Designing and Tuning RF Filters to a Prescribed Specification
|
|
- Eustacia Shields
- 5 years ago
- Views:
Transcription
1 Desigig ad Tuig RF Filters to a Prescribed ecificatio Oe for Busiess Day 8 th August 03 Dr. Richard Parry Radio Desig Ltd, hiley, West Yorkshire
2 Radio Desig Radio Desig is becomig recogised as the world leader i the desig ad maufacture of custom filter systems for cellular etworks Hardware Reair ervices ca reair 3 rd arty roducts global resece We suly filter systems to leadig cellular ifrastructure OEMs ad cellular etwork oeratig comaies worldwide Our roducts are used i some of the worlds biggest shared cellular etworks
3 What is a RF Filter? A device for isolatig a defied bad of frequecies from withi the radio sectrum We are cocered maily with mobile commuicatios chaels i the UHF bad We eed to isert or extract frequecies withi this bad without geeratig iterferece i, or receivig iterferece from systems i adjacet bads (TV, WiFi, Radio etc.)
4 Filters i ystems I a mobile commuicatios basestatio, filters are used To combie sigals from differet systems so that they ca use the same atea structure ANT f ystem Badass ystem Badass ystem ystem f f
5 Filters i ystems I a mobile commuicatios basestatio, filters are used To combie sigals from differet systems so that they ca use the same atea structure ANT f UMT Tx Badass UMT Tx Badsto UMT Rx Badass UMT Rx Badsto UMT GM f f
6 Ideal Trasfer Fuctio H j Passbad Trasmit all the ower with ero distortio Zero loss Uity gai Flat amlitude Zero hase distortio Liear hase Flat grou delay (Phase gradiet) tobad - Prevet trasmissio of all ower i the uwated bad(s) Zero gai Abrut trasitio from assbad to stobad (electivity) 0 - c 0 + c 0 H j 0 - c 0 + c Ideally we wat All or Nothig This is ot ossible!! o what is ossible?? H j V out Vi V i V out
7 Real Trasfer Fuctio H j Passbad Trasmit the maximum ossible ower with low distortio Low loss Gai close to uity Low amlitude rile Low hase distortio Liear hase over most of the bad Flat grou delay (Phase gradiet) tobad - Prevet trasmissio of as much ower as ossible i the uwated bad(s) High atteuatio tee trasitio from assbad to stobad (electivity) 0 - c 0 + c 0 H j 0 - c 0 + c igle Resoator Low loss at the cetre frequecy High Q Good hase resose close to cetre Gradual trasitio to stobad Poor electivity V i H j V out Vi L V out H ( j) + jk 0 0 K L L
8 Real Trasfer Fuctio H j Passbad Trasmit the maximum ower with low distortio Low loss Gai close to uity Low amlitude rile Low hase distortio Liear hase over most of the bad Flat grou delay (Phase gradiet) tobad - Prevet trasmissio of as much ower as ossible i the uwated bad(s) High atteuatio tee trasitio from assbad to stobad (electivity) 0 - c 0 + c 0 H j 0 - c 0 + c ouled resoators Flatter assbad (low rile) Q deeds o degree Better hase resose Better selectivity V i H j V out Vi V out
9 Real Trasfer Fuctio H j Passbad Trasmit the maximum ower with low distortio Low loss Gai close to uity Low amlitude rile Low hase distortio Liear hase over most of the bad Flat grou delay (Phase gradiet) tobad - Prevet trasmissio of as much ower as ossible i the uwated bad(s) High atteuatio tee trasitio from assbad to stobad (electivity) 0 - c 0 + c 0 H j 0 - c 0 + c No adjacet coulig Trasmissio eros Imrove selectivity Target atteuatio H j V out Vi V i V out
10 Real Trasfer Fuctio H j Passbad Trasmit the maximum ower with low distortio Low loss Gai close to uity Low amlitude rile Low hase distortio Liear hase over most of the bad Flat grou delay (Phase gradiet) tobad - Prevet trasmissio of as much ower as ossible i the uwated bad(s) High atteuatio tee trasitio from assbad to stobad (electivity) 0 - c 0 + c 0 H j 0 - c 0 + c No adjacet coulig Trasmissio eros Imrove selectivity Target atteuatio H j V out Vi V i V out
11 Lowass Prototye ythesisig a lowass is easier tha sythesisig a badass A lowass filter serves as a temlate for other filter tyes We trasform its elemets to rovide the other filter tyes calig elemet values to give lowass filters with differet cut-off frequecies Traslatio ad badwidth scalig for a badass filter resose calig ad frequecy iversio for highass filters Traslatio, badwidth scalig ad frequecy iversio for badsto filters Imedace scalig L L4 Lowass Prototye Amlitude - c =- 0 + c =+ Frequecy Badass 0 0 Frequecy BP Elemet LP Prototye W 3 5 R L W P out P i () L3 ource Load Power I Power Out
12 Equirile Trasfer Fuctio Trasfer Fuctio oservatio of Eergy P P + P + P For low loss dissiated reflected Zero Loss -> Uitary oditio We use the lossless reflected ower fuctio to fid the iut imedace ad carry out the sythesis i ( j) + ( ) It s easier to measure ad alig a filter usig the reflected ower out P out + P P i reflected T N
