COURSE OUTLINE. Introduction Signals and Noise Filtering: High-Pass Filters 2 HPF2 Sensors and associated electronics. Sensors, Signals and Noise 1

Size: px
Start display at page:

Download "COURSE OUTLINE. Introduction Signals and Noise Filtering: High-Pass Filters 2 HPF2 Sensors and associated electronics. Sensors, Signals and Noise 1"

Transcription

1 esors, igals ad Noise COURE OULINE Iroducio igals ad Noise ilerig: High-ass ilers H esors ad associaed elecroics igal Recovery, 07/08 H

2 / Noise ad High-ass ilers Measurig pulse sigals i presece o / oise wih cosa-parameer ilers Basic cosa-parameer High-ass iler (CR diereiaor) Cosa-arameer High-ass ilers i measuremes o pulses i sequece wiched-arameer High-ass iler: he Baselie Resorer Appedix: Bad-limi o he high-pass CR diereiaor or / oise igal Recovery, 07/08 H

3 3 Measurig pulse sigals i presece o / oise igal Recovery, 07/08 H

4 ulse sigals i presece o / oise 4 Case: ampliude measureme o pulse sigals wih / ad widebad oise. he classic approach o opimum ilerig (o id irs a oise-whieig iler ad he a mached iler) is arduous i his case because / oise ses a remarkably diicul mahemaical problem makes he whieig iler diicul o desig, o implemeable wih lumped circui compoes, bu wih disribued parameers (disribued RC delay lies, ec.) However, by oig ha a) or / oise he ilered power maily depeds o he spa o he bad-pass measured by he badlimi raio, hece i is markedly sesiive o he lower badlimi level weakly depeds o he shape o he iler weighig ucio b) or widebad oise he /N depeds o he spa o he bad-pass measured by he badlimi dierece, hece i is weakly sesiive o he lower badlimi level markedly depeds o he shape o he weighig ucio a aleraive approach leadig o quasi-opimum ilerig ca be devised igal Recovery, 07/08 H

5 ulses ad / oise: ilerig i wo-seps 5 IR E: Desig a mai iler or sigal ad widebad oise oly (ha is, cosiderig oexise he / oise) ad he ake he io accou he / compoe ad evaluae he addiioal oise power ha / oise brigs o he mai iler oupu. I he (lucky) cases where his / oise power is smaller ha he wide-bad oise (or a leas comparable), he mai iler may be cosidered suicie wihou urher ilerig. Oherwise, i he addiio due o / oise is excessive, proceed o he ECOND E : desig a addiioal iler or limiig he / oise power wihou worseig excessively he ilerig o he widebad oise. I is obviously a high-pass iler, which mus combie he goal o a) reducig eiciely he / oise power wih he urher requiremes o b) limiig o olerable level he icrease o he ilered wide-bad oise c) limiig o olerable level he reducio o he oupu sigal ampliude igal Recovery, 07/08 H

6 ilerig ulses ad / Noise: irs ep 6 he issue is beer clariied by cosiderig as IR E he opimum iler or sigal ad wide-bad oise (or is approximaio) composed by Noise-whieig iler, wih oupu whie oise B ad pulse sigal. Le be he upper bad-limi ad A he ceer-bad ampliude o he pulse rasorm. Mached iler, which has weighig ucio mached o he pulse sigal rom he whieig iler ad is hereore a low-pass iler wih upper badlimi. he oupu has a sigal wih ampliude roughly V A ad bad-limied whie oise wih bad-limi ad power B B or ocusig he ideas, le s cosider a well kow speciic case: ilerig o pulse-sigals rom a high impedace sesor wih a approximaely opimum iler, i.e. wih mached iler approximaed by a cosa-parameer RC iegraor. I his case, he oupu oise correspodig o he ipu wide-bad oise is a whie oise specrum wih bad-limi se by a pole wih ime cosa RC c igal Recovery, 07/08 H

7 ilerig ulses ad / Noise: ecod ep 7 Le s ow ake io accou also a / oise source, which brigs a he whieig iler oupu a sigiica / specral desiy B C /. A high rquecy, he / compoe is limied by he upper badlimi o he mached iler. A low requecy, he / compoe ca be limied by a lower bad-limi i se by a addiioal cosa-parameer iler. Wih i << he oupu power o he / oise ca be evaluaed as l i B C However, he cosa-parameer high-pass iler operaes also o he sigal: i aeuaes he low requecy compoes ad hus causes a loss i pulse ampliude, hece a loss i /N. he reduced ampliude is roughly evaluaed as or limiig he sigal loss, i / mus be limied; e.g. or keepig loss < 5% i mus be i ha is ( ) V A( ) A i i 0,05 ( ) l 3 i igal Recovery, 07/08 H

