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Econometrics – lecture 5 – assumptions

Lecture 5 -  WLAN Infrastruc

Lecture 5 - WLAN Infrastruc

... publication 250 NEMA Type 4) February 20 05 Copyright 20 05 All Rights Reserved 16 Access Point Mounts February 20 05 Copyright 20 05 All Rights Reserved 17 Wireless Bridge February 20 05 Copyright 20 05 All ... handle between 8-1 6 clients An Enterprise grade WGB can handle up to 255 clients February 20 05 Copyright 20 05 All Rights Reserved 22 Wireless Router February 20 05 Copyright 20 05 All Rights Reserved ... GPS enabled topographical maps http://www.cisco.com/warp/public/102 /wlan/ faq-hardware-us-calc.html February 20 05 Copyright 20 05 All Rights Reserved 21 Wireless Workgroup Bridges q A Wireless Workgroup...
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Tài liệu Modulation and coding course- lecture 5 doc

Tài liệu Modulation and coding course- lecture 5 doc

... z = ( z1 , z , , z N ) are independent Gaussian random variables Its pdf is ⎛ z − si ⎞ ⎟ pz ( z | s i ) = exp⎜ − N /2 ⎜ N0 ⎟ (πN ) ⎝ ⎠ Lecture 5 Detection Optimum decision rule (maximum a posteriori ... Z i z Lecture i 14 Example for binary PAM pz (z | m2 ) pz (z | m1 ) s2 − Eb s1 ψ (t ) Eb ⎛ s1 − s / ⎞ ⎟ Pe (m1 ) = Pe (m2 ) = Q⎜ ⎜ N /2 ⎟ ⎝ ⎠ ⎛ Eb PB = PE (2) = Q⎜ ⎜ N ⎝ Lecture ⎞ ⎟ ⎟ ⎠ 15 Union ... deterministic Elements of noise vector n = (n1 , n2 , , nN ) are i.i.d Gaussian random variables with zero-mean and variance N / The noise vector pdf is ⎛ n2⎞ ⎟ pn (n) = exp⎜ − (πN )N / ⎜ N ⎟...
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Tài liệu LECTURE 5: SOFTWARE PROJECT MANAGEMENT - Software Engineering Mike Wooldridge pdf

Tài liệu LECTURE 5: SOFTWARE PROJECT MANAGEMENT - Software Engineering Mike Wooldridge pdf

... for many projects, this is the raison d’etre Mike Wooldridge Lecture Software Engineering • Activities in software project management: project planning; – project scheduling; – risk management; ... management cannot guarantee success, but poor management on significant projects always leads to failure Mike Wooldridge Lecture Software Engineering Software projects have several properties that make ... computers meant that larger software projects were tackled with techniques developed on much smaller projects • Techniques were needed for software project management Good project management cannot guarantee...
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lecture 5 hplc

lecture 5 hplc

... – Normal phase HPLC – Reverse phase HPLC http://www.waters.com/WatersDivision/Contentd.asp?watersit=JDRS-6UXGZ4 Design & Operation of an HPLC Instrument Design & Operation of an HPLC Instrument ... faster runs Ex: mobile phase composition can be programmed to vary from 75% water: 25% acetonitrile at time zero to 25% water: 75% acetonitrile at the end of the run • More polar components will tend ... components will elute later in the gradient Design & Operation of an HPLC Instrument Design & Operation of an HPLC Instrument 4) HPLC pump: 5) Injector: • Fill stroke: mobile phase is pulled from the...
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CMOS VLSI Design - Lecture 5: DC & Transient Response doc

