Ch5 Appendix Q-factor and Smith Chart Matching

Size: px
Start display at page:

Download "Ch5 Appendix Q-factor and Smith Chart Matching"

Transcription

1 h5 Appedx -factr ad mth hart Matchg 5B-1 We-ha a udwg, F rcut Desg Thery ad Applcat, hapter 8 Frequecy espse f -type Matchg Netwrks 5B- Fg.8-8 Tw desg realzats f a -type matchg etwrk.65pf, 80 f 1 GHz Fg.8-9 Frequecy respse f the tw matchg etwrk realzats.

2 5B-3 Badpass Flter Equvalet (1) T fd the badwdth f the matchg etwrk, Fg.8-8 (c) ca be redraw as a badpass flter wth a laded qualty factr BW f (Detal the fllwg pages) Fg.8-10 (a) Equvalet badpass flter Fg.8-10 (b) Frequecy respse f the matchg etwrk 5B-4 Badpass Flter Equvalet () Frst, the & s replaced by a equvalet parallel cect f P & P, ad addg the capactaces T P. T get T & N, replacg the seres cect V s, s, & wth the Nrt equvalet curret surce I N. ( ) ( ) ( ) ( ) ( ) 1 1 ) /( N N s s N j G j j j Y j V I

3 Badpass Flter Equvalet (3) Next, the curret surce I N & cductace G N are cverted back t a Theve equvalet vltage surce 5B-5 V T T I N / G N T V s 6.54Ω j 1 ( ) T GN Frm resatr thery : V (1 T j1.) T 1/( ) T 0.61 Badpass Flter Equvalet (4) 5B-6 Frm the kw (0.61), BWf / 1GHz/ GHz Frm the Fg.8-9 (b) 3dB pt fr f < f 0 at f m 0.4 GHz fr f >f 0 at f max.19 GHz, BW f max -f m 1.79 GHz The equvalet badpass flter aalyss allw us t expla the respse f the matchg etwrk ear f 0 Fg.8-8(c) Fg.8-9(b)

4 Ndal ualty Factr (1) The equvalet badpass flter aalyss s cmplcated > a smpler methd f estmatg the qualty factr s called dal qualty factr. At each de f the matchg etwrk the mpedace ca be expressed as a equvalet mpedace Z j r admttace Y P GP jbp > B G P P 5B-7 Z Z B Z Z Fg.8-8(c).65pF, 80 f 1 GHz Z B Z B Ndal ualty Factr () The maxmum dal qualty factr s btaed frm the pt B. B 1.3 The relat f the laded qualty factr ad dal qualty factr. 5B-8.61, 1. 3 / 0 Ths result s true fr ay -type matchg etwrk Fg.8-10 (a) Equvalet badpass flter (frm a example, t prf) The laded qualty factr f the matchg etwrk s usually estmated as the maxmum dal qualty factr

5 mth V3.10 & AD chematc Accrdg t the AD crcut respse, BW GHz f BW Frm the mth chart maxmum dal, , 1., 1.3 Ndal ualty Factr (3) m4 m4 1.3 freq 1.005GHz db((4,3))-3.344e-5 Peak 5B-9 db((4,3)) m freq 405.0MHz db((4,3)) m freq.10ghz db((4,3)) Num3 Z50 Ohm H 0.6 pf 3.6 pf 4 Num4 Z80 Ohm freq, GHz stat- turs mth hart T bta the equats fr stat- cturs, the rmalzed mpedace: Z r 1 Γ jx (1 Γ r r ) Γ Γ Γ j (1 Γ Γ r) The dal qualty factr ca be wrtte as: x Γ 1 1, Γr 1 r Γ ± 1 Γ Γ r 5B-10 1 Γr ( Γ ± 1) 1 1 ceter (0, ± 1) a crclewth radus Fg.8-11 stat turs dsplayed the mth hart

6 -matchg wth turs mth hart(1) Example 8-4 Desg -type matchg etwrks f0 1GHz Z ( 5 j0) Zs 50Ω z (0.5 j0.4) zs 1Ω 5B-11 Bth f tw -type matchg etwrks have the same maxmum dal qualty factr 1 BW f / f / GHz 0 Fg.8-11(b)() Impedace Trasfrmat the mth hart -matchg wth turs mth hart() 5B-1 Fg.8-11(a) Impedace Trasfrmat the mth hart Nte: -type matchg cat determe the ad badwdth.

7 mth V3.10 -matchg wth turs mth hart(3) 5B-13 Z Z Z Z AD chematc -matchg wth turs mth hart(4) ( BW f / f / GHz /1 GHz) 0.0 Frm AD BW 1.995GHz GHz 5B Nu Z50 Ohm pf 0.8 H 3.18 H Num Z5 Ohm db((,1)) freq 1.000GHz db((,1))-1.116e-6 Max m freq 1.955GHz db((,1)) freq, GHz m BW.4GHz GHz( f / ) 3 Num3 Z50 Ohm H 3.54 pf H 4 Num4 Z5 Ohm

8 T-matchg wth turs mth hart (1) 5B-15 Because -type matchg etwrks prvde ctrl ver the value f > Itrduce the 3rd elemet the matchg etwrk T ad π matchg etwrk >The extra f freedm t adjust the qualty factr (badwdth) Example 8-5 Desg the T-mathcg etwrk wth determed f0 1GHz Z ( 60 j0) Ω 0 / 60 1/ 3 ; Z ( 10 j0) Ω 0 /10 If the dal qualty factr s set t be 3 Fg.8-15 Desg f a T-type matchg etwrk fr a specfed 3 T-matchg wth turs mth hart () 5B-16 mth V3.10 & AD chematc Accrdg t the dal qualty factr 3, f 1.5, BW 0.67 GHz Accrdg t the AD crcut respse, BW GHz db((,1)) - freq 685.0MHz db((,1)) m freq 1.75GHz db((,1)) m Nu 7.85 H Z(10-j*0) Ohm pf 3.53 pf Num Z(60-j*30) Ohm freq, GHz