8 ilerig ulses ad / Noise: ecod ep 8 or reducig he / oise o he whie oise level or lower l ( ) B C i B We eed ha C l ( ) i ad sice or keepig he sigal loss <5% i mus be we eed o have C < 3 ( ) l 3 i his meas ha he goal ca be achieved oly i he / oise compoe is low or moderae. Noe ha C ad are daa o he problem, hey cao be chaged. I cases where C exceeds he above limi, a cosa-parameer high-pass iler is NO a suiable soluio or reducig he / oise power. CONCLUION: cosa-parameer high-pass ilers ca be useul as addiioal iler or limiig he / oise, bu jus i cases wih moderae / oise iesiy, because o heir derimeal eec o he sigal pulse ampliude. igal Recovery, 07/08 H

9 9 Basic cosa-parameer High-ass iler (CR diereiaor) igal Recovery, 07/08 H

10 Basic High-ass iler (CR diereiaor) 0 x() C R y() δ() δ-respose h () δ () () e p RC π # ep-respose u () () e raser ucio j π H( ) + j π ( ) π H( ) + π ( ) H() 3 db requecy (ole) % π # 0.5 igal Recovery, 07/08 H

11 A view o High-ass ilerig he iuiive view «High-ass iler All-ass - Low-ass iler» is coirmed by raser ucio j π H( ) + j π + j π h() δ-respose h () δ () () e Weighig ucio w( α) δ( α) ( α) e α α w(α) # igal Recovery, 07/08 H

12 A view o High-ass ilerig he circui mesh srucure isel coirms ha «High-ass iler All-ass - Low-ass iler» V C V i C R V R V i ipu volage V C low-pass ilered V i V R high-pass ilered V i Kircho s mesh volage law V i V C + V R V R V i V C hereore ha is High-pass ilered V i resisor volage ipu volage V i capacior volage ipu volage V i Low-pass ilered V i igal Recovery, 07/08 H

13 Bad-limi o CR diereiaor 3 High-pass bad-limi or Whie oise remise: wih oly a high-pass CR iler he whie oise power +, is diverge, hereore we cosider here also a low-pass iler wih bad-limi s >> /RC. he high-pass bad-limi i o he CR iler wih weighig ucio W() is deied by ( ) p B B 0 B 0 ( ) B i + p W ( ) d d ( ) he compuaio o he iegral ca be avoided by recallig ha CR high pass iler all-pass RC low-pass iler ad hereore high-pass bad-limi i o he CR iler low-pass bad-limi h o he RC iler icr hrc 4RC igal Recovery, 07/08 H

14 Bad-limi o CR diereiaor 4 High-pass bad-limi or / oise remise: wih oly a high-pass CR iler he / oise power #, is diverge, hereore we cosider here also a low-pass iler wih a high bad-limi s >> /RC. he high-pass bad-limi i o he CR iler is deied by ( ) p d d B c 0 ( ) B c B c i + p l( ) I his case he irs iegral is airly easily compued * ad shows ha i + p ( ) ha is, or s >> p i p p s π RC * ee he appedix. ice he high-pass limi o he CR diereiaor is also he low-pass limi o he RC iegraor, we ca avoid he compuaio or he laer (which is airly diicul). i igal Recovery, 07/08 H

15 Abou bad-limis ad oise power 5 he upper requecy limi : - is ecessary or limiig he whie oise power - is useul also or limiig he / oise power - he level o is dicaed by he pulse sigal o be measured he lower requecy limi i : - is ecessary or limiig he / oise power, - he seleced level o i is codiioed by he pulse sigal, i cao be arbirary - however, he reducio o / oise is sigiica eve wih airly low i, ha is, wih / i values ha are high, bu ayway iie. igal Recovery, 07/08 H

16 6 Cosa-arameer High-ass ilers i measuremes o pulses i sequece igal Recovery, 07/08 H

17 CR iler ad pulse sequece 7 Le s look i deail he eec o a high-pass iler (RC ) o a pulse sigal pulse area A V V View o HOR IME scale A INU View o LONG IME scale V RC A A OUU A NB: DC raser o CR is zero à Log ail A e e area o he oupu sigal is zero igal Recovery, 07/08 H

18 CR iler ad pulse sequece 8 V Δ V Δ A pulse ha ollows a previous oe wihi a airly shor ime ierval ( D < 5 ) seps o he slow ail o he irs pulse. hereore, i sars rom a dow-shied baselie, so ha he ampliude measured or i is smaller ha he rue oe. Δ D or periodic pulses wih airly shor repeiio period R <<, he superposiio o slow pulse-ails shis dow he baselie by a V ha makes zero he e area o he oupu sigal V INU V OUU R R V Repeiio-rae-depede baselie-shi V V A R R igal Recovery, 07/08 H

