπαιδευτικό
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Διαδικασίες Γεννήσεων - Θανάτων Εξισώσεις Ισορροπίας - Ουρές Μ/Μ/1, M/M/1/N Προσομοίωση Ουράς Μ/Μ/1/Ν
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Διαδικασίες Γεννήσεων - Θανάτων Εξισώσεις Ισορροπίας - Ουρές Μ/Μ/1, M/M/1/N Προσομοίωση Ουράς Μ/Μ/1/Ν Βασίλης Μάγκλαρης maglaris@netmode.ntua.gr 23/3/2016 Άδεια Χρήσης
FREE VIBRATION OF A SINGLE-DEGREE-OF-FREEDOM SYSTEM Revision B
FREE VIBRATION OF A SINGLE-DEGREE-OF-FREEDOM SYSTEM Revisio B By Tom Irvie Email: tomirvie@aol.com February, 005 Derivatio of the Equatio of Motio Cosier a sigle-egree-of-freeom system. m x k c where m
Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)
Phys460.nb 81 ψ n (t) is still the (same) eigenstate of H But for tdependent H. The answer is NO. 5.5.5. Solution for the tdependent Schrodinger s equation If we assume that at time t 0, the electron starts
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
p n r.01.05.10.15.20.25.30.35.40.45.50.55.60.65.70.75.80.85.90.95
r r Table 4 Biomial Probability Distributio C, r p q This table shows the probability of r successes i idepedet trials, each with probability of success p. p r.01.05.10.15.0.5.30.35.40.45.50.55.60.65.70.75.80.85.90.95
Homework for 1/27 Due 2/5
Name: ID: Homework for /7 Due /5. [ 8-3] I Example D of Sectio 8.4, the pdf of the populatio distributio is + αx x f(x α) =, α, otherwise ad the method of momets estimate was foud to be ˆα = 3X (where
Introduction of Numerical Analysis #03 TAGAMI, Daisuke (IMI, Kyushu University)
Itroductio of Numerical Aalysis #03 TAGAMI, Daisuke (IMI, Kyushu Uiversity) web page of the lecture: http://www2.imi.kyushu-u.ac.jp/~tagami/lec/ Strategy of Numerical Simulatios Pheomea Error modelize
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Εισαγωγή (1/2) Βασίλης Μάγκλαρης maglaris@netmode.ntua.gr 1/3/2017 ΠΕΡΙΕΧΟΜΕΝΑ (1/3) http://www.netmode.ntua.gr/main/index.php?option=com_content&task=view& id=130&itemid=48
Outline. Detection Theory. Background. Background (Cont.)
Outlie etectio heory Chapter7. etermiistic Sigals with Ukow Parameters afiseh S. Mazloum ov. 3th Backgroud Importace of sigal iformatio Ukow amplitude Ukow arrival time Siusoidal detectio Classical liear
Bessel function for complex variable
Besse fuctio for compex variabe Kauhito Miuyama May 4, 7 Besse fuctio The Besse fuctio Z ν () is the fuctio wich satisfies + ) ( + ν Z ν () =. () Three kids of the soutios of this equatio are give by {
The challenges of non-stable predicates
The challenges of non-stable predicates Consider a non-stable predicate Φ encoding, say, a safety property. We want to determine whether Φ holds for our program. The challenges of non-stable predicates
(C) 2010 Pearson Education, Inc. All rights reserved.
Connectionless transmission with datagrams. Connection-oriented transmission is like the telephone system You dial and are given a connection to the telephone of fthe person with whom you wish to communicate.
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Παράμετροι Συστημάτων Αναμονής Τύπος Little. Β. Μάγκλαρης, Σ. Παπαβασιλείου
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Παράμετροι Συστημάτων Αναμονής Τύπος Little Β. Μάγκλαρης, Σ. Παπαβασιλείου 8-5-2014 Άδεια Χρήσης Το παρόν εκπαιδευτικό υλικό υπόκειται σε άδειες χρήσης Creative Commons.