9 π -matchg wth turs mth hart(1) 5B-17 ce the lad ad put mpedaces are fxed, we cat prduce a matchg etwrk that has a qualty factr lwer tha the hghest. Example 8-5 Desg the π -mathcg etwrk wth lwest f0. 4GHz Z Z <l> (10 (0 j10) j40) / / 1 ce the lad ad put mpedaces are fxed > we cat prduce a matchg etwrk that has a qualty factr lwer tha the hghest. Fg.8-17 π-type matchg etwrk fgurat π -matchg wth turs mth hart() 5B-18 The badwdth cat be creased arbtrarly by reducg the dal factr. The lmts are set by the desred cmplex put ad utput mpedaces. f0. 4GHz Z Z (10 (0 j10) j40) / / 1 Fg.8-17 Desg f a π-type matchg etwrk usg mmal

10 π-matchg wth turs mth hart () 5B-19 mth V3.10 & AD chematc Accrdg t the dal qualty factr,.4 f 1, BW.4GHz 1 Accrdg t the AD crcut respse, BW GHz 0-1 freq.395ghz db((,1))-7.60e-6 Peak db((,1)) m freq 1.760GHz db((,1)) m m4 freq 4.355GHz db((,1)) m Nu Z(0-j*40) Ohm pf 1.66 H 1.31 H Num Z(10-j*10) O freq, GHz clus ce -type matchg etwrks prvde ctrl ver the value f, > We ca trduce the 3rd elemet the matchg etwrk T &π matchg etwrk The extra f freedm t adjust the qualty factr (badwdth) f matchg etwrk cmes at the expese f a addtal crcut elemet. The badwdth cat be creased arbtrarly by reducg the dal factr. > The lmts are set by the desred cmplex put ad utput mpedaces. 5B-0

Ch5 Appendix Q-factor and Smith Chart Matching

Ch5 Appendix Q-factor and Smith Chart Matching Ch5 Appedx -factr ad mth Chart Matchg 5B-1 We-Cha a udwg, F Crcut Deg hery ad Applcat, Chapter 8 -type matchg etwrk w-cmpet Matchg Netwrk hee etwrk ue tw reactve cmpet t trafrm the lad mpedace t the dered

More information

POWER AMPLIFIERS. 1. Explain what are classes A, B, AB and C amplifiers in terms of DC biasing using a MOSFET drain characteristic.

POWER AMPLIFIERS. 1. Explain what are classes A, B, AB and C amplifiers in terms of DC biasing using a MOSFET drain characteristic. CTONIC 3 XCI OW AMII. xpla what are classes A, B, AB and C amplifiers terms f DC biasg usg a MOT dra characteristic.. efer t the graphs f page and the table at the tp f page 3 f the thery ntes t answer

More information

Feedback Principle :-

Feedback Principle :- Feedback Prncple : Feedback amplfer s that n whch a part f the utput f the basc amplfer s returned back t the nput termnal and mxed up wth the nternal nput sgnal. The sub netwrks f feedback amplfer are:

More information

Introduction to Electronic circuits.

Introduction to Electronic circuits. Intrductn t Electrnc crcuts. Passve and Actve crcut elements. Capactrs, esstrs and Inductrs n AC crcuts. Vltage and current dvders. Vltage and current surces. Amplfers, and ther transfer characterstc.

More information

Circuits Op-Amp. Interaction of Circuit Elements. Quick Check How does closing the switch affect V o and I o?

Circuits Op-Amp. Interaction of Circuit Elements. Quick Check How does closing the switch affect V o and I o? Crcuts Op-Amp ENGG1015 1 st Semester, 01 Interactn f Crcut Elements Crcut desgn s cmplcated by nteractns amng the elements. Addng an element changes vltages & currents thrughut crcut. Example: clsng a

More information

IGEE 401 Power Electronic Systems. Solution to Midterm Examination Fall 2004

IGEE 401 Power Electronic Systems. Solution to Midterm Examination Fall 2004 Jós, G GEE 401 wer Electrnc Systems Slutn t Mdterm Examnatn Fall 2004 Specal nstructns: - Duratn: 75 mnutes. - Materal allwed: a crb sheet (duble sded 8.5 x 11), calculatr. - Attempt all questns. Make

More information

Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques Data Mg: cepts ad Techques 3 rd ed. hapter 10 1 Evaluat f lusterg lusterg evaluat assesses the feasblty f clusterg aalyss a data set ad the qualty f the results geerated by a clusterg methd. Three mar

More information

The Simple Linear Regression Model: Theory

The Simple Linear Regression Model: Theory Chapter 3 The mple Lear Regress Mdel: Ther 3. The mdel 3.. The data bservats respse varable eplaatr varable : : Plttg the data.. Fgure 3.: Dsplag the cable data csdered b Che at al (993). There are 79

More information

Copyright Paul Tobin 63

Copyright Paul Tobin 63 DT, Kevin t. lectric Circuit Thery DT87/ Tw-Prt netwrk parameters ummary We have seen previusly that a tw-prt netwrk has a pair f input terminals and a pair f utput terminals figure. These circuits were

More information

EE 221 Practice Problems for the Final Exam

EE 221 Practice Problems for the Final Exam EE 1 Practce Prblems fr the Fnal Exam 1. The netwrk functn f a crcut s 1.5 H. ω 1+ j 500 Ths table recrds frequency respnse data fr ths crcut. Fll n the blanks n the table:. The netwrk functn f a crcut