19 Drawbacks o he CR diereiaor iler 9 he high-pass ilerig (diereiaor acio) o he CR iler has MIXED eecs. he eec o oise is ADVANAGEOU: by cuig o he he low requecies i markedly decreases he / oise power (ad mildly reduces he whie oise power) he eec o he sigal is DIADVANAGEOU: Ø i decreases he sigal ampliude by cuig o he low requecies o he sigal, hece i mus be kep low ( i << o he pulse) i order o limi he sigal loss. However, his limis also he reducio o / oise Ø i geeraes slow ails aer he pulses, which shi dow he baselie ad hus cause a error i he measured ampliude o a ollowig pulse Ø Wih a periodic sequece o equal pulses, all pulses id he same baselie shi. he ampliude error is cosa, sisemaically depede o he repeiio rae. Ø Wih radom-repeiio pulses (e.g. pulses rom ioizig radiaio deecors) he pulses occur radomly i ime. Hece he radom superposiio o ails produces a radomly lucuaig baselie shi. he resulig ampliude error is radom: i his case he eec is equivale o ha o a addiioal oise source. CONCLUION: a diereiaor acio is desirable o oise, bu NO o he sigal. WANED: o a cosa-parameer diereiaor, bu a rue Base-Lie Resorer (BLR) igal Recovery, 07/08 H

20 0 wiched-arameer High-ass iler: he Baselie Resorer igal Recovery, 07/08 H

21 Baselie Resorer (BLR) priciple: swiched CR High-pass ilerig acio o he oise ad NO o he sigal: swiched-parameer CR iler wih CR à whe sigal is prese, iie CR whe o pulse is prese V C -dow -up -dow C α V i RC w( α ) ( α ) e R V R V i - V C α α x() V i ( α) δ( α) ( α ) w w B y() V R V i - V C As is ope a he pulse ose (a α ), chargig o C sops ad volage V C says cosa a he sored value pulse peakig ime δ(α) α 0 igal Recovery, 07/08 H

22 Comparig cosa CR iler ad BLR CONAN-ARAMEER ILER CR cosa a all imes WICHED-ARAMEER ILER wih -up R à ad CR à -dow -up -dow α x() x() α w (α) δ(α) α 0 α w (α- ) δ(α) α 0 igal loss y() y() igal Recovery, 07/08 H

23 BLR (All-ass) (Low-ass Boxcar Iegraor) 3 BLR V C -dow -up -dow -up -dow -up V i C R V R w B (α) BLR weighig m δ(α) V R V i - V C α α 0 BOXCAR V i R C α w (α- ) Boxcar weighig r, - r - - BLR weighig (All-ass Low-pass Boxcar) weighig ( α) δ( α) ( α ) w w B igal Recovery, 07/08 H

24 BLR weighig i requecy 4 α x() -dow -up -dow BLR priciple is alike ilered zero-seig, bu wih a basic advaage: much shorer much higher bad-limi i (high-pass) (he BLR swich is elecroically corolled, he ierval ca be very shor) α δ(α) α 0 BLR weighig i requecy: BLR weighig All ass Low-pass ( α) δ( α) ( α ) w w B Low-pass weighig i requecy: W ( ω) [ w ( α)] R ( ω) + i I ( ω) jω W ( ω) e W ( ω) [cosω jsi ω ] [ R + ji ] B [ R cosω I si ω ] j[ I cosω R si ω ] igal Recovery, 07/08 H

25 BLR weighig i requecy 5 BLR weighig or oise: B( ω) [ cosω si ω ] [ cosω si ω ] W R I + I R R I R cosω I siω + W R cosω I siω Le s cosider jus cases where he ierval bewee pulses is much loger ha α so ha w ( α) ( α) e ad W ( ω) + jω ad hereore W ( ω) + cosω + ω siω + ω + ω + ω B igal Recovery, 07/08 H

26 BLR cuo 6 I he low-requecy regio siω ω we ge wih he approximaios ω cosω W B ω ω ( ω) ω + ω + ω + ω ( ) ω ω ω ω ad i he lower regio ( ) B( ω) ω + W ha is, he BLR has a cuo equivale o a CR high-pass wih RC + igal Recovery, 07/08 H

27 BLR vs. CR High-ass iler: Cu-O 7 W W B BODE DIAGRAM highlighs he low-req cuo db W CR Example: BLR wih ad 0 CR iler wih RC + Log << / (i.e. << 0, i he example) ( ) B( ω) ω + W W ( ) CR ω ω R C / < << / (i.e. << i he example) W B W ( ω) CR ( ω) ( + ) ω + ω ω RC +ω RC igal Recovery, 07/08 H

28 BLR vs. CR High-ass iler: Whie Noise 8 W W B LIN LIN DIAGRAM highlighs whie oise power area o W W CR Example: BLR wih ad 0 CR iler wih RC + i π p 4RC 4 4 ( + ) i BLR high-pass bad-limi or whie oise. Noe ha: i is equal o ha o he equivale CR High-pass iler i is equal o badlimi o he low-pass secio i he BLR circui igal Recovery, 07/08 H