Homework 8 Model Solution Section
MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx
Solutions: Homework 3
Solutios: Homework 3 Suppose that the radom variables Y,, Y satisfy Y i = βx i + ε i : i,, where x,, x R are fixed values ad ε,, ε Normal0, σ ) with σ R + kow Fid ˆβ = MLEβ) IND Solutio: Observe that Y
Last Lecture. Biostatistics Statistical Inference Lecture 19 Likelihood Ratio Test. Example of Hypothesis Testing.
Last Lecture Biostatistics 602 - Statistical Iferece Lecture 19 Likelihood Ratio Test Hyu Mi Kag March 26th, 2013 Describe the followig cocepts i your ow words Hypothesis Null Hypothesis Alterative Hypothesis
EN40: Dynamics and Vibrations
EN40: Dyamics a Vibratios School of Egieerig Brow Uiversity Solutios to Differetial Equatios of Motio for Vibratig Systems Here, we summarize the solutios to the most importat ifferetial equatios of motio
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
Δίκτυα Επικοινωνιών ΙΙ: OSPF Configuration
Δίκτυα Επικοινωνιών ΙΙ: OSPF Configuration Δρ. Απόστολος Γκάμας Διδάσκων 407/80 gkamas@uop.gr Δίκτυα Επικοινωνιών ΙΙ Διαφάνεια 1 1 Dynamic Routing Configuration Router (config) # router protocol [ keyword
Inertial Navigation Mechanization and Error Equations
Iertial Navigatio Mechaizatio ad Error Equatios 1 Navigatio i Earth-cetered coordiates Coordiate systems: i iertial coordiate system; ECI. e earth fixed coordiate system; ECEF. avigatio coordiate system;
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Παράμετροι Συστημάτων Αναμονής Τύπος Little
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Παράμετροι Συστημάτων Αναμονής Τύπος Little Βασίλης Μάγκλαρης maglaris@netmode.ntua.gr 2/3/2016 Άδεια Χρήσης Το παρόν εκπαιδευτικό υλικό υπόκειται σε άδειες χρήσης Creative
EE 570: Location and Navigation
EE 570: Locatio ad Navigatio INS Iitializatio Aly El-Osery Electrical Egieerig Departmet, New Mexico Tech Socorro, New Mexico, USA April 25, 2013 Aly El-Osery (NMT) EE 570: Locatio ad Navigatio April 25,
ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ. ΕΠΛ342: Βάσεις Δεδομένων. Χειμερινό Εξάμηνο Φροντιστήριο 10 ΛΥΣΕΙΣ. Επερωτήσεις SQL
ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ ΕΠΛ342: Βάσεις Δεδομένων Χειμερινό Εξάμηνο 2013 Φροντιστήριο 10 ΛΥΣΕΙΣ Επερωτήσεις SQL Άσκηση 1 Για το ακόλουθο σχήμα Suppliers(sid, sname, address) Parts(pid, pname,
A study on generalized absolute summability factors for a triangular matrix
Proceedigs of the Estoia Acadey of Scieces, 20, 60, 2, 5 20 doi: 0.376/proc.20.2.06 Available olie at www.eap.ee/proceedigs A study o geeralized absolute suability factors for a triagular atrix Ere Savaş
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
Steady-state Analysis of the GI/M/1 Queue with Multiple Vacations and Set-up Time
Moder Applied Sciece September 8 Steady-state Aalysis of the GI/M/ Queue with Multiple Vacatios ad Set-up Time Guohui Zhao College of Sciece Yasha Uiersity Qihuagdao 664 Chia E-mail: zhaoguohui8@6com Xixi
LAD Estimation for Time Series Models With Finite and Infinite Variance
LAD Estimatio for Time Series Moels With Fiite a Ifiite Variace Richar A. Davis Colorao State Uiversity William Dusmuir Uiversity of New South Wales 1 LAD Estimatio for ARMA Moels fiite variace ifiite
Presentation of complex number in Cartesian and polar coordinate system
1 a + bi, aεr, bεr i = 1 z = a + bi a = Re(z), b = Im(z) give z = a + bi & w = c + di, a + bi = c + di a = c & b = d The complex cojugate of z = a + bi is z = a bi The sum of complex cojugates is real:
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