More information

CTN 2/23/16. EE 247B/ME 218: Introduction to MEMS Design Lecture 11m2: Mechanics of Materials. Copyright 2016 Regents of the University of California

CTN 2/23/16. EE 247B/ME 218: Introduction to MEMS Design Lecture 11m2: Mechanics of Materials. Copyright 2016 Regents of the University of California Vlume Change fr a Unaxal Stress Istrpc lastcty n 3D Istrpc = same n all drectns The cmplete stress-stran relatns fr an strpc elastc Stresses actng n a dfferental vlume element sld n 3D: (.e., a generalzed

More information

EE 204 Lecture 25 More Examples on Power Factor and the Reactive Power

EE 204 Lecture 25 More Examples on Power Factor and the Reactive Power EE 204 Lecture 25 Mre Examples n Pwer Factr and the Reactve Pwer The pwer factr has been defned n the prevus lecture wth an example n pwer factr calculatn. We present tw mre examples n ths lecture. Example

More information

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II CEE49b Chapter - Free Vbrato of Mult-Degree-of-Freedom Systems - II We ca obta a approxmate soluto to the fudametal atural frequecy through a approxmate formula developed usg eergy prcples by Lord Raylegh

More information

CHAPTER 5. Solutions for Exercises

CHAPTER 5. Solutions for Exercises HAPTE 5 Slutins fr Exercises E5. (a We are given v ( t 50 cs(00π t 30. The angular frequency is the cefficient f t s we have ω 00π radian/s. Then f ω / π 00 Hz T / f 0 ms m / 50 / 06. Furthermre, v(t attains

More information

Continuous-Time Filters

Continuous-Time Filters tuute Flter.0 Operatal Tracductace Aplfer (OTA Z Z ut (a (b (c (d Fgure. deal all gal equvalet crcut f Sgle eded OTA ad Fully dfferetal OTA pleetat Ug Sgle eded OTA. Fgure (a h the ybl f gle eded OTA.

More information

E o and the equilibrium constant, K

E o and the equilibrium constant, K lectrchemical measuremets (Ch -5 t 6). T state the relati betwee ad K. (D x -b, -). Frm galvaic cell vltage measuremet (a) K sp (D xercise -8, -) (b) K sp ad γ (D xercise -9) (c) K a (D xercise -G, -6)

More information

55:041 Electronic Circuits

55:041 Electronic Circuits 55:04 Electrnc Crcuts Feedback & Stablty Sectns f Chapter 2. Kruger Feedback & Stablty Cnfguratn f Feedback mplfer S S S S fb Negate feedback S S S fb S S S S S β s the feedback transfer functn Implct

More information

The fuzzy decision of transformer economic operation

The fuzzy decision of transformer economic operation The fuzzy decs f trasfrmer ecmc perat WENJUN ZHNG, HOZHONG CHENG, HUGNG XIONG, DEXING JI Departmet f Electrcal Egeerg hagha Jatg Uversty 954 Huasha Rad, 3 hagha P. R. CHIN bstract: - Ths paper presets

More information

MODULE TITLE : ELECTRONICS TOPIC TITLE : AMPLIFIERS LESSON 1 : FEEDBACK

MODULE TITLE : ELECTRONICS TOPIC TITLE : AMPLIFIERS LESSON 1 : FEEDBACK MODULE TITLE : ELECTONICS TOPIC TITLE : AMPLIFIES LESSON : FEEDBACK EL - 3 - INTODUCTION This lessn trduces the ideas f negative feedback, which we shw can vercme the disadvantages f wide parameter variat

More information

Fourier Analysis, Low Pass Filters, Decibels

Fourier Analysis, Low Pass Filters, Decibels Lecture 8 Furier Analysis, Lw Pass Filters, Decibels ELECTRICAL ENGINEERING: PRINCIPLES AND APPLICATIONS, Furth Edit, by Allan R. Hambley, 008 Pearsn Educat, Inc. Chapter 6 Frequency Respnse, Bde Plts,

More information

CIRCUIT ANALYSIS II Chapter 1 Sinusoidal Alternating Waveforms and Phasor Concept. Sinusoidal Alternating Waveforms and

CIRCUIT ANALYSIS II Chapter 1 Sinusoidal Alternating Waveforms and Phasor Concept. Sinusoidal Alternating Waveforms and U ANAYSS hapter Snusdal Alternatng Wavefrs and Phasr ncept Snusdal Alternatng Wavefrs and Phasr ncept ONNS. Snusdal Alternatng Wavefrs.. General Frat fr the Snusdal ltage & urrent.. Average alue..3 ffectve

More information

Revision: August 19, E Main Suite D Pullman, WA (509) Voice and Fax

Revision: August 19, E Main Suite D Pullman, WA (509) Voice and Fax .7.4: Direct frequency dmain circuit analysis Revisin: August 9, 00 5 E Main Suite D Pullman, WA 9963 (509) 334 6306 ice and Fax Overview n chapter.7., we determined the steadystate respnse f electrical

More information

Exergy Analysis of Large ME-TVC Desalination System

Exergy Analysis of Large ME-TVC Desalination System Exergy Aalyss f arge ME-V esalat System Awar O. Bamer Water & Eergy Prgram\Research rectrate Kuwat udat fr the Advacemet f Sceces (KAS) he 0 th Gulf Water ferece, -4 Aprl 0, ha- Qatar Outles Itrduct Prcess

More information

Load Frequency Control in Interconnected Power System Using Modified Dynamic Neural Networks

Load Frequency Control in Interconnected Power System Using Modified Dynamic Neural Networks Prceedgs f the 5th Medterraea Cferece Ctrl & Autmat, July 7-9, 007, Athes - Greece 6-0 Lad Frequecy Ctrl tercected Pwer System Usg Mdfed Dyamc Neural Netwrks K.Sabah, M.A.Neku, M.eshehlab, M.Alyar ad M.Masur