29 BLR vs. CR High-ass iler: / Noise 9 W W B LIN LOG DIAGRAM highlighs / oise power area o W W CR Example: BLR wih ad 0 CR iler wih RC + i p πrc π π ( + ) i BLR high-pass bad-limi or / oise. Noe ha: i is equal o ha o he equivale CR High-pass iler i is equal o badlimi o he low-pass secio i he BLR circui igal Recovery, 07/08 H

30 elecio o he BLR parameers 30 he BLR ilerig is ruled by:. ime delay rom swich opeig o pulse-ampliude measureme. here is o choice: is equal o he rise ime rom pulse ose o peak. I ac, ca be shorer ha he rise o he pulse sigal ad should be as shor as possible or ilerig eecively o he / oise.. RC diereiaio ime cosa:o be seleced or opimizig he overall ilerig o oise. he quesio is: how should be seleced or a) providig a good reducio o he / oise power ad b) avoidig o ehace sigiicaly he whie oise power ice he BLR cuo is se by /( + ), a very shor migh look advisable, bu i is o: a BLR wih << operaes like a CD, hece i doubles he whie oise ad remarkably ehaces also he / oise above he cuo requecy. I he ollowig discussio abou he selecio, or ocusig he ideas we will reer o a speciic case: sigals rom a high impedace sesor processed by a approximaely opimum iler, amely a CR-RC iler. he oupu correspodig o he ipu wide-bad oise is a whie specrum bad-limied by a simple pole. uch a siuaio is me i pracice also i may oher cases. A beer isigh i he issue is gaied wih a ime-domai aalysis o BLR ilerig igal Recovery, 07/08 H

31 BLR ilerig o Noise: ime-domai aalysis 3 α RC w w B δ(α) BLR weighig ucio α wb δ( α) w ( α) δ ( α) ( α ) exp δ(τ) k δδ auocorrelaio o δ(α) crosscorrel. δ wih w k δ k δ τ k auocorrelaio o w τ τ crosscorrel w wih δ k wwb auocorrelaio o w B k k + k + k + k wwb δδ δ δ τ igal Recovery, 07/08 H

32 BLR ilerig o Bad-Limied Whie Noise 3 ( ) ( ) ( ) ( ) ( ) k δ τ + k + τ w τ + τ + w τ + wwb τ w ( τ ) exp τ R xx Auocorrelaio o whie oise (bad-limied by a sigle pole) τ Rxx ( τ ) xe τ B Rxx( τ) kwwb( τ) dτ Rxx( 0) + R ( ) ( ) ( ) ( ) 0 xx τ w τ dτ Rxx τ w τ dτ Rxx ( 0) + Rxx ( τ) w ( τ) dτ R ( ) ( ) 0 xx β + w β dβ Rxx ( τ) Rxx ( τ) rxx ( τ ) R ( 0) Deoig We have xx x τ β B x + rxx( τ) e dτ r ( ) 0 xx β e dβ + igal Recovery, 07/08 H

33 BLR ilerig o Bad-Limied Whie Noise 33 τ β B x + rxx( τ) e dτ r ( ) 0 xx β e dβ + τ + β + x + e dτ e e dβ 0 x + e + + ad ially B x + e + Wih as diereiaio, i.e. wih <<, i is quaiaively coirmed ha he BLR acs like a CD wih B x e igal Recovery, 07/08 H

34 BLR ilerig wih as diereiaio 34 0 B x e Wih << he eec o BLR o bad-limied whie oise depeds o how log is he correlaio ime wih respec o he delay wih shor correlaio ime (wide bad) he oise is doubled: wih i is wih moderae correlaio ime (moderaely wide bad) he oise is ehaced: wih B x < 5 i is as diereiaio wih << B x /,73 B x oly wih log correlaio ime (low-requecy bad) he oise is aeuaed*: wih i is > 0 B x < 0,x * oe ha ayway he level is double o ha give by a simple CR iler wih equal cuo, ha is wih RC igal Recovery, 07/08 H

35 BLR ilerig wih as diereiaio 35 BLR WEIGHING wih << NOIE: 3 CAE R xx a) wih shor correlaio: R xx k wwb τ BLR weigh auocorrelaio k k + k + k + k wwb δδ δ δ Noise Auocorrelaio R b) wih moderae correlaio: xx ( τ ) e x τ B x, 73 B x > 0 R xx c) wih log correlaio: < 0, B x x igal Recovery, 07/08 H

36 BLR ilerig wih slow diereiaio 36 w ( τ ) exp τ ( ) ( ) ( ) ( ) ( ) k δ τ + k + τ w τ + τ + w τ + wwb τ Noise Auocorrelaio ( ) R xx τ e x τ R xx wih shor correlaio /0 or +, <,05 4, we eed > 0 τ wih moderae correlaio / R xx or +, <,05 4, we eed > 7 3,5 τ wih log correlaio > 0 R xx or +, <,05 4, o problem eve wih shor τ igal Recovery, 07/08 H