13 Trasfer Fuctio The ratio of two olyomials ( ) K N( ) K ( )( ) ( k D( ) ( )( ) ( ) The deomiator Poles of the trasfer fuctio are ormally comlex ad ot o the imagiary axis There are the same umber of oles as there are filter elemets Numerator Fiite frequecy trasmissio eros There are the same umber of factors i the umerator as there are trasmissio ero roducig elemets Normally they occur at frequecies we ca see o a trace o the imagiary axis Trasmissio eros A filter without fiite frequecy trasmissio eros has a umerator of degree 0 ad is called a All Pole trasfer fuctio If we have oles we ca have a max eros Toology iflueces the umber of ossible eros ythesis Fid the elemet values from the trasfer fuctio Magitude <= Passive & Lossless ) W ource Power I P out L P 3 L3 i L4 5 () R L W Load Power Out
14 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
15 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
16 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
17 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
18 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
19 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
20 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
21 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
22 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
23 Poles Zeros Zeros Pole Zero Plot () & () Im j db 0-5 lowass : Grah : Mag db / Mag db 0 db e-0 e-0 3e-0 5e-0 GH Re j i d j ~ i ~ j j ~ i ~ i ji i j j ~ d j ~ i ~ j i ~ i ji
24 ythesis ythesise a lowass rototye from the trasfer fuctio Uitary coditio Lossless etwork Factorise hoose LHP oles (stability) ( j) ( ) + ( j) ( ) + ( ) ( ) Poles of are the same as oles of P iut Lossless -Port P reflected Network P trasmitted L L4 Y( ) + ( ) ( ) W 3 5 R L W L3 ource Load Power I Power Out
25 ythesis Trasform the rototye ito a badass structure of resoators ad couligs Evaluatio of circuit losses Loss does ot ecessarily eed to be uiformly distributed over the resoators everal alterative toologies ca be used to realise the same trasfer fuctio Differet toologies will have differet assbad loss variatio P iut P reflected ( j) ( ) + ( j) ( ) + ( ) Lossless -Port Network ( ) P trasmitted Y( ) + ( ) ( ) P i P out
26 ythesis Trasform the rototye ito a badass structure of resoators ad couligs Evaluatio of circuit losses Loss does ot ecessarily eed to be uiformly distributed over the resoators everal alterative toologies ca be used to realise the same trasfer fuctio Differet toologies will have differet assbad loss variatio Aroximatios to ideal elemets require otimisatio to restore trasfer fuctio P iut P reflected ( j) ( ) + ( j) ( ) + ( ) Lossless -Port Network ( ) P trasmitted Y( ) + ( ) ( ) P i P out
27 Practical Badass Filter Resoators hort circuit trasmissio lies resoated by caacitive ed loadig urface resistivity adds loss Larger resoators, smaller loss Distributed loss Passbad width affects loss Larger badwidths give smaller losses Highest loss is ormally at badedge Trasfer fuctio degree affects loss Higher degree trasfer fuctios (more resoators) result i larger losses K i K K 3 K 3 3 K 34 4 K 45 5 K 5o
28 Determie The Trasfer Fuctio (Maual Otimisatio) Passbad Isertio Loss Iut ad Outut Retur Loss tobad Frequecy/MH D Temerature Rage ystem Imedace MH 0.5 db (max) 5 db (mi) Atteuatio/dB (mi) -0 to W Fid a trasfer fuctio that fits the required assbad ad stobad temlates efficietly Determie the degree (oles) Determie the umber of trasmissio eros ad their frequecies to miimise the umber of oles Determie the uloaded Q of the resoators from the ermitted loss (ultimately determies sie) Accout for shiftig of the resose due to temerature chages Is it ossible at all!! All of this is doe maually by a exerieced desiger ie?? How do we kow that we have distributed the losses ad adjusted the trasfer fuctio to give the smallest sie With distributed sies (losses) differet etwork toologies have differet assbad loss characteristics
29 ie omariso Degree 5 Badwidth 36.0MH ( ) Tx 98.6MH Resoator Model Diam Qu Uiform Qu Qu=69 Footrit 786 mm sq K i K K 3 K 3 3 K 34 4 K 45 5 K 5o
30 ie omariso Degree 5 Badwidth 37.4MH ( ) Tx 980.0MH Resoator Model Diam Qu Uiform Qu Qu=34 Footrit 569 mm sq 7% K i K K 3 K 3 3 K 34 4 K 45 5 K 5o
31 ie omariso Degree 5 Badwidth 37.4MH ( ) Tx 980.0MH Resoator Model Diam Qu Distributed Qu Qu=73, 706, 488, 98, 73 Footrit 54 mm sq 65% K i K K 3 K 3 3 K 34 4 K 45 5 K 5o
32 ie omariso Degree 5 Badwidth 37.4MH ( ) Tx 980.0MH Resoator Model Diam Qu Distributed Qu Qu=76, 74, 87, 74, 76 Footrit 503 mm sq 64% K i K 3 3 K 34 K K 4 K K 5o
33 ie omariso Degree 5 Badwidth 38.6MH ( ) Tx 978.0, 990.6MH Resoator Model Diam Qu Distributed Qu Qu=665, 378, 35, 450, 66 Footrit 453 mm sq 57% Is this otimum?? ometimes a icrease i degree is better K i K 4 K K 34 3 K 45 K 3 K K 5o
34 Desig Process ummary (Maual Otimisatio) Re-sythesise ad evaluate ew etwork No Trasfer Fuctio Degree Badwidth Trasmissio Zero Locatios ythesis Resoator & ouligs ircuit Trasformatios Aroximatios Otimisatio Evaluatio Iclude Loss omare with ecificatio Distributio of Loss alculate ie ecificatio Met? ie Mi? Determie dimesios Verify 3D model Yes
35 3D EM imulatios/physical Device Dimesios for hysical device The Ls ad s of the circuit simulator model are ot measureable i the hysical device Resoat frequecies, coulig badwidths ad exteral Qs are measureable quatities that defie the trasfer fuctio Poles ad eros are maiulated idirectly by tuig resoat frequecies ad badwidths orrect values for these will esure correct locatio of oles ad eros ad hece the required trasfer fuctio Iitial dimesios come from these values Res Frequecy (MH) oulig Badwidth (MH) ig ve ve ve ve ve K i K 3 3 K 34 K K 4 K K 5o Ideedat Variables oles + eros + 5Resoators + 6Mai K + ross K