More information

CHAPTER 3: FEEDBACK. Dr. Wan Mahani Hafizah binti Wan Mahmud

CHAPTER 3: FEEDBACK. Dr. Wan Mahani Hafizah binti Wan Mahmud CHPTER 3: FEEDBCK Dr. Wan Mahan Hafzah bnt Wan Mahmud Feedback ntrductn Types f Feedback dvantages, Characterstcs and effect f Negatve Feedback mplfers Crcuts wth negatve feedback Pstve feedback and Oscllatr

More information

Applying Kirchoff s law on the primary circuit. V = - e1 V+ e1 = 0 V.D. e.m.f. From the secondary circuit e2 = v2. K e. Equivalent circuit :

Applying Kirchoff s law on the primary circuit. V = - e1 V+ e1 = 0 V.D. e.m.f. From the secondary circuit e2 = v2. K e. Equivalent circuit : TRANSFORMERS Definitin : Transfrmers can be defined as a static electric machine which cnverts electric energy frm ne ptential t anther at the same frequency. It can als be defined as cnsists f tw electric

More information

Newton s Power Flow algorithm

Newton s Power Flow algorithm Power Egeerg - Egll Beedt Hresso ewto s Power Flow algorthm Power Egeerg - Egll Beedt Hresso The ewto s Method of Power Flow 2 Calculatos. For the referece bus #, we set : V = p.u. ad δ = 0 For all other

More information

SIMULATION OF THREE PHASE THREE LEG TRANSFORMER BEHAVIOR UNDER DIFFERENT VOLTAGE SAG TYPES

SIMULATION OF THREE PHASE THREE LEG TRANSFORMER BEHAVIOR UNDER DIFFERENT VOLTAGE SAG TYPES SIMULATION OF THREE PHASE THREE LEG TRANSFORMER BEHAVIOR UNDER DIFFERENT VOLTAGE SAG TYPES Mhammadreza Dlatan Alreza Jallan Department f Electrcal Engneerng, Iran Unversty f scence & Technlgy (IUST) e-mal:

More information

Lecture 2. Basic Semiconductor Physics

Lecture 2. Basic Semiconductor Physics Lecture Basc Semcductr Physcs I ths lecture yu wll lear: What are semcductrs? Basc crystal structure f semcductrs Electrs ad hles semcductrs Itrsc semcductrs Extrsc semcductrs -ded ad -ded semcductrs Semcductrs

More information

The number of observed cases The number of parameters. ith case of the dichotomous dependent variable. the ith case of the jth parameter

The number of observed cases The number of parameters. ith case of the dichotomous dependent variable. the ith case of the jth parameter LOGISTIC REGRESSION Notato Model Logstc regresso regresses a dchotomous depedet varable o a set of depedet varables. Several methods are mplemeted for selectg the depedet varables. The followg otato s

More information

COMPLEX FREQUENCY TRANSFORMATIONS FOR DSP APPLICATIONS

COMPLEX FREQUENCY TRANSFORMATIONS FOR DSP APPLICATIONS COPLEX FREQUECY TRASFORATIOS FOR DSP APPLICATIOS 3 Artur Kruws, Iet Kale ad Gerald D. Ca 3 Uversty f Westmster, Appled DSP ad VLSI Research Grup, Ld, Uted Kgdm. atal Cetre fr Scetfc Research Demrts, Athes,

More information

G S Power Flow Solution

G S Power Flow Solution G S Power Flow Soluto P Q I y y * 0 1, Y y Y 0 y Y Y 1, P Q ( k) ( k) * ( k 1) 1, Y Y PQ buses * 1 P Q Y ( k1) *( k) ( k) Q Im[ Y ] 1 P buses & Slack bus ( k 1) *( k) ( k) Y 1 P Re[ ] Slack bus 17 Calculato

More information

Waveshapping Circuits and Data Converters. Lesson #17 Comparators and Schmitt Triggers Section BME 373 Electronics II J.

Waveshapping Circuits and Data Converters. Lesson #17 Comparators and Schmitt Triggers Section BME 373 Electronics II J. Waeshappg Crcuts and Data Cnerters Lessn #7 Cmparatrs and Schmtt Trggers Sectn. BME 7 Electrncs II 0 Waeshappg Crcuts and Data Cnerters Cmparatrs and Schmtt Trggers Astable Multbratrs and Tmers ectfers,

More information

Module B3. VLoad = = V S V LN

Module B3. VLoad = = V S V LN Mdule B Prblem The -hase lads are cnnected n arallel. One s a urely resste lad cnnected n wye. t cnsumes 00kW. The secnd s a urely nducte 00kR lad cnnected n wye. The thrd s a urely caacte 00kR lad cnnected

More information

Goal of the Lecture. Lecture Structure. FWF 410: Analysis of Habitat Data I: Definitions and Descriptive Statistics

Goal of the Lecture. Lecture Structure. FWF 410: Analysis of Habitat Data I: Definitions and Descriptive Statistics FWF : Aalyss f Habtat Data I: Defts ad Descrptve tatstcs Number f Cveys A A B Bur Dsk Bur/Dsk Habtat Treatmet Matthew J. Gray, Ph.D. Cllege f Agrcultural ceces ad Natural Resurces Uversty f Teessee-Kvlle

More information

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR Pot Patter Aalyss Part I Outle Revst IRP/CSR, frst- ad secod order effects What s pot patter aalyss (PPA)? Desty-based pot patter measures Dstace-based pot patter measures Revst IRP/CSR Equal probablty:

More information

, where. This is a highpass filter. The frequency response is the same as that for P.P.14.1 RC. Thus, the sketches of H and φ are shown below.