37 BLR ilerig wih slow diereiaio 37 Wih NO egligible wih respec o, he eec o whie oise depeds also o he size o compared o ad. A log ca limi he whie oise ehaceme Le s evaluae how log mus be i he various cases o oise correlaio wih shor correlaio ime /0 i is or keepig we eed > 0 wih moderae correlaio ime / i is or keepig <,05 <,05 B x + B x B x B x + e + + B x + 0, 73 x + + e + i his case we eed > 7 3,5 igal Recovery, 07/08 H

38 BLR ilerig wih slow diereiaio 38 wih log correlaio ime > 0 i is B x x + + No problem wih such a low-requecy oise: i is aeued by he BLR jus as by a CR cosa-parameer iler (wih equal ime cosa RC) he mos ieresig case or us is oise wih moderae. I ac, whe he BLR works o he oupu o a opimum (or approximae-opimum) iler or widebad oise, he correlaio ime ad delay p are comparable, sice hey are boh closely relaed o he bad-limi o he sigal pulse. We coclude ha or avoidig ehaceme o he whie oise i is ecessary o selec a airly slow BLR diereiaio, i.e. a airly log 5 his approach is saisacory also or ilerig he / oise, owihsadig ha makig loger ha shis dow he BLR cuo requecy, hece reduces he aeuaio o / oise. his is couerbalaced by he ac ha he ehaceme o / oise a requecies above he cuo is limied by he low-pass ilerig i he baselie subracio, whereas wih shor i is remarkable. igal Recovery, 07/08 H

39 BLR i summary 39 he BLR is a high-pass iler ha acs o oise ad disurbaces wihou aecig he pulse sigal he BLR is a swiched-parameer iler: he low-pass secio wihi he high-pass iler srucure is a boxcar iegraor ha acquires he baselie oly i he iervals ree rom pulses he BLR ca hus esablish a high-pass bad-limi a a high value (suiable or reducig eiciely he / oise oupu power) wihou causig he sigal loss suered wih a cosa-parameer high-pass iler havig he same bad-limi he high-pass bad-limi eorced by he BLR is give (wih good approximaio) by he low-pass badlimi o he low-pass secio i he BLR circui srucure he combiaio o: () opimum iler desiged or he case o pulse sigal i presece o widebad oise oly (i.e. wihou / oise) ad () BLR speciically desiged (or reducig he acual / oise wihou worseig he wide-bad oise) provides i mos cases a quasi-opimum ilerig soluio. igal Recovery, 07/08 H

40 Appedix: Bad-limi o he high-pass CR diereiaor or / oise 40 remise: wih oly a high-pass CR iler he / oise power #, is diverge, hereore we cosider here also a low-pass iler wih very high bad-limi s >> p /πrc. B c 0 + By chagig variable We have ad by seig p d ( ) ( ) p p equivale o d dx x x x dx x dx d x + x x + x + x x x x B c B c B c x y xdx dy x y d i B c B c p x l( ) ( ) i We obai dy l( + y) l( + y ) y B c B c y B c y igal Recovery, 07/08 H

41 Appedix: Bad-limi o he high-pass CR diereiaor or / oise 4 B c l( + y) B cl + y Bcl + p ice he high-pass bad-limi i is deied by d i B c B c l( ) i i is i + p ad hereore i + p ( ) p s ad akig io accou ha s >> p we have ially i p π RC igal Recovery, 07/08 H

SUMMATION OF INFINITE SERIES REVISITED

SUMMATION OF INFINITE SERIES REVISITED SUMMATION OF INFINITE SERIES REVISITED I several aricles over he las decade o his web page we have show how o sum cerai iiie series icludig he geomeric series. We wa here o eed his discussio o he geeral

More information

10.3 Autocorrelation Function of Ergodic RP 10.4 Power Spectral Density of Ergodic RP 10.5 Normal RP (Gaussian RP)

10.3 Autocorrelation Function of Ergodic RP 10.4 Power Spectral Density of Ergodic RP 10.5 Normal RP (Gaussian RP) ENGG450 Probabiliy ad Saisics for Egieers Iroducio 3 Probabiliy 4 Probabiliy disribuios 5 Probabiliy Desiies Orgaizaio ad descripio of daa 6 Samplig disribuios 7 Ifereces cocerig a mea 8 Comparig wo reames

More information

Section 8 Convolution and Deconvolution

Section 8 Convolution and Deconvolution APPLICATIONS IN SIGNAL PROCESSING Secio 8 Covoluio ad Decovoluio This docume illusraes several echiques for carryig ou covoluio ad decovoluio i Mahcad. There are several operaors available for hese fucios:

More information

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory Liear Time-Ivaria Sysems (LTI Sysems) Oulie Basic Sysem Properies Memoryless ad sysems wih memory (saic or dyamic) Causal ad o-causal sysems (Causaliy) Liear ad o-liear sysems (Lieariy) Sable ad o-sable

More information

Sampling. AD Conversion (Additional Material) Sampling: Band limited signal. Sampling. Sampling function (sampling comb) III(x) Shah.