36 3D EM imulatios/physical Device EM Model Provides a accurate full 3D EM simulatio of the filter Relaces the eed for hackig at a rototye The EM model icludes the facility to tue resoators ad couligs as we would i reality Poles ad eros are maiulated idirectly by tuig resoat frequecies ad badwidths We tue the EM model s dimesios to a tolerace that is withi the tuig rage of the available hysical adjustmet (crews) Eables a hybrid maual/automated otimisatio techique Res Frequecy (MH) oulig Badwidth (MH) ig ve ve ve ve ve K i K 3 3 K 34 K K 4 K K 5o Ideedat Variables oles + eros + 5Resoators + 6Mai K + ross K
37 Utued Res D Frequecy (MH) oulig D Badwidth (MH) This resose is tyical of a first cut 3D EM model or ractical device Poles are ot i the required locatio Reflectio eros have moved off the imagiary axis Fiite, trasmissio eros are ot located correctly ad may actually be i-bad or off the imagiary axis This still reresets a trasfer fuctio which is a ratioal olyomial of essetially the same degree as the theoretical oe ad ca be tued to restore the desired trasfer fuctio Resoat frequecies, coulig badwidths, ad exteral Q s Measuremets ca be made (with some difficulty) Give a clue to which dimesios should be modified ad by how much
38 Pre-tued Res D Frequecy (MH) Ideedat Variables + + oulig D Badwidth (MH) oles oles eros Refl Zero Refl Rile + BE 5 Resoators + 6 Mai K + ross K This resose is tyical after iitial tuig usig resoat frequecy ad coulig badwidth iformatio Reflectio eros are all visible (rile levels) Trasmissio eros are roughly laced EM Model I this state the EM model ca be tued by mathematically otimisig the aroriate tuig elemets to give the equirile reflectio with the correct badwidth ad atteuatio riles Real Filter Withi the tuig rage of the mechaical adjusters Tued by exerieced techicia
39 Tued Res D Frequecy (MH) Ideedat Variables + + oulig D Badwidth (MH) oles oles eros Refl Zero Refl Rile + BE 5 Resoators + 6 Mai K + ross K After tuig/otimisatio All reflectio eros are visible ad the rile levels correct Badwidth is correct Trasmissio eros ositioed to give correct atteuatio rile levels Mixed distributed ad lumed elemets The oles, reflectio ad trasmissio eros locatios are ot recisely the same as the origial rototye Rile levels are more imortat Reflectio miima are ket close to ero
40 Automated Aligmet Res D Frequecy (MH) oulig D Badwidth (MH) reate the ratioal olyomial fuctios that fit the measured data,,? ythesise the etwork? Fid the resoat frequecies ad badwidths? Provide tuig guidace?
41 Fially Desig ie eeds to be miimised Distributed loss adds to desig comlexity Evaluated loss is deedat uo the etwork toology Loss caot be icluded util after sythesis Evaluated loss is a fuctio of Degree Badwidth Trasmissio ero locatios ie Loss distributio How ca we esure that the fial desig has the smallest sie Aligmet Poles ad Zeros are ot where we require Measurig resoat frequecies ad coulig badwidths is slow ad difficult i ractice The utued resose essetially still has the correct degree of umerator ad deomiator We ought to be able to fit a ratioal olyomial to measured results Higher order terms may be eeded for the fit (mixed lumed ad distributed variables) a we use the fitted olyomial to derive resoat frequecies ad coulig badwidths
732 Appendix E: Previous EEE480 Exams. Rules: One sheet permitted, calculators permitted. GWC 352,
732 Aedix E: Previous EEE0 Exams EEE0 Exam 2, Srig 2008 A.A. Rodriguez Rules: Oe 8. sheet ermitted, calculators ermitted. GWC 32, 9-372 Problem Aalysis of a Feedback System Cosider the feedback system
More information2W Wideband Microwave PA Design for MHz Band Using Normalized Gain Function Method
W Widebad Microwave PA Desig for 84-7 MHz Bad Usig Normalized ai uctio Method Ramaza Körü, Haka Kutma, ad B. S. Yarma 3 Ik Uiversity, Electrical-Electroics Eg. Det., Istabul/urkiye ramaza.koru@isiku.edu.tr
More information6.003 Homework #3 Solutions
6.00 Homework # Solutios Problems. Complex umbers a. Evaluate the real ad imagiary parts of j j. π/ Real part = Imagiary part = 0 e Euler s formula says that j = e jπ/, so jπ/ j π/ j j = e = e. Thus the
More informationEL 675 UHF Propagation for Modern Wireless Systems. Henry L. Bertoni Polytechnic University
EL 675 UHF Propagatio for Moder Wireless Systems Hery L. Bertoi Polytechic Uiversity otext for Discussig Wireless hael haracteristics Frequecies above ~ 300 MHz (λ < m) adio liks i ma-made eviromets At
More informationClassification of DT signals
Comlex exoetial A discrete time sigal may be comlex valued I digital commuicatios comlex sigals arise aturally A comlex sigal may be rereseted i two forms: jarg { z( ) } { } z ( ) = Re { z ( )} + jim {
More informationThe z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j
The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.