, where. This is a highpass filter. The frequency response is the same as that for P.P.14.1 RC. Thus, the sketches of H and φ are shown below. hapter 4, Slutn. H ( H(, where H π H ( φ H ( tan - ( Th a hghpa lter. The requency repne the ame a that r P.P.4. except that. Thu, the ketche H and φ are hwn belw. H.77 / φ 9 45 / hapter 4, Slutn. H(,

More information

Square law expression is non linear between I D and V GS. Need to operate in appropriate region for linear behaviour. W L

Square law expression is non linear between I D and V GS. Need to operate in appropriate region for linear behaviour. W L MOS Feld-Effec Trassrs (MOSFETs ecure # 4 MOSFET as a Amplfer k ( S Square law express s lear bewee ad. Need perae apprprae reg fr lear behaur. Cpyrgh 004 by Oxfrd Uersy Press, c. MOSFET as a Amplfer S

More information

Analysis of a Positive Output Super-Lift Luo Boost Converter

Analysis of a Positive Output Super-Lift Luo Boost Converter Ausha eade et al. t. Jural f Egeerg esearch ad Applicats SSN: 8-96, l. 6, ssue, (Part - 5) February 06, pp.7-78 ESEACH ACE www.ijera.cm OPEN ACCESS Aalys f a Psitive Output Super-ift u Bst Cverter Ausha

More information

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

More information

Definition of Strain. Tutorial

Definition of Strain. Tutorial Defit f Stra Tutrial Part 1. Defit f Stra Stra is the parameter used t quantify the defrmat f an bject. In igure 1B and 1C, ppsg frces are applied t each end f a rd with an rigal length f L. The applied

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

PY3101 Optics. Learning objectives. Wave propagation in anisotropic media Poynting walk-off The index ellipsoid Birefringence. The Index Ellipsoid

PY3101 Optics. Learning objectives. Wave propagation in anisotropic media Poynting walk-off The index ellipsoid Birefringence. The Index Ellipsoid The Ide Ellpsd M.P. Vaugha Learg bjectves Wave prpagat astrpc meda Ptg walk-ff The de ellpsd Brefrgece 1 Wave prpagat astrpc meda The wave equat Relatve permttvt I E. Assumg free charges r currets E. Substtutg

More information

Quantum Mechanics for Scientists and Engineers. David Miller

Quantum Mechanics for Scientists and Engineers. David Miller Quatum Mechaics fr Scietists ad Egieers David Miller Time-depedet perturbati thery Time-depedet perturbati thery Time-depedet perturbati basics Time-depedet perturbati thery Fr time-depedet prblems csider

More information

Uniform DFT Filter Banks 1/27

Uniform DFT Filter Banks 1/27 .. Ufor FT Flter Baks /27 Ufor FT Flter Baks We ll look at 5 versos of FT-based flter baks all but the last two have serous ltatos ad are t practcal. But they gve a ce trasto to the last two versos whch

More information

5.2 Single-Stub Tuning

5.2 Single-Stub Tuning 3/26/29 5_2 Sgle_Stub Tung.doc 1/1 5.2 Sgle-Stub Tung Readg Assignment: pp. 228-235 Q: If we cannot use lumped elements like ductors or capacitors to build lossless matchg networks, what can we use? A:

More information

1. Transformer A transformer is used to obtain the approximate output voltage of the power supply. The output of the transformer is still AC.

1. Transformer A transformer is used to obtain the approximate output voltage of the power supply. The output of the transformer is still AC. PHYSIS 536 Experiment 4: D Pwer Supply I. Intrductin The prcess f changing A t D is investigated in this experiment. An integrated circuit regulatr makes it easy t cnstruct a high-perfrmance vltage surce

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

Exercises for Frequency Response. ECE 102, Winter 2011, F. Najmabadi

Exercises for Frequency Response. ECE 102, Winter 2011, F. Najmabadi Eercses r Frequency espnse EE 0, Wnter 0, F. Najabad Eercse : A Mdy the crcut belw t nclude a dnant ple at 00 Mz ( 00 Ω, k, k, / 00 Ω, λ 0, and nre nternal capactances the MOS. pute the dnant ple n the

More information

KLT Tracker. Alignment. 1. Detect Harris corners in the first frame. 2. For each Harris corner compute motion between consecutive frames

KLT Tracker. Alignment. 1. Detect Harris corners in the first frame. 2. For each Harris corner compute motion between consecutive frames KLT Tracker Tracker. Detect Harrs corers the frst frame 2. For each Harrs corer compute moto betwee cosecutve frames (Algmet). 3. Lk moto vectors successve frames to get a track 4. Itroduce ew Harrs pots

More information

Improved Expression for Intensity Noise in Subcarrier Multiplexed Fiber Networks

Improved Expression for Intensity Noise in Subcarrier Multiplexed Fiber Networks 53 mprved Express fr testy Nse Subcarrer Multplexed Fber Netwrks Xaver Ferad* ad Hatce Ksek SRAMT, epartmet f Electrcal ad Cmputer Egeerg Ryers Uversty, Trt, Otar, Caada Tel: -46-979-5000 ext.6077; Fax:

More information

6.4.5 MOS capacitance-voltage analysis

6.4.5 MOS capacitance-voltage analysis 6.4.5 MOS capactace-voltage aalyss arous parameters of a MOS devce ca be determed from the - characterstcs.. Type of substrate dopg. Isulator capactace = /d sulator thckess d 3. The mmum depleto capactace

More information

Faculty of Engineering

Faculty of Engineering Faculty f Engneerng DEPARTMENT f ELECTRICAL AND ELECTRONIC ENGINEERING EEE 223 Crcut Thery I Instructrs: M. K. Uygurğlu E. Erdl Fnal EXAMINATION June 20, 2003 Duratn : 120 mnutes Number f Prblems: 6 Gd