Sampling. AD Conversion (Additional Material) Sampling: Band limited signal. Sampling. Sampling function (sampling comb) III(x) Shah. AD Coversio (Addiioal Maerial Samplig Samplig Properies of real ADCs wo Sep Flash ADC Pipelie ADC Iegraig ADCs: Sigle Slope, Dual Slope DA Coverer Samplig fucio (samplig comb III(x Shah III III ( x = δ

More information

The Eigen Function of Linear Systems

The Eigen Function of Linear Systems 1/25/211 The Eige Fucio of Liear Sysems.doc 1/7 The Eige Fucio of Liear Sysems Recall ha ha we ca express (expad) a ime-limied sigal wih a weighed summaio of basis fucios: v ( ) a ψ ( ) = where v ( ) =

More information

OLS bias for econometric models with errors-in-variables. The Lucas-critique Supplementary note to Lecture 17

OLS bias for econometric models with errors-in-variables. The Lucas-critique Supplementary note to Lecture 17 OLS bias for ecoomeric models wih errors-i-variables. The Lucas-criique Supplemeary oe o Lecure 7 RNy May 6, 03 Properies of OLS i RE models I Lecure 7 we discussed he followig example of a raioal expecaios

More information

Electrical Engineering Department Network Lab.

Electrical Engineering Department Network Lab. Par:- Elecrical Egieerig Deparme Nework Lab. Deermiaio of differe parameers of -por eworks ad verificaio of heir ierrelaio ships. Objecive: - To deermie Y, ad ABD parameers of sigle ad cascaded wo Por

More information

Notes 03 largely plagiarized by %khc

Notes 03 largely plagiarized by %khc 1 1 Discree-Time Covoluio Noes 03 largely plagiarized by %khc Le s begi our discussio of covoluio i discree-ime, sice life is somewha easier i ha domai. We sar wih a sigal x[] ha will be he ipu io our

More information

Power Bus Decoupling Algorithm

Power Bus Decoupling Algorithm Rev. 0.8.03 Power Bus Decoulig Algorihm Purose o Algorihm o esimae he magiude o he oise volage o he ower bus es. Descriio o Algorihm his algorihm is alied oly o digial ower bus es. or each digial ower

More information

Linear Time Invariant Systems

Linear Time Invariant Systems 1 Liear Time Ivaria Sysems Oulie We will show ha he oupu equals he covoluio bewee he ipu ad he ui impulse respose: sysem for a discree-ime, for a coiuous-ime sysdem, y x h y x h 2 Discree Time LTI Sysems

More information

In this section we will study periodic signals in terms of their frequency f t is said to be periodic if (4.1)

In this section we will study periodic signals in terms of their frequency f t is said to be periodic if (4.1) Fourier Series Iroducio I his secio we will sudy periodic sigals i ers o heir requecy is said o be periodic i coe Reid ha a sigal ( ) ( ) ( ) () or every, where is a uber Fro his deiiio i ollows ha ( )

More information

Big O Notation for Time Complexity of Algorithms

Big O Notation for Time Complexity of Algorithms BRONX COMMUNITY COLLEGE of he Ciy Uiversiy of New York DEPARTMENT OF MATHEMATICS AND COMPUTER SCIENCE CSI 33 Secio E01 Hadou 1 Fall 2014 Sepember 3, 2014 Big O Noaio for Time Complexiy of Algorihms Time

More information

Clock Skew and Signal Representation

Clock Skew and Signal Representation Clock Skew ad Sigal Represeaio Ch. 7 IBM Power 4 Chip 0/7/004 08 frequecy domai Program Iroducio ad moivaio Sequeial circuis, clock imig, Basic ools for frequecy domai aalysis Fourier series sigal represeaio

More information

Problems and Solutions for Section 3.2 (3.15 through 3.25)

Problems and Solutions for Section 3.2 (3.15 through 3.25) 3-7 Problems ad Soluios for Secio 3 35 hrough 35 35 Calculae he respose of a overdamped sigle-degree-of-freedom sysem o a arbirary o-periodic exciaio Soluio: From Equaio 3: x = # F! h "! d! For a overdamped

More information

STK4080/9080 Survival and event history analysis

STK4080/9080 Survival and event history analysis STK48/98 Survival ad eve hisory aalysis Marigales i discree ime Cosider a sochasic process The process M is a marigale if Lecure 3: Marigales ad oher sochasic processes i discree ime (recap) where (formally