More informationDISTRIBUTION LAW Okunev I.V.
1 DISTRIBUTION LAW Okuev I.V. Distributio law belogs to a umber of the most complicated theoretical laws of mathematics. But it is also a very importat practical law. Nothig ca help uderstad complicated
More informationA Generalized Fractal Radiation Pattern Synthesis Technique for the Design of Multiband Arrays
A Geeralized Fractal Radiatio Patter Sythesis Techique for the Desig of Multibad Arrays D.H. Werer, M.A. Gigrich, ad P.L. Werer The Pesylvaia State Uiversity Deartmet of Electrical Egieerig Self-Similar
More informationChapter 7 z-transform
Chapter 7 -Trasform Itroductio Trasform Uilateral Trasform Properties Uilateral Trasform Iversio of Uilateral Trasform Determiig the Frequecy Respose from Poles ad Zeros Itroductio Role i Discrete-Time
More informationChapter 7: The z-transform. Chih-Wei Liu
Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability
More informationDigital Integrated Circuits
Digital Itegrated Circuits YuZhuo Fu cotact:fuyuzhuo@ic.sjtu.edu.c Office locatio:417 room WeiDiaZi buildig,no 800 DogChua road,mihag Camus Itroductio outlie CMOS at a glace CMOS static behavior CMOS dyamic
More informationRun-length & Entropy Coding. Redundancy Removal. Sampling. Quantization. Perform inverse operations at the receiver EEE
Geeral e Image Coder Structure Motio Video (s 1,s 2,t) or (s 1,s 2 ) Natural Image Samplig A form of data compressio; usually lossless, but ca be lossy Redudacy Removal Lossless compressio: predictive
More informationYuZhuo Fu Office location:417 room WeiDianZi building,no 800 DongChuan road,minhang Campus
Digital Itegrated Circuits YuZhuo Fu cotact:fuyuzhuo@ic.sjtu.edu.c Office locatio:417 room WeiDiaZi buildig,no 800 DogChua road,mihag Camus Itroductio Digital IC outlie CMOS at a glace CMOS static behavior
More informationDigital Integrated Circuits. Inverter. YuZhuo Fu. Digital IC. Introduction
Digital Itegrated Circuits Iverter YuZhuo Fu Itroductio outlie CMOS at a glace CMOS static behavior CMOS dyamic behavior Power, Eergy, ad Eergy Delay Persective tech. /48 outlie CMOS at a glace CMOS static
More informationAntenna Engineering Lecture 8: Antenna Arrays
Atea Egieerig Lecture 8: Atea Arrays ELCN45 Sprig 211 Commuicatios ad Computer Egieerig Program Faculty of Egieerig Cairo Uiversity 2 Outlie 1 Array of Isotropic Radiators Array Cofiguratios The Space
More informationJitter Transfer Functions For The Reference Clock Jitter In A Serial Link: Theory And Applications
Jitter Trasfer Fuctios For The Referece Clock Jitter I A Serial Lik: Theory Ad Applicatios Mike Li, Wavecrest Ady Martwick, Itel Gerry Talbot, AMD Ja Wilstrup, Teradye Purposes Uderstad various jitter
More informationDefinition of z-transform.
- Trasforms Frequecy domai represetatios of discretetime sigals ad LTI discrete-time systems are made possible with the use of DTFT. However ot all discrete-time sigals e.g. uit step sequece are guarateed
More informationIntroduction to Signals and Systems, Part V: Lecture Summary
EEL33: Discrete-Time Sigals ad Systems Itroductio to Sigals ad Systems, Part V: Lecture Summary Itroductio to Sigals ad Systems, Part V: Lecture Summary So far we have oly looked at examples of o-recursive
More information6.003 Homework #12 Solutions
6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] (below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F
More information6.003 Homework #12 Solutions
6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F for
More informationSinusoidal Steady-state Analysis
Siusoidal Steady-state Aalysis Complex umber reviews Phasors ad ordiary differetial equatios Complete respose ad siusoidal steady-state respose Cocepts of impedace ad admittace Siusoidal steady-state aalysis
More informationGeneralizing the DTFT. The z Transform. Complex Exponential Excitation. The Transfer Function. Systems Described by Difference Equations
Geeraliig the DTFT The Trasform M. J. Roberts - All Rights Reserved. Edited by Dr. Robert Akl 1 The forward DTFT is defied by X e jω = x e jω i which = Ω is discrete-time radia frequecy, a real variable.
More informationMechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter
Time Respose & Frequecy Respose d -Order Dyamic System -Pole, Low-Pass, Active Filter R 4 R 7 C 5 e i R 1 C R 3 - + R 6 - + e out Assigmet: Perform a Complete Dyamic System Ivestigatio of the Two-Pole,
More informationFilter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and
Filter bas Separately, the lowpass ad highpass filters are ot ivertible T removes the highest frequecy / ad removes the lowest frequecy Together these filters separate the sigal ito low-frequecy ad high-frequecy
More informationChapter 4 : Laplace Transform
4. Itroductio Laplace trasform is a alterative to solve the differetial equatio by the complex frequecy domai ( s = σ + jω), istead of the usual time domai. The DE ca be easily trasformed ito a algebraic
More informationEE 508 Lecture 6. Dead Networks Scaling, Normalization and Transformations
EE 508 Lecture 6 Dead Network Scalig, Normalizatio ad Traformatio Filter Cocept ad Termiology 2-d order polyomial characterizatio Biquadratic Factorizatio Op Amp Modelig Stability ad Itability Roll-off
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science. BACKGROUND EXAM September 30, 2004.