More information

A tighter lower bound on the circuit size of the hardest Boolean functions

A tighter lower bound on the circuit size of the hardest Boolean functions Electroc Colloquum o Computatoal Complexty, Report No. 86 2011) A tghter lower boud o the crcut sze of the hardest Boolea fuctos Masak Yamamoto Abstract I [IPL2005], Fradse ad Mlterse mproved bouds o the

More information

DISTURBANCE TERMS. is a scalar and x i

DISTURBANCE TERMS. is a scalar and x i DISTURBANCE TERMS I a feld of research desg, we ofte have the qesto abot whether there s a relatoshp betwee a observed varable (sa, ) ad the other observed varables (sa, x ). To aswer the qesto, we ma

More information

NONLINEAR CONTROL OF BOOST AC/DC CONVERTERS OUTPUT VOLTAGE REGULATION AND POWER FACTOR CORRECTION. Abdelmajid ABOULOIFA, Fouad GIRI, Ibtissam LACHKAR

NONLINEAR CONTROL OF BOOST AC/DC CONVERTERS OUTPUT VOLTAGE REGULATION AND POWER FACTOR CORRECTION. Abdelmajid ABOULOIFA, Fouad GIRI, Ibtissam LACHKAR NONLINEAR CONTROL OF BOOST AC/DC CONVERTERS OUTPUT VOLTAGE REGULATION AND POWER FACTOR CORRECTION Abdelmajd ABOULOIFA, Fuad GIRI, Ibtssam LACHKAR GREYC, ISMRA, 6 Bd Maréchal Ju, 4050 Cae Abstract: We are

More information

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled

More information

Synchronous Motor V-Curves

Synchronous Motor V-Curves Synchrnus Mtr V-Curves 1 Synchrnus Mtr V-Curves Intrductin Synchrnus mtrs are used in applicatins such as textile mills where cnstant speed peratin is critical. Mst small synchrnus mtrs cntain squirrel

More information

A Method for Damping Estimation Based On Least Square Fit

A Method for Damping Estimation Based On Least Square Fit Amerca Joural of Egeerg Research (AJER) 5 Amerca Joural of Egeerg Research (AJER) e-issn: 3-847 p-issn : 3-936 Volume-4, Issue-7, pp-5-9 www.ajer.org Research Paper Ope Access A Method for Dampg Estmato

More information

D.S.G. POLLOCK: TOPICS IN TIME-SERIES ANALYSIS STATISTICAL FOURIER ANALYSIS

D.S.G. POLLOCK: TOPICS IN TIME-SERIES ANALYSIS STATISTICAL FOURIER ANALYSIS STATISTICAL FOURIER ANALYSIS The Furier Represetati f a Sequece Accrdig t the basic result f Furier aalysis, it is always pssible t apprximate a arbitrary aalytic fucti defied ver a fiite iterval f the

More information

Ahmed Elgamal. MDOF Systems & Modal Analysis

Ahmed Elgamal. MDOF Systems & Modal Analysis DOF Systems & odal Aalyss odal Aalyss (hese otes cover sectos from Ch. 0, Dyamcs of Structures, Al Chopra, Pretce Hall, 995). Refereces Dyamcs of Structures, Al K. Chopra, Pretce Hall, New Jersey, ISBN

More information

MEASURES OF DISPERSION

MEASURES OF DISPERSION MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda

More information

Signal,autocorrelation -0.6

Signal,autocorrelation -0.6 Sgal,autocorrelato Phase ose p/.9.3.7. -.5 5 5 5 Tme Sgal,autocorrelato Phase ose p/.5..7.3 -. -.5 5 5 5 Tme Sgal,autocorrelato. Phase ose p/.9.3.7. -.5 5 5 5 Tme Sgal,autocorrelato. Phase ose p/.8..6.

More information

Laboratory #2: Introduction to Microstripline Transmission Lines, Reflection and Transmission Coefficients, and S-Parameters

Laboratory #2: Introduction to Microstripline Transmission Lines, Reflection and Transmission Coefficients, and S-Parameters EEE 7 La # Laratry #: Intrductin t Micrstripline Transmissin Lines, Reflectin and Transmissin Cefficients, and -Parameters I. OBJECTIVE A micrstrip transmissin line is designed fr nminally 50Ω. The reflectin

More information

ECE 2100 Circuit Analysis

ECE 2100 Circuit Analysis ECE 00 Circuit Analysis Lessn 6 Chapter 4 Sec 4., 4.5, 4.7 Series LC Circuit C Lw Pass Filter Daniel M. Litynski, Ph.D. http://hmepages.wmich.edu/~dlitynsk/ ECE 00 Circuit Analysis Lessn 5 Chapter 9 &

More information

Lesson #14. Section BME 373 Electronics II J.Schesser

Lesson #14. Section BME 373 Electronics II J.Schesser Feedback and Oscillatrs Lessn #4 Impedances Sectin 9.35 65 Types f ffeedback Type f ffeedback k(the utput tentity fed dback): Vltage Feedback s. Current Feedback β s. β Hw it is achieed (the means t fed

More information

Section I5: Feedback in Operational Amplifiers

Section I5: Feedback in Operational Amplifiers Sectin I5: eedback in Operatinal mplifiers s discussed earlier, practical p-amps hae a high gain under dc (zer frequency) cnditins and the gain decreases as frequency increases. This frequency dependence

More information

Part a: Writing the nodal equations and solving for v o gives the magnitude and phase response: tan ( 0.25 )