More information

BEST LINEAR FORECASTS VS. BEST POSSIBLE FORECASTS

BEST LINEAR FORECASTS VS. BEST POSSIBLE FORECASTS BEST LINEAR FORECASTS VS. BEST POSSIBLE FORECASTS Opimal ear Forecasig Alhough we have o meioed hem explicily so far i he course, here are geeral saisical priciples for derivig he bes liear forecas, ad

More information

ELEG5693 Wireless Communications Propagation and Noise Part II

ELEG5693 Wireless Communications Propagation and Noise Part II Deparme of Elecrical Egieerig Uiversiy of Arkasas ELEG5693 Wireless Commuicaios Propagaio ad Noise Par II Dr. Jigxia Wu wuj@uark.edu OUTLINE Wireless chael Pah loss Shadowig Small scale fadig Simulaio

More information

Solutions Manual 4.1. nonlinear. 4.2 The Fourier Series is: and the fundamental frequency is ω 2π

Solutions Manual 4.1. nonlinear. 4.2 The Fourier Series is: and the fundamental frequency is ω 2π Soluios Maual. (a) (b) (c) (d) (e) (f) (g) liear oliear liear liear oliear oliear liear. The Fourier Series is: F () 5si( ) ad he fudameal frequecy is ω f ----- H z.3 Sice V rms V ad f 6Hz, he Fourier

More information

Chapter 2: Time-Domain Representations of Linear Time-Invariant Systems. Chih-Wei Liu

Chapter 2: Time-Domain Representations of Linear Time-Invariant Systems. Chih-Wei Liu Caper : Time-Domai Represeaios of Liear Time-Ivaria Sysems Ci-Wei Liu Oulie Iroucio Te Covoluio Sum Covoluio Sum Evaluaio Proceure Te Covoluio Iegral Covoluio Iegral Evaluaio Proceure Iercoecios of LTI

More information

ECE-314 Fall 2012 Review Questions

ECE-314 Fall 2012 Review Questions ECE-34 Fall 0 Review Quesios. A liear ime-ivaria sysem has he ipu-oupu characerisics show i he firs row of he diagram below. Deermie he oupu for he ipu show o he secod row of he diagram. Jusify your aswer.

More information

COS 522: Complexity Theory : Boaz Barak Handout 10: Parallel Repetition Lemma

COS 522: Complexity Theory : Boaz Barak Handout 10: Parallel Repetition Lemma COS 522: Complexiy Theory : Boaz Barak Hadou 0: Parallel Repeiio Lemma Readig: () A Parallel Repeiio Theorem / Ra Raz (available o his websie) (2) Parallel Repeiio: Simplificaios ad he No-Sigallig Case

More information

Exercise 3 Stochastic Models of Manufacturing Systems 4T400, 6 May

Exercise 3 Stochastic Models of Manufacturing Systems 4T400, 6 May Exercise 3 Sochasic Models of Maufacurig Sysems 4T4, 6 May. Each week a very popular loery i Adorra pris 4 ickes. Each ickes has wo 4-digi umbers o i, oe visible ad he oher covered. The umbers are radomly

More information

Math 2414 Homework Set 7 Solutions 10 Points

Math 2414 Homework Set 7 Solutions 10 Points Mah Homework Se 7 Soluios 0 Pois #. ( ps) Firs verify ha we ca use he iegral es. The erms are clearly posiive (he epoeial is always posiive ad + is posiive if >, which i is i his case). For decreasig we

More information

Lecture 9: Polynomial Approximations

Lecture 9: Polynomial Approximations CS 70: Complexiy Theory /6/009 Lecure 9: Polyomial Approximaios Isrucor: Dieer va Melkebeek Scribe: Phil Rydzewski & Piramaayagam Arumuga Naiar Las ime, we proved ha o cosa deph circui ca evaluae he pariy

More information

ECE 340 Lecture 15 and 16: Diffusion of Carriers Class Outline:

ECE 340 Lecture 15 and 16: Diffusion of Carriers Class Outline: ECE 340 Lecure 5 ad 6: iffusio of Carriers Class Oulie: iffusio rocesses iffusio ad rif of Carriers Thigs you should kow whe you leave Key Quesios Why do carriers diffuse? Wha haes whe we add a elecric

More information

t = s D Overview of Tests Two-Sample t-test: Independent Samples Independent Samples t-test Difference between Means in a Two-sample Experiment

t = s D Overview of Tests Two-Sample t-test: Independent Samples Independent Samples t-test Difference between Means in a Two-sample Experiment Overview of Te Two-Sample -Te: Idepede Sample Chaper 4 z-te Oe Sample -Te Relaed Sample -Te Idepede Sample -Te Compare oe ample o a populaio Compare wo ample Differece bewee Mea i a Two-ample Experime