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Departmet of Electrical Egieerig ad Computer Sciece 6.34 Discrete Time Sigal Processig Fall 24 BACKGROUND EXAM September 3, 24. Full Name: Note: This exam is closed
More informationFIR Filter Design: Part II
EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we cosider how we might go about desigig FIR filters with arbitrary frequecy resposes, through compositio of multiple sigle-peak
More informationRegenerative Property
DESIGN OF LOGIC FAMILIES Some desirable characteristics to have: 1. Low ower dissiatio. High oise margi (Equal high ad low margis) 3. High seed 4. Low area 5. Low outut resistace 6. High iut resistace
More informationEE Control Systems
Copyright FL Lewis 7 All rights reserved Updated: Moday, November 1, 7 EE 4314 - Cotrol Systems Bode Plot Performace Specificatios The Bode Plot was developed by Hedrik Wade Bode i 1938 while he worked
More informationExperiments #6 & #7: The Operational Amplifier
EECS 40/4 Exerimets #6 & #7: The Oeratioal mlifier I. Objective The urose of these exerimets is to itroduce the most imortat of all aalog buildig blocks, the oeratioal amlifier ( o-am for short). This
More informationVoltage controlled oscillator (VCO)
Voltage cotrolled oscillator (VO) Oscillatio frequecy jl Z L(V) jl[ L(V)] [L L (V)] L L (V) T VO gai / Logf Log 4 L (V) f f 4 L(V) Logf / L(V) f 4 L (V) f (V) 3 Lf 3 VO gai / (V) j V / V Bi (V) / V Bi
More informationCh3 Discrete Time Fourier Transform
Ch3 Discrete Time Fourier Trasform 3. Show that the DTFT of [] is give by ( k). e k 3. Determie the DTFT of the two sided sigal y [ ],. 3.3 Determie the DTFT of the causal sequece x[ ] A cos( 0 ) [ ],
More informationNew Definition of Density on Knapsack Cryptosystems
Africacryt008@Casablaca 008.06.1 New Defiitio of Desity o Kasac Crytosystems Noboru Kuihiro The Uiversity of Toyo, Jaa 1/31 Kasac Scheme rough idea Public Key: asac: a={a 1, a,, a } Ecrytio: message m=m
More informationCOMM 602: Digital Signal Processing
COMM 60: Digital Sigal Processig Lecture 4 -Properties of LTIS Usig Z-Trasform -Iverse Z-Trasform Properties of LTIS Usig Z-Trasform Properties of LTIS Usig Z-Trasform -ve +ve Properties of LTIS Usig Z-Trasform
More informationThe Z-Transform. (t-t 0 ) Figure 1: Simplified graph of an impulse function. For an impulse, it can be shown that (1)
The Z-Trasform Sampled Data The geeralied fuctio (t) (also kow as the impulse fuctio) is useful i the defiitio ad aalysis of sampled-data sigals. Figure below shows a simplified graph of a impulse. (t-t
More information2.004 Dynamics and Control II Spring 2008
MIT OpeCourseWare http://ocw.mit.edu 2.004 Dyamics ad Cotrol II Sprig 2008 For iformatio about citig these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Massachusetts Istitute of Techology
More informationPolynomials with Rational Roots that Differ by a Non-zero Constant. Generalities
Polyomials with Ratioal Roots that Differ by a No-zero Costat Philip Gibbs The problem of fidig two polyomials P(x) ad Q(x) of a give degree i a sigle variable x that have all ratioal roots ad differ by
More informationComplex Numbers Solutions
Complex Numbers Solutios Joseph Zoller February 7, 06 Solutios. (009 AIME I Problem ) There is a complex umber with imagiary part 64 ad a positive iteger such that Fid. [Solutio: 697] 4i + + 4i. 4i 4i
More informationMATHEMATICAL MODELLING OF ARCH FORMATION IN GRANULAR MATERIALS
6 th INTERNATIONAL MULTIDISCIPLINARY CONFERENCE MATHEMATICAL MODELLING OF ARCH FORMATION IN GRANULAR MATERIALS Istva eppler SZIE Faculty of Mechaics, H-2103 Gödöllő Páter. 1., Hugary Abstract: The mathematical
More informationChapter 9: Numerical Differentiation
178 Chapter 9: Numerical Differetiatio Numerical Differetiatio Formulatio of equatios for physical problems ofte ivolve derivatives (rate-of-chage quatities, such as velocity ad acceleratio). Numerical
More informationLecture #18
18-1 Variatioal Method (See CTDL 1148-1155, [Variatioal Method] 252-263, 295-307[Desity Matrices]) Last time: Quasi-Degeeracy Diagoalize a part of ifiite H * sub-matrix : H (0) + H (1) * correctios for
More informationWave Phenomena Physics 15c
Wave Pheomea Physics 5c Lecture Fourier Aalysis (H&L Sectios 3. 4) (Georgi Chapter ) Admiistravia! Midterm average 68! You did well i geeral! May got the easy parts wrog, e.g. Problem (a) ad 3(a)! erm
More informationELEC1200: A System View of Communications: from Signals to Packets Lecture 3
ELEC2: A System View of Commuicatios: from Sigals to Packets Lecture 3 Commuicatio chaels Discrete time Chael Modelig the chael Liear Time Ivariat Systems Step Respose Respose to sigle bit Respose to geeral
More informationEE 508 Lecture 6. Scaling, Normalization and Transformation
EE 508 Lecture 6 Scalig, Normalizatio ad Traformatio Review from Lat Time Dead Network X IN T X OUT T X OUT N T = D D The dead etwork of ay liear circuit i obtaied by ettig ALL idepedet ource to zero.