Part a: Writing the nodal equations and solving for v o gives the magnitude and phase response: tan ( 0.25 ) + - Hmewrk 0 Slutin ) In the circuit belw: a. Find the magnitude and phase respnse. b. What kind f filter is it? c. At what frequency is the respnse 0.707 if the generatr has a ltage f? d. What is the

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

Chapter 5. Root Locus Techniques

Chapter 5. Root Locus Techniques Chapter 5 Rt Lcu Techique Itrducti Sytem perfrmace ad tability dt determied dby cled-lp l ple Typical cled-lp feedback ctrl ytem G Ope-lp TF KG H Zer -, - Ple 0, -, - K Lcati f ple eaily fud Variati f

More information

Coupled Inductors and Transformers

Coupled Inductors and Transformers Cupled nductrs and Transfrmers Self-nductance When current i flws thrugh the cil, a magnetic flux is prduced arund it. d d di di v= = = dt di dt dt nductance: = d di This inductance is cmmnly called self-inductance,

More information

Multiple Regression. More than 2 variables! Grade on Final. Multiple Regression 11/21/2012. Exam 2 Grades. Exam 2 Re-grades

Multiple Regression. More than 2 variables! Grade on Final. Multiple Regression 11/21/2012. Exam 2 Grades. Exam 2 Re-grades STAT 101 Dr. Kar Lock Morga 11/20/12 Exam 2 Grades Multple Regresso SECTIONS 9.2, 10.1, 10.2 Multple explaatory varables (10.1) Parttog varablty R 2, ANOVA (9.2) Codtos resdual plot (10.2) Trasformatos

More information

Physics 114 Exam 2 Fall Name:

Physics 114 Exam 2 Fall Name: Physcs 114 Exam Fall 015 Name: For gradg purposes (do ot wrte here): Questo 1. 1... 3. 3. Problem Aswer each of the followg questos. Pots for each questo are dcated red. Uless otherwse dcated, the amout

More information

Fields and Waves I. Lecture 3

Fields and Waves I. Lecture 3 Fields and Waves I ecture 3 Input Impedance n Transmissin ines K. A. Cnnr Electrical, Cmputer, and Systems Engineering Department Rensselaer Plytechnic Institute, Try, NY These Slides Were Prepared by

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON430 Statstcs Date of exam: Frday, December 8, 07 Grades are gve: Jauary 4, 08 Tme for exam: 0900 am 00 oo The problem set covers 5 pages Resources allowed:

More information

means the first term, a2 means the term, etc. Infinite Sequences: follow the same pattern forever.

means the first term, a2 means the term, etc. Infinite Sequences: follow the same pattern forever. 9.4 Sequeces ad Seres Pre Calculus 9.4 SEQUENCES AND SERIES Learg Targets:. Wrte the terms of a explctly defed sequece.. Wrte the terms of a recursvely defed sequece. 3. Determe whether a sequece s arthmetc,

More information

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table.

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table. CURVE FITTING Obectve curve ttg s t represet set dscrete dt b uct curve. Csder set dscrete dt s gve tble. 3 3 = T use the dt eectvel, curve epress s tted t the gve dt set, s = + = + + = e b ler uct plml

More information

Experiment 3 Inductors and Transformers

Experiment 3 Inductors and Transformers ENGR-4300 prg 006 Experiment 3 Experiment 3 nductrs and Transfrmers Purpse: Partly as preparatin fr the next prject and partly t help develp a mre cmplete picture f vltage surces, we will return t cnsiderg

More information

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen.

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen. .5 x 54.5 a. x 7. 786 7 b. The raked observatos are: 7.4, 7.5, 7.7, 7.8, 7.9, 8.0, 8.. Sce the sample sze 7 s odd, the meda s the (+)/ 4 th raked observato, or meda 7.8 c. The cosumer would more lkely

More information

Lab 11 LRC Circuits, Damped Forced Harmonic Motion

Lab 11 LRC Circuits, Damped Forced Harmonic Motion Physics 6 ab ab 11 ircuits, Damped Frced Harmnic Mtin What Yu Need T Knw: The Physics OK this is basically a recap f what yu ve dne s far with circuits and circuits. Nw we get t put everything tgether

More information

Non-uniform Turán-type problems

Non-uniform Turán-type problems Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at

More information

Logistic regression (continued)

Logistic regression (continued) STAT562 page 138 Logstc regresso (cotued) Suppose we ow cosder more complex models to descrbe the relatoshp betwee a categorcal respose varable (Y) that takes o two (2) possble outcomes ad a set of p explaatory

More information

THERMAL-VACUUM VERSUS THERMAL- ATMOSPHERIC TESTS OF ELECTRONIC ASSEMBLIES

THERMAL-VACUUM VERSUS THERMAL- ATMOSPHERIC TESTS OF ELECTRONIC ASSEMBLIES PREFERRED RELIABILITY PAGE 1 OF 5 PRACTICES PRACTICE NO. PT-TE-1409 THERMAL-VACUUM VERSUS THERMAL- ATMOSPHERIC Practice: Perfrm all thermal envirnmental tests n electrnic spaceflight hardware in a flight-like

More information

( ) Thermal noise ktb (T is absolute temperature in kelvin, B is bandwidth, k is Boltzamann s constant) Shot noise

( ) Thermal noise ktb (T is absolute temperature in kelvin, B is bandwidth, k is Boltzamann s constant) Shot noise OISE Thermal oe ktb (T abolute temperature kelv, B badwdth, k Boltzama cotat) 3 k.38 0 joule / kelv ( joule /ecod watt) ( ) v ( freq) 4kTB Thermal oe refer to the ketc eergy of a body of partcle a a reult

More information

Application of Matrix Iteration for Determining the Fundamental Frequency of Vibration of a Continuous Beam