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
Volume of a Cuboid. Volume = length x breadth x height. V = l x b x h. The formula for the volume of a cuboid is
Volume of a Cuboid The formula for the volume of a cuboid is Volume = length x breadth x height V = l x b x h Example Work out the volume of this cuboid 10 cm 15 cm V = l x b x h V = 15 x 6 x 10 V = 900cm³
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuig Systems Επισκόπηση Γνώσεων Πιθανοτήτων Βασίλης Μάγκλαρης maglaris@etmode.tua.gr 7/3/2018 1 Η ΔΙΑΔΙΚΑΣΙΑ ΚΑΤΑΜΕΤΡΗΣΗΣ ΓΕΓΟΝΟΤΩΝ POISSON Η τυχαία εμφάνιση παλμών περιγράφεται σαν
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
Chapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =?
Teko Classes IITJEE/AIEEE Maths by SUHAAG SIR, Bhopal, Ph (0755) 3 00 000 www.tekoclasses.com ANSWERSHEET (TOPIC DIFFERENTIAL CALCULUS) COLLECTION # Question Type A.Single Correct Type Q. (A) Sol least
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Ψηφιακή Οικονομία Άσκηση αυτοαξιολόγησης 4 Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών CS-593 Game Theory 1. For the game depicted below, find the mixed strategy
Fractional Colorings and Zykov Products of graphs
Fractional Colorings and Zykov Products of graphs Who? Nichole Schimanski When? July 27, 2011 Graphs A graph, G, consists of a vertex set, V (G), and an edge set, E(G). V (G) is any finite set E(G) is
Physical DB Design. B-Trees Index files can become quite large for large main files Indices on index files are possible.
B-Trees Index files can become quite large for large main files Indices on index files are possible 3 rd -level index 2 nd -level index 1 st -level index Main file 1 The 1 st -level index consists of pairs
Homework 4.1 Solutions Math 5110/6830
Homework 4. Solutios Math 5/683. a) For p + = αp γ α)p γ α)p + γ b) Let Equilibria poits satisfy: p = p = OR = γ α)p ) γ α)p + γ = α γ α)p ) γ α)p + γ α = p ) p + = p ) = The, we have equilibria poits
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,
Solutions to Exercise Sheet 5
Solutions to Eercise Sheet 5 jacques@ucsd.edu. Let X and Y be random variables with joint pdf f(, y) = 3y( + y) where and y. Determine each of the following probabilities. Solutions. a. P (X ). b. P (X
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
MATH 38061/MATH48061/MATH68061: MULTIVARIATE STATISTICS Solutions to Problems on Matrix Algebra
MATH 38061/MATH48061/MATH68061: MULTIVARIATE STATISTICS Solutios to Poblems o Matix Algeba 1 Let A be a squae diagoal matix takig the fom a 11 0 0 0 a 22 0 A 0 0 a pp The ad So, log det A t log A t log
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 6/5/2006
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Ολοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα είναι μικρότεροι το 1000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Διάρκεια: 3,5 ώρες Καλή
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 :
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 24/3/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Όλοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα μικρότεροι του 10000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Αν κάπου κάνετε κάποιες υποθέσεις
CE 530 Molecular Simulation
C 53 olecular Siulation Lecture Histogra Reweighting ethods David. Kofke Departent of Cheical ngineering SUNY uffalo kofke@eng.buffalo.edu Histogra Reweighting ethod to cobine results taken at different
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
the total number of electrons passing through the lamp.