More informationWarped, Chirp Z-Transform: Radar Signal Processing
arped, Chirp Z-Trasform: Radar Sigal Processig by Garimella Ramamurthy Report o: IIIT/TR// Cetre for Commuicatios Iteratioal Istitute of Iformatio Techology Hyderabad - 5 3, IDIA Jauary ARPED, CHIRP Z
More information10-701/ Machine Learning Mid-term Exam Solution
0-70/5-78 Machie Learig Mid-term Exam Solutio Your Name: Your Adrew ID: True or False (Give oe setece explaatio) (20%). (F) For a cotiuous radom variable x ad its probability distributio fuctio p(x), it
More informationMCT242: Electronic Instrumentation Lecture 2: Instrumentation Definitions
Faculty of Egieerig MCT242: Electroic Istrumetatio Lecture 2: Istrumetatio Defiitios Overview Measuremet Error Accuracy Precisio ad Mea Resolutio Mea Variace ad Stadard deviatio Fiesse Sesitivity Rage
More informationProperties and Hypothesis Testing
Chapter 3 Properties ad Hypothesis Testig 3.1 Types of data The regressio techiques developed i previous chapters ca be applied to three differet kids of data. 1. Cross-sectioal data. 2. Time series data.
More informationFirst, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So,
0 2. OLS Part II The OLS residuals are orthogoal to the regressors. If the model icludes a itercept, the orthogoality of the residuals ad regressors gives rise to three results, which have limited practical
More informationChapter 6: BINOMIAL PROBABILITIES
Charles Bocelet, Probability, Statistics, ad Radom Sigals," Oxford Uiversity Press, 016. ISBN: 978-0-19-00051-0 Chater 6: BINOMIAL PROBABILITIES Sectios 6.1 Basics of the Biomial Distributio 6. Comutig
More informationThe Scattering Matrix
2/23/7 The Scatterig Matrix 723 1/13 The Scatterig Matrix At low frequecies, we ca completely characterize a liear device or etwork usig a impedace matrix, which relates the currets ad voltages at each
More informationPolynomial Functions and Their Graphs
Polyomial Fuctios ad Their Graphs I this sectio we begi the study of fuctios defied by polyomial expressios. Polyomial ad ratioal fuctios are the most commo fuctios used to model data, ad are used extesively
More informationButterworth LC Filter Designer
Butterworth LC Filter Desiger R S = g g 4 g - V S g g 3 g R L = Fig. : LC filter used for odd-order aalysis g R S = g 4 g V S g g 3 g - R L = useful fuctios ad idetities Uits Costats Table of Cotets I.
More informationCork Institute of Technology Bachelor of Science (Honours) in Applied Physics and Instrumentation-Award - (NFQ Level 8)
ork Istitute of Techology Bachelor of Sciece (Hoours) i Applied Physics ad Istrumetatio-Award - (NFQ Level 8) Istructios Aswer Four questios, at least TWO questios from each Sectio. Use separate aswer
More informationEE123 Digital Signal Processing
EE123 Digital Sigal Processig Lecture 20 Filter Desig Liear Filter Desig Used to be a art Now, lots of tools to desig optimal filters For DSP there are two commo classes Ifiite impulse respose IIR Fiite
More informationx c the remainder is Pc ().
Algebra, Polyomial ad Ratioal Fuctios Page 1 K.Paulk Notes Chapter 3, Sectio 3.1 to 3.4 Summary Sectio Theorem Notes 3.1 Zeros of a Fuctio Set the fuctio to zero ad solve for x. The fuctio is zero at these
More informationSpecial Modeling Techniques
Colorado School of Mies CHEN43 Secial Modelig Techiques Secial Modelig Techiques Summary of Toics Deviatio Variables No-Liear Differetial Equatios 3 Liearizatio of ODEs for Aroximate Solutios 4 Coversio
More informationChapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io
Chapter 9 - CD compaio CHAPTER NINE CD-9.2 CD-9.2. Stages With Voltage ad Curret Gai A Geeric Implemetatio; The Commo-Merge Amplifier The advaced method preseted i the text for approximatig cutoff frequecies
More informationProblem Set 4 Due Oct, 12
EE226: Radom Processes i Systems Lecturer: Jea C. Walrad Problem Set 4 Due Oct, 12 Fall 06 GSI: Assae Gueye This problem set essetially reviews detectio theory ad hypothesis testig ad some basic otios
More information(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3
MATH 337 Sequeces Dr. Neal, WKU Let X be a metric space with distace fuctio d. We shall defie the geeral cocept of sequece ad limit i a metric space, the apply the results i particular to some special
More informationConfidence intervals for proportions
Cofidece itervals for roortios Studet Activity 7 8 9 0 2 TI-Nsire Ivestigatio Studet 60 mi Itroductio From revious activity This activity assumes kowledge of the material covered i the activity Distributio
More informationModule 11: Applications : Linear prediction, Speech Analysis and Speech Enhancement Prof. Eliathamby Ambikairajah Dr. Tharmarajah Thiruvaran School
Module : Applicatios : Liear predictio, Speech Aalysis ad Speech Ehacemet Prof. Eliathamby Ambiairajah Dr. Tharmarajah Thiruvara School of Electrical Egieerig & Telecommuicatios The Uiversity of New South
More informationCS284A: Representations and Algorithms in Molecular Biology
CS284A: Represetatios ad Algorithms i Molecular Biology Scribe Notes o Lectures 3 & 4: Motif Discovery via Eumeratio & Motif Represetatio Usig Positio Weight Matrix Joshua Gervi Based o presetatios by
More informationMicroscopic Theory of Transport (Fall 2003) Lecture 6 (9/19/03) Static and Short Time Properties of Time Correlation Functions
.03 Microscopic Theory of Trasport (Fall 003) Lecture 6 (9/9/03) Static ad Short Time Properties of Time Correlatio Fuctios Refereces -- Boo ad Yip, Chap There are a umber of properties of time correlatio