Application of Matrix Iteration for Determining the Fundamental Frequency of Vibration of a Continuous Beam Iteratal Jural f Egeerg Research ad Develpet e-issn: 78-67, p-issn : 78-8, www.jerd.c Vlue 4, Issue (Nveber ), PP. -6 Applcat f Matrx Iterat fr Deterg the Fudaetal Frequecy f Vbrat f a Ctuus Bea S. Sule,

More information

ME2142/ME2142E Feedback Control Systems. Modelling of Physical Systems The Transfer Function

ME2142/ME2142E Feedback Control Systems. Modelling of Physical Systems The Transfer Function Mdellng Physcal Systems The Transer Functn Derental Equatns U Plant Y In the plant shwn, the nput u aects the respnse the utput y. In general, the dynamcs ths respnse can be descrbed by a derental equatn

More information

ELG4139: Op Amp-based Active Filters

ELG4139: Op Amp-based Active Filters ELG439: Op Amp-baed Actve Flter Advantage: educed ze and weght, and therere paratc. Increaed relablty and mprved perrmance. Smpler degn than r pave lter and can realze a wder range unctn a well a prvdng

More information

Impedance matching concept given ZL, design a matching network to have in=0 or selected value. matching. Zin (=Z Z o )

Impedance matching concept given ZL, design a matching network to have in=0 or selected value. matching. Zin (=Z Z o ) Chapter 5 Ipedance atching and tuning 5. Matching with luped eleents -sectin atching netwrks using Sith chart 5. Single-stub tuning shunt stub, series stub 5.3 Duble-stub tuning frbidden regin 5.4 The

More information

Basics of heteroskedasticity

Basics of heteroskedasticity Sect 8 Heterskedastcty ascs f heterskedastcty We have assumed up t w ( ur SR ad MR assumpts) that the varace f the errr term was cstat acrss bservats Ths s urealstc may r mst ecmetrc applcats, especally

More information

Fuel & Advanced Combustion. Lecture Chemical Reaction

Fuel & Advanced Combustion. Lecture Chemical Reaction Fuel & Advaced Cmbust Lecture Cemcal eact Ideal Gas Mdel e deal gas equat f state s: V m m M were s te Uversal Gas Cstat (8.34 kj/kml K, M s te mlecular wegt ad s te umber f mles. Secfc teral eergy (uts:

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

LECTURES 4 AND 5 THREE-PHASE CONNECTIONS (1)

LECTURES 4 AND 5 THREE-PHASE CONNECTIONS (1) ECE 330 POWER CIRCUITS AND ELECTROMECHANICS LECTURES 4 AND 5 THREEPHASE CONNECTIONS (1) AcknwledgmentThese handuts and lecture ntes given in class are based n material frm Prf. Peter Sauer s ECE 330 lecture

More information

EE 245: Introduction to MEMS Lecture 13: Mechanics of Materials II CTN 10/6/09. Copyright 2009 Regents of the University of California

EE 245: Introduction to MEMS Lecture 13: Mechanics of Materials II CTN 10/6/09. Copyright 2009 Regents of the University of California EE 45: Intrductn t MEMS Lecture 3: Mecancs Materals II CTN 0/6/09 Materal Prpertes r MEMS MEMS Materal Prpertes (E/ρ) s acustc velcty [Mark Spearng, MIT] EE C45: Intrductn t MEMS Desgn LecM 7 C. Nguyen

More information

Design of Analog Integrated Circuits

Design of Analog Integrated Circuits Desgn f Analg Integrated Crcuts I. Amplfers Desgn f Analg Integrated Crcuts Fall 2012, Dr. Guxng Wang 1 Oerew Basc MOS amplfer structures Cmmn-Surce Amplfer Surce Fllwer Cmmn-Gate Amplfer Desgn f Analg

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted

More information

Review Problems 3. Four FIR Filter Types

Review Problems 3. Four FIR Filter Types Review Prblems 3 Fur FIR Filter Types Fur types f FIR linear phase digital filters have cefficients h(n fr 0 n M. They are defined as fllws: Type I: h(n = h(m-n and M even. Type II: h(n = h(m-n and M dd.

More information

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America SOLUTION OF SYSTEMS OF SIMULTANEOUS LINEAR EQUATIONS Gauss-Sedel Method 006 Jame Traha, Autar Kaw, Kev Mart Uversty of South Florda Uted States of Amerca kaw@eg.usf.edu Itroducto Ths worksheet demostrates

More information

Diodes Waveform shaping Circuits. Sedra & Smith (6 th Ed): Sec. 4.5 & 4.6 Sedra & Smith (5 th Ed): Sec. 3.5 & 3.6

Diodes Waveform shaping Circuits. Sedra & Smith (6 th Ed): Sec. 4.5 & 4.6 Sedra & Smith (5 th Ed): Sec. 3.5 & 3.6 des Waefrm shapng Cruts Sedra & Smth (6 th Ed): Se. 4.5 & 4.6 Sedra & Smth (5 th Ed): Se. 3.5 & 3.6 Tw-prt netwrks as buldng blks Reall: Transfer funtn f a tw-prt netwrk an be fund by slng ths rut ne.

More information

Laboratory I.10 It All Adds Up

Laboratory I.10 It All Adds Up Laboratory I. It All Adds Up Goals The studet wll work wth Rema sums ad evaluate them usg Derve. The studet wll see applcatos of tegrals as accumulatos of chages. The studet wll revew curve fttg sklls.

More information

PTAS for Bin-Packing

PTAS for Bin-Packing CS 663: Patter Matchg Algorthms Scrbe: Che Jag /9/00. Itroducto PTAS for B-Packg The B-Packg problem s NP-hard. If we use approxmato algorthms, the B-Packg problem could be solved polyomal tme. For example,

More information