1. A 12 V 36 W lamp is lit to normal brightness using a 12 V car battery of negligible internal resistance. The lamp is switched on for one hour (3600 s). For the time of 1 hour, calculate (i) the energy
Solar Neutrinos: Fluxes
Solar Neutrinos: Fluxes pp chain Sun shines by : 4 p 4 He + e + + ν e + γ Solar Standard Model Fluxes CNO cycle e + N 13 =0.707MeV He 4 C 1 C 13 p p p p N 15 N 14 He 4 O 15 O 16 e + =0.997MeV O17
HOMEWORK#1. t E(x) = 1 λ = (b) Find the median lifetime of a randomly selected light bulb. Answer:
HOMEWORK# 52258 李亞晟 Eercise 2. The lifetime of light bulbs follows an eponential distribution with a hazard rate of. failures per hour of use (a) Find the mean lifetime of a randomly selected light bulb.
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Εισαγωγή (2/2) Επισκόπηση Γνώσεων Πιθανοτήτων (1/2)
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Εισαγωγή (2/2) Επισκόπηση Γνώσεων Πιθανοτήτων (1/2) Βασίλης Μάγκλαρης maglaris@netmode.ntua.gr 8/3/2017 ΠΑΡΑΜΕΤΡΟΙ (1/4) (Επανάληψη) Ένταση φορτίου (traffic intensity)
INTEGRATION OF THE NORMAL DISTRIBUTION CURVE
INTEGRATION OF THE NORMAL DISTRIBUTION CURVE By Tom Irvie Email: tomirvie@aol.com March 3, 999 Itroductio May processes have a ormal probability distributio. Broadbad radom vibratio is a example. The purpose
Biorthogonal Wavelets and Filter Banks via PFFS. Multiresolution Analysis (MRA) subspaces V j, and wavelet subspaces W j. f X n f, τ n φ τ n φ.
Chapter 3. Biorthogoal Wavelets ad Filter Baks via PFFS 3.0 PFFS applied to shift-ivariat subspaces Defiitio: X is a shift-ivariat subspace if h X h( ) τ h X. Ex: Multiresolutio Aalysis (MRA) subspaces
4. ELECTROCHEMISTRY - II
4. ELETROHEMISTRY - II Molar coductace, Equivalet coductace, cell cetat ad Kohlraush Law :. Give : l 0.98 cm a.3 cm cell cost. cell cost. a l cell cost. a l 0.98.3 0.7538 cm As : ell costat for the cell
Παραμετρικές εξισώσεις καμπύλων. ΗΥ111 Απειροστικός Λογισμός ΙΙ
ΗΥ-111 Απειροστικός Λογισμός ΙΙ Παραμετρικές εξισώσεις καμπύλων Παραδείγματα ct (): U t ( x ( t), x ( t)) 1 ct (): U t ( x ( t), x ( t), x ( t)) 3 1 3 Θέσης χρόνου ταχύτητας χρόνου Χαρακτηριστικού-χρόνου
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Διαδικασίες Birth-Death, Ουρές Markov:
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Διαδικασίες Birth-Death, Ουρές Markov: 1. Διαγράμματα Μεταβάσεων Εργοδικών Καταστάσεων, Εξισώσεις Ισορροπίας 2. Προσομοιώσεις, Άσκηση Προσομοίωσης Ουράς M/M/1/10 Βασίλης
Ειδικό πρόγραμμα ελέγχου για τον ιό του Δυτικού Νείλου και την ελονοσία, ενίσχυση της επιτήρησης στην ελληνική επικράτεια (MIS 365280)
«Ειδικό πρόγραμμα ελέγχου για τον ιό του Δυτικού Νείλου και την ελονοσία, ενίσχυση της επιτήρησης στην ελληνική επικράτεια» Παραδοτέο Π1.36 Έκδοση ενημερωτικών φυλλαδίων Υπεύθυνος φορέας: Κέντρο Ελέγχου
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Διαδικασίες Birth-Death, Ουρές Markov: 1. Διαγράμματα Μεταβάσεων Εργοδικών Καταστάσεων 2. Εξισώσεις Ισορροπίας 3. Προσομοιώσεις Βασίλης Μάγκλαρης maglaris@netmode.ntua.gr
Πανεπιστήμιο Κρήτης, Τμήμα Επιστήμης Υπολογιστών Άνοιξη 2009. HΥ463 - Συστήματα Ανάκτησης Πληροφοριών Information Retrieval (IR) Systems
Πανεπιστήμιο Κρήτης, Τμήμα Επιστήμης Υπολογιστών Άνοιξη 2009 HΥ463 - Συστήματα Ανάκτησης Πληροφοριών Information Retrieval (IR) Systems Στατιστικά Κειμένου Text Statistics Γιάννης Τζίτζικας άλ ιάλεξη :
k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +
[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +](/thumbs/73/69566903.jpg "k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +")
Chapter 3. Fuzzy Arithmetic 3- Fuzzy arithmetic: ~Addition(+) and subtraction (-): Let A = [a and B = [b, b in R If x [a and y [b, b than x+y [a +b +b Symbolically,we write A(+)B = [a (+)[b, b = [a +b
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
Systems with unlimited supply of work: MCQN with infinite virtual buffers A Push Pull multiclass system
Systems with unlimited supply of work: MCQN with infinite virtual buffers A Push Pull multiclass system Gideon Weiss University of Haifa Joint work with students: Anat (Anastasia) Kopzon Yoni Nazarathy
EE101: Resonance in RLC circuits
EE11: Resonance in RLC circuits M. B. Patil mbatil@ee.iitb.ac.in www.ee.iitb.ac.in/~sequel Deartment of Electrical Engineering Indian Institute of Technology Bombay I V R V L V C I = I m = R + jωl + 1/jωC
EE 570: Location and Navigation
EE 570: Location and Navigation INS Initialization Aly El-Osery Kevin Wedeward Electrical Engineering Department, New Mexico Tech Socorro, New Mexico, USA In Collaboration with Stephen Bruder Electrical
Example of the Baum-Welch Algorithm
Example of the Baum-Welch Algorithm Larry Moss Q520, Spring 2008 1 Our corpus c We start with a very simple corpus. We take the set Y of unanalyzed words to be {ABBA, BAB}, and c to be given by c(abba)
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems
ΣΥΣΤΗΜΑΤΑ ΑΝΑΜΟΝΗΣ Queuing Systems Παράμετροι Ουρών Αναμονής Βασίλης Μάγκλαρης maglaris@netmode.ntua.gr 13/3/2019 ΠΑΡΑΜΕΤΡΟΙ (1/3) Ένταση φορτίου (traffic intensity) Σε περίπτωση 1 ουράς, 1 εξυπηρετητή:
12. Radon-Nikodym Theorem
Tutorial 12: Radon-Nikodym Theorem 1 12. Radon-Nikodym Theorem In the following, (Ω, F) is an arbitrary measurable space. Definition 96 Let μ and ν be two (possibly complex) measures on (Ω, F). We say
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ & ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ Τοµέας Επικοινωνιών, Ηεκτρονικής & Συστηµάτων Πηροφορικής Εργαστήριο ιαχείρισης & Βετίστου Σχεδιασµού ικτύων - NETMODE Πουτεχνειούποη
HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:
HOMEWORK 4 Problem a For the fast loading case, we want to derive the relationship between P zz and λ z. We know that the nominal stress is expressed as: P zz = ψ λ z where λ z = λ λ z. Therefore, applying
MATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)
![MATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)](/thumbs/81/84712331.jpg "MATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)")
1. MATH43 String Theory Solutions 4 x = 0 τ = fs). 1) = = f s) ) x = x [f s)] + f s) 3) equation of motion is x = 0 if an only if f s) = 0 i.e. fs) = As + B with A, B constants. i.e. allowe reparametrisations
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) =
Differential equations
Differential equations Differential equations: An equation inoling one dependent ariable and its deriaties w. r. t one or more independent ariables is called a differential equation. Order of differential
Προσομοίωση BP με το Bizagi Modeler
Προσομοίωση BP με το Bizagi Modeler Α. Τσαλγατίδου - Γ.-Δ. Κάπος Πρόγραμμα Μεταπτυχιακών Σπουδών Τεχνολογία Διοίκησης Επιχειρησιακών Διαδικασιών 2017-2018 BPMN Simulation with Bizagi Modeler: 4 Levels
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
Ευρωπαϊκός Αριθμός 112.