CMOS VLSI Design - Lecture 5: DC & Transient Response doc

... and 5: DC and Transient Response CMOS VLSI Design 4th Ed Pass Transistor Ckts VDD VDD VDD VDD VDD VDD Vs = VDD-Vtn VDD-Vtn VDD-Vtn VDD VDD-Vtn VDD-Vtn Vs = |Vtp| VDD VDD-2Vtn VSS 5: DC and Transient ... 3C 3C 3C 5: DC and Transient Response CMOS VLSI Design 4th Ed 7C 3C 3C 35 Layout Comparison  Which layout is better? VDD A VDD B Y GND 5: DC and Transient Response A B Y GND CMOS VLSI Design 4th ... 6RC 5: DC and Transient Response CMOS VLSI Design 4th Ed 27 Delay Model Comparison 5: DC and Transient Response CMOS VLSI Design 4th Ed 28 Example: 3-input NAND  Sketch a 3-input NAND with transistor...
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Digital Communication I: Modulation and Coding Course-Lecture 5 potx

Digital Communication I: Modulation and Coding Course-Lecture 5 potx

... we talked about:  Receiver structure  Impact of AWGN and ISI on the transmitted signal  Optimum filter to maximize SNR  Matched filter and correlator receiver  Signal space used for detection ... deterministic  Elements of noise vector n = (n1 , n2 , , nN ) are i.i.d Gaussian random variables with zero-mean and variance N / The noise vector pdf is  n2  pn (n) = exp − ( πN ) N /  N ... z = ( z1 , z , , z N ) are independent Gaussian random variables Its pdf is  z − si   pz ( z | s i ) = exp − N /2  N0  ( πN )   Lecture 5 Detection  Optimum decision rule (maximum a posteriori...
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Lecture 5: Interface Design pptx

Lecture 5: Interface Design pptx

... ); Extending interfaces • Interfaces support multiple inheritance – an interface can extend more than one interface • Superinterfaces and subinterfaces Example public interface SerializableRunnable ... – In the subinterface, explicitly use the superinterface name to refer to the constant of that superinterface E.g B.val); interface A int val } interface B int val } { = 1; { = 2; interface C ... (2) • If a superinterface and a subinterface contain two constants with the same name, then the one belonging to the superinterface is hidden in the subinterface – access the subinterface-version...
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graduate econometrics lecture notes - michael creel

graduate econometrics lecture notes - michael creel

... These lecture notes are copyrighted by Michael Creel with the date that appears above They are provided under the terms of the GNU General Public License, which forms Section 25 of the notes ... editable form for your version of the notes 1.2 Obtaining the notes These notes are part of the OMEGA (Open-source Materials for Econometrics, GPL Archive) project at pareto.uab.es/omega They ... 53 6.2.1 t-test 53 6.2.2 F test 57 6.2.3 Wald-type tests 58 6.2.4 Score-type tests (Rao tests,...
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Handbook of Econometrics Vols1-5 _ Chapter 1 pdf

Handbook of Econometrics Vols1-5 _ Chapter 1 pdf

... matrices of order L X L and K X L, respectively: r YII Y 21 Y12-.*YIL PI1 Pl2-.-PIL Y22 Y2L P 21 P22 P2L YLI r= YL2 where n X L P,, P,L_ XB=E, Yll Y 21 _Y nl (2.3) matrices of the two sets of ... modeling of a disturbance covariance matrix 9 .1 Rational random behavior 9.2 The asymptotics of rational random behavior 9.3 Applications to demand and supply 10 The Moore-Penrose 10 .1 10.2 10 .3 10 .4 ... y,_s_, + A*x, + AA*+, + + A”A*x ,_, + u, + Au ,_, + + AS~t_s (7 .16 ) If all roots of A are less than in absolute value, so that A” converges to zero as s -+ cc and (7 .15 ) holds, the limit of...
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Handbook of Econometrics Vols1-5 _ Chapter 2 ppsx