More informationMAXIMALLY FLAT FIR FILTERS
MAXIMALLY FLAT FIR FILTERS This sectio describes a family of maximally flat symmetric FIR filters first itroduced by Herrma [2]. The desig of these filters is particularly simple due to the availability
More informationDigital Integrated Circuits
Digital Itegrated Circuits YuZhuo Fu cotact:fuyuzhuo@ic.sjtu.edu.c Office locatio:417 room WeiDiaZi buildig,no 800 DogChua road,mihag Camus Itroductio Review cotet Tye Cocet 15, Comutig 10 hours Fri. 6
More informationEE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course
Sigal-EE Postal Correspodece Course 1 SAMPLE STUDY MATERIAL Electrical Egieerig EE / EEE Postal Correspodece Course GATE, IES & PSUs Sigal System Sigal-EE Postal Correspodece Course CONTENTS 1. SIGNAL
More informationFormation of A Supergain Array and Its Application in Radar
Formatio of A Supergai Array ad ts Applicatio i Radar Tra Cao Quye, Do Trug Kie ad Bach Gia Duog. Research Ceter for Electroic ad Telecommuicatios, College of Techology (Coltech, Vietam atioal Uiversity,
More information7-1. Chapter 4. Part I. Sampling Distributions and Confidence Intervals
7-1 Chapter 4 Part I. Samplig Distributios ad Cofidece Itervals 1 7- Sectio 1. Samplig Distributio 7-3 Usig Statistics Statistical Iferece: Predict ad forecast values of populatio parameters... Test hypotheses
More informationAnalog Filter Design. Part. 1: Introduction. P. Bruschi - Analog Filter Design 1
Aalog Filter Desig Part. : Itroductio P. Bruschi - Aalog Filter Desig Defiitio of Filter Electroic filters are liear circuits hose operatio is defied i the frequecy domai, i.e. they are itroduced to perform
More information10.5 Positive Term Series: Comparison Tests Contemporary Calculus 1
0. Positive Term Series: Compariso Tests Cotemporary Calculus 0. POSITIVE TERM SERIES: COMPARISON TESTS This sectio discusses how to determie whether some series coverge or diverge by comparig them with
More informationConfidence Intervals
Cofidece Itervals Berli Che Deartmet of Comuter Sciece & Iformatio Egieerig Natioal Taiwa Normal Uiversity Referece: 1. W. Navidi. Statistics for Egieerig ad Scietists. Chater 5 & Teachig Material Itroductio
More informationFrequency Domain Filtering
Frequecy Domai Filterig Raga Rodrigo October 19, 2010 Outlie Cotets 1 Itroductio 1 2 Fourier Represetatio of Fiite-Duratio Sequeces: The Discrete Fourier Trasform 1 3 The 2-D Discrete Fourier Trasform
More informationAnalog Filter Design. Part. 3: Time Continuous Filter Implementation. P. Bruschi - Analog Filter Design 1
Aalog Filter Deig Part. 3: Time otiuou Filter Implemetatio P. ruchi - Aalog Filter Deig Deig approache Paive (R) ladder filter acade of iquadratic (iquad) ad iliear cell State Variable Filter Simulatio
More informationCharacterization of anisotropic acoustic metamaterials
INTER-NOISE 06 Characteriatio of aisotropic acoustic metamaterials Ju Hyeog PARK ; Hyug Ji LEE ; Yoo Youg KIM 3 Departmet of Mechaical ad Aerospace Egieerig, Seoul Natioal Uiversity, Korea Istitute of
More informationCourse Outline. Designing Control Systems. Proportional Controller. Amme 3500 : System Dynamics and Control. Root Locus. Dr. Stefan B.
Amme 3500 : System Dyamics ad Cotrol Root Locus Course Outlie Week Date Cotet Assigmet Notes Mar Itroductio 8 Mar Frequecy Domai Modellig 3 5 Mar Trasiet Performace ad the s-plae 4 Mar Block Diagrams Assig
More informationReview of Discrete-time Signals. ELEC 635 Prof. Siripong Potisuk
Review of Discrete-time Sigals ELEC 635 Prof. Siripog Potisuk 1 Discrete-time Sigals Discrete-time, cotiuous-valued amplitude (sampled-data sigal) Discrete-time, discrete-valued amplitude (digital sigal)
More informationChapter 2. Finite Fields (Chapter 3 in the text)
Chater 2. Fiite Fields (Chater 3 i the tet 1. Grou Structures 2. Costructios of Fiite Fields GF(2 ad GF( 3. Basic Theory of Fiite Fields 4. The Miimal Polyomials 5. Trace Fuctios 6. Subfields 1. Grou Structures
More informationFig. 2. Block Diagram of a DCS
Iformatio source Optioal Essetial From other sources Spread code ge. Format A/D Source ecode Ecrypt Auth. Chael ecode Pulse modu. Multiplex Badpass modu. Spread spectrum modu. X M m i Digital iput Digital
More informationE. Bashirova, N. Svobodina THE EVALUATION OF METAL OIL AND GAS EQUIPMENT IN A CURRENT CONDITION BY MEANS OF TRANSFER FUNCTION PARAMETERS
1 УДК 62.179.14 E. Bashirova, N. Svobodia THE EVALUATION OF METAL OIL AND GAS EQUIPMENT IN A CURRENT CONDITION BY MEANS OF TRANSFER FUNCTION PARAMETERS The equiet used for oil refiig, dealig with highly
More informationOBJECTIVES. Chapter 1 INTRODUCTION TO INSTRUMENTATION FUNCTION AND ADVANTAGES INTRODUCTION. At the end of this chapter, students should be able to:
OBJECTIVES Chapter 1 INTRODUCTION TO INSTRUMENTATION At the ed of this chapter, studets should be able to: 1. Explai the static ad dyamic characteristics of a istrumet. 2. Calculate ad aalyze the measuremet
More informationNanomaterials for Photovoltaics (v11) 6. Homojunctions
Naomaterials for Photovoltaics (v11) 1 6. Homojuctios / juctio diode The most imortat device cocet for the coversio of light ito electrical curret is the / juctio diode. We first cosider isolated ad regios
More information3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,
3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [
More informationSample Size Estimation in the Proportional Hazards Model for K-sample or Regression Settings Scott S. Emerson, M.D., Ph.D.