Ευρωπαϊκός Αριθμός 112. Επίδραση στο χρόνο καθυστέρησης των ασθενών (patient delay) Δημήτριος Γ. Πύρρος, MD, EMDM Συντονιστής Διευθυντής, Τμ. Ιατρικών Υπηρεσιών, EKAB President, European Emergency Number
Special edition of the Technical Chamber of Greece on Video Conference Services on the Internet, 2000 NUTWBCAM
NUTWBCAM A.S. DRIGAS Applied Technologies Department NCSR DEMOKRITOS Ag. Paraskevi GREECE dr@imm.demokritos.gr http://imm.demokritos.gr Το NutWBCam είναι ένα RealVideo πρόγραµµα που σας δίνει τη δυνατότητα
Θεωρία Τηλεπικοινωνιακής Κίνησης Ενότητα 2: Θεμελιώδεις σχέσεις
Θεωρία Τηλεπικοινωνιακής Κίνησης Ενότητα 2: Θεμελιώδεις σχέσεις Μιχαήλ Λογοθέτης Πολυτεχνική Σχολή Τμήμα Ηλεκτρολόγων Μηχανικών και Τεχνολογίας Υπολογιστών Σκοποί ενότητας Περιγραφή βασικών μοντέλων τηλεπικοινωνιακής
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
Bayesian statistics. DS GA 1002 Probability and Statistics for Data Science.
Bayesian statistics DS GA 1002 Probability and Statistics for Data Science http://www.cims.nyu.edu/~cfgranda/pages/dsga1002_fall17 Carlos Fernandez-Granda Frequentist vs Bayesian statistics In frequentist
A Bonus-Malus System as a Markov Set-Chain. Małgorzata Niemiec Warsaw School of Economics Institute of Econometrics
A Bonus-Malus System as a Markov Set-Chain Małgorzata Niemiec Warsaw School of Economics Institute of Econometrics Contents 1. Markov set-chain 2. Model of bonus-malus system 3. Example 4. Conclusions
ΣΧΕΔΙΑΣΜΟΣ ΔΙΚΤΥΩΝ ΔΙΑΝΟΜΗΣ. Η εργασία υποβάλλεται για τη μερική κάλυψη των απαιτήσεων με στόχο. την απόκτηση του διπλώματος
ΣΧΕΔΙΑΣΜΟΣ ΔΙΚΤΥΩΝ ΔΙΑΝΟΜΗΣ Η εργασία υποβάλλεται για τη μερική κάλυψη των απαιτήσεων με στόχο την απόκτηση του διπλώματος «Οργάνωση και Διοίκηση Βιομηχανικών Συστημάτων με εξειδίκευση στα Συστήματα Εφοδιασμού
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
Calculating the propagation delay of coaxial cable
Your source for quality GNSS Networking Solutions and Design Services! Page 1 of 5 Calculating the propagation delay of coaxial cable The delay of a cable or velocity factor is determined by the dielectric
Digital Integrated Circuits, 2 nd edition, J. M. Rabaey, A. Chandrakasan, B. Nikolic
Πρόβληµα 4. gital Itegrated Circuits, d editio, J. M. abaey, A. Chadrakasa, B. Nikolic You are desigig a clock distributio etwork i which it is critical to miimize skew betwee local clocks (CLK, CLK, ad