Handbook of Econometrics Vols1-5 _ Chapter 2 ppsx

... (2ncf;)- 2 exp{-(x2-P2 )2/ 2~~ ,2) (2. 56) and f(xJx2;)= [27 ro:(1-p2)]- 2 Xexp{-[x,-~,-p, .2( x2- ~2) 12/ 2(1-p2)o:}, (2. 57) where p, = a,p/u, From (2. 56), it is seen that the marginal pdf for Z2 is normal ... (2~ )-“ 21 G,111~2exp{- (2. 67a) and dx,lce,) = w- m2’ - %GII’ 21 G 22 G 121 1/2w{- Q2 /2) , (2. 67b) with mi the number of elements in xi, i = 1 ,2, ml + m2 = m, Q,, and Q2 as defined in (2. 65) and (2. 66), ... conditional variance - p2 Since t, = (2, - p2)/u2 the conditional pdf for Z2, given Z,, is normal, that is, f(x,lx,J)= [2nu;(1-PZ)]- 2 Xexp{-[x2- ~2 - _2 .~(x~-11.~) 12/ 2(1-P2)u 22} ~ u2), wheree’ (P,P,,...
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Handbook of Econometrics Vols1-5 _ Chapter 4 docx

Handbook of Econometrics Vols1-5 _ Chapter 4 docx

... replace ,) Conditions 4. 4.2 and 4. 4.3 by those similar to Conditions 4. 3.2 and 4. 3.3 to keep the system identified Or we may rely on [Kohn (1979)]: Theorem 4. 4.2 Under Condition 4. 4.1 and 0, = Zc, ... constant and (4. 32) and (4. 33) hold Combining Lemma 4. 2.1 and Lemma 4. 4.1 we obtain the following proposition about observationally equivalent structures with regard to model (4. 1) Lemma 4. 4.2 Twostructures,S=[B(L) ... identification of those rows of A Similarly for Condition 4. 3.3’ below “For instance, Condition 4. 3.2 implied Condition 6.2.1 of Fisher (1966) 250 C Hsiao 4. 3.1 by Condition 4. 3.3’ For each row of A,...
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Handbook of Econometrics Vols1-5 _ Chapter 5 pot

Handbook of Econometrics Vols1-5 _ Chapter 5 pot

... fall into one of four categories, each of which measures different aspects of the problem.4 (1) (2) (3) (4) Measures of Measures .of Measures of Measures of the the the the “quality of the design” ... Hypotheses by Goodness of Fit”, Economics Journal, 85, 877-882 Ch 5: Model Choice 329 Neyman, Jerzy (1 958 ) “The Use of the Concept of Power in Agricultural Experimentation”, Indian Society of ... Problem”, Annals of Mathematical Srarisrics, 33, 255 -2 65 of an Ad Hoc Procedure for Estimating Parameters Ando, A and G M Kaufman (I 966) “Evaluation of Some Linear Models”, Review of Economics and...
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Handbook of Econometrics Vols1-5 _ Chapter 6 ppsx

Handbook of Econometrics Vols1-5 _ Chapter 6 ppsx

... x/S> a T_ K) ’ (2 .65 ) Note that j? actually drops out of the denominator of (2 .65 ), which makes the computation of the confidence region simple in this case In analogy to (2 .65 ), Hartley (1 964 ) ... Z)-‘ ](y-f) ...
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Handbook of Econometrics Vols1-5 _ Chapter 7 pot

Handbook of Econometrics Vols1-5 _ Chapter 7 pot

... is found in Goldberger (1 970 ), Geraci (1 977 ,1 978 ), Hausman (1 977 ), and Hsiao (1 976 ) Also, see Aigner, Hsiao, Kapteyn and Wansbeek (Chapter 23 in this Handbook) Ch 7: Simultaneous Equation Models ... the case of restrictions on Xl4 14Hsiao (Chapter models He discusses in this Handbook) also discusses the case of errors in variables also identification of simultaneous equation Ch 7: Simultaneous ... 38Malinvaud (1 970 , pp 678 - 679 ) derives the concentrated Rothenberg (1 973 , p 78 ) derives the Cramer-Rao bound log-likelihood function for this case 428 J A Hausman term p”ui which is, of course,...
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