ample ie Estimatio i the Proportioal Haards Model for K-sample or Regressio ettigs cott. Emerso, M.D., Ph.D. ample ie Formula for a Normally Distributed tatistic uppose a statistic is kow to be ormally
More informationBode Diagrams School of Mechanical Engineering ME375 Frequency Response - 29 Purdue University Example Ex:
ME375 Hadouts Bode Diagrams Recall that if m m bs m + bm s + + bs+ b Gs () as + a s + + as+ a The bm( j z)( j z) ( j zm) G( j ) a ( j p )( j p ) ( j p ) bm( s z)( s z) ( s zm) a ( s p )( s p ) ( s p )
More informationProvläsningsexemplar / Preview TECHNICAL REPORT INTERNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE
TECHNICAL REPORT CISPR 16-4-3 2004 AMENDMENT 1 2006-10 INTERNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE Amedmet 1 Specificatio for radio disturbace ad immuity measurig apparatus ad methods Part 4-3:
More informationZ - Transform. It offers the techniques for digital filter design and frequency analysis of digital signals.
Z - Trasform The -trasform is a very importat tool i describig ad aalyig digital systems. It offers the techiques for digital filter desig ad frequecy aalysis of digital sigals. Defiitio of -trasform:
More informationMath 1314 Lesson 16 Area and Riemann Sums and Lesson 17 Riemann Sums Using GeoGebra; Definite Integrals
Math 1314 Lesso 16 Area ad Riema Sums ad Lesso 17 Riema Sums Usig GeoGebra; Defiite Itegrals The secod questio studied i calculus is the area questio. If a regio coforms to a kow formula from geometry,
More informationElementary Statistics
Elemetary Statistics M. Ghamsary, Ph.D. Sprig 004 Chap 0 Descriptive Statistics Raw Data: Whe data are collected i origial form, they are called raw data. The followig are the scores o the first test of
More informationThe statistical pattern of the arrival can be indicated through the probability distribution of the number of the arrivals in an interval.
Itroductio Queuig are the most freuetly ecoutered roblems i everyday life. For examle, ueue at a cafeteria, library, bak, etc. Commo to all of these cases are the arrivals of objects reuirig service ad
More informationtests 17.1 Simple versus compound
PAS204: Lecture 17. tests UMP ad asymtotic I this lecture, we will idetify UMP tests, wherever they exist, for comarig a simle ull hyothesis with a comoud alterative. We also look at costructig tests based
More informationCONSTRUCTING TRUNCATED IRRATIONAL NUMBERS AND DETERMINING THEIR NEIGHBORING PRIMES
CONSTRUCTING TRUNCATED IRRATIONAL NUMBERS AND DETERMINING THEIR NEIGHBORING PRIMES It is well kow that there exist a ifiite set of irratioal umbers icludig, sqrt(), ad e. Such quatities are of ifiite legth
More informationDead Time compensators for Stable Processes
J. Acad. Idus. Res. Vol. 1(7) December 01 393 RESEARCH ARTICLE ISSN: 78-513 Dead Time comesators for Stable Processes Varu Sharma ad Veea Sharma Electrical Egieerig Deartmet, Natioal Istitute of Techology,
More informationTHE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS
R775 Philips Res. Repts 26,414-423, 1971' THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS by H. W. HANNEMAN Abstract Usig the law of propagatio of errors, approximated
More informationLarge Signal Analysis of Low-Voltage BiMOS Analog Multipliers Using Fourier-Series Approximations
Proc. atl. Sci. Couc. ROC(A) Vol. 4, o. 6, 000.. 480-488 (Short Commuicatio) Large Sigal Aalysis of Low-Voltage BiOS Aalog ultiliers Usig Fourier-Series Aroximatios UHAAD TAHER ABUELA ATTI ig Fahd Uiversity
More informationApply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.
Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α
More informationAppendix: The Laplace Transform
Appedix: The Laplace Trasform The Laplace trasform is a powerful method that ca be used to solve differetial equatio, ad other mathematical problems. Its stregth lies i the fact that it allows the trasformatio
More informationExponential Moving Average Pieter P
Expoetial Movig Average Pieter P Differece equatio The Differece equatio of a expoetial movig average lter is very simple: y[] x[] + (1 )y[ 1] I this equatio, y[] is the curret output, y[ 1] is the previous
More informationCrash course part 2. Frequency compensation
Crash course part Frequecy compesatio Ageda Frequecy depedace Feedback amplifiers Frequecy depedace of the Trasistor Frequecy Compesatio Phatom Zero Examples Crash course part poles ad zeros I geeral a
More information