More information

Solutions to selected problems from the midterm exam Math 222 Winter 2015

Solutions to selected problems from the midterm exam Math 222 Winter 2015 Soluios o seleced problems from he miderm eam Mah Wier 5. Derive he Maclauri series for he followig fucios. (cf. Pracice Problem 4 log( + (a L( d. Soluio: We have he Maclauri series log( + + 3 3 4 4 +...,

More information

Fresnel Dragging Explained

Fresnel Dragging Explained Fresel Draggig Explaied 07/05/008 Decla Traill Decla@espace.e.au The Fresel Draggig Coefficie required o explai he resul of he Fizeau experime ca be easily explaied by usig he priciples of Eergy Field

More information

λiv Av = 0 or ( λi Av ) = 0. In order for a vector v to be an eigenvector, it must be in the kernel of λi

λiv Av = 0 or ( λi Av ) = 0. In order for a vector v to be an eigenvector, it must be in the kernel of λi Liear lgebra Lecure #9 Noes This week s lecure focuses o wha migh be called he srucural aalysis of liear rasformaios Wha are he irisic properies of a liear rasformaio? re here ay fixed direcios? The discussio

More information

Topic Astable Circuits. Recall that an astable circuit has two unstable states;

Topic Astable Circuits. Recall that an astable circuit has two unstable states; Topic 2.2. Asable Circuis. Learning Objecives: A he end o his opic you will be able o; Recall ha an asable circui has wo unsable saes; Explain he operaion o a circui based on a Schmi inverer, and esimae

More information

EEC 483 Computer Organization

EEC 483 Computer Organization EEC 8 Compuer Orgaizaio Chaper. Overview of Pipeliig Chau Yu Laudry Example Laudry Example A, Bria, Cahy, Dave each have oe load of clohe o wah, dry, ad fold Waher ake 0 miue A B C D Dryer ake 0 miue Folder

More information

Department of Mathematical and Statistical Sciences University of Alberta

Department of Mathematical and Statistical Sciences University of Alberta MATH 4 (R) Wier 008 Iermediae Calculus I Soluios o Problem Se # Due: Friday Jauary 8, 008 Deparme of Mahemaical ad Saisical Scieces Uiversiy of Albera Quesio. [Sec.., #] Fid a formula for he geeral erm

More information

Sensors, Signals and Noise

Sensors, Signals and Noise Sensors, Signals and Noise COURSE OUTLINE Inroducion Signals and Noise: 1) Descripion Filering Sensors and associaed elecronics rv 2017/02/08 1 Noise Descripion Noise Waveforms and Samples Saisics of Noise

More information

ECE 145B / 218B, notes set 5: Two-port Noise Parameters

ECE 145B / 218B, notes set 5: Two-port Noise Parameters class oes, M. odwell, copyrihed 01 C 145B 18B, oes se 5: Two-por Noise Parameers Mark odwell Uiersiy of Califoria, aa Barbara rodwell@ece.ucsb.edu 805-893-344, 805-893-36 fax efereces ad Ciaios: class

More information

1 Notes on Little s Law (l = λw)

1 Notes on Little s Law (l = λw) Copyrigh c 26 by Karl Sigma Noes o Lile s Law (l λw) We cosider here a famous ad very useful law i queueig heory called Lile s Law, also kow as l λw, which assers ha he ime average umber of cusomers i

More information

Moment Generating Function

Moment Generating Function 1 Mome Geeraig Fucio m h mome m m m E[ ] x f ( x) dx m h ceral mome m m m E[( ) ] ( ) ( x ) f ( x) dx Mome Geeraig Fucio For a real, M () E[ e ] e k x k e p ( x ) discree x k e f ( x) dx coiuous Example

More information

Fourier transform. Continuous-time Fourier transform (CTFT) ω ω

Fourier transform. Continuous-time Fourier transform (CTFT) ω ω Fourier rasform Coiuous-ime Fourier rasform (CTFT P. Deoe ( he Fourier rasform of he sigal x(. Deermie he followig values, wihou compuig (. a (0 b ( d c ( si d ( d d e iverse Fourier rasform for Re { (

More information

FIXED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE

FIXED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE Mohia & Samaa, Vol. 1, No. II, December, 016, pp 34-49. ORIGINAL RESEARCH ARTICLE OPEN ACCESS FIED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE 1 Mohia S. *, Samaa T. K. 1 Deparme of Mahemaics, Sudhir Memorial

More information

Chapter 7 - Sampling and the DFT

Chapter 7 - Sampling and the DFT M. J. Rober - 8/7/04 Chaper 7 - Samplig ad he DT Seleced Soluio (I hi oluio maual, he ymbol,, i ued or periodic covoluio becaue he preerred ymbol which appear i he ex i o i he o elecio o he word proceor

More information

C(p, ) 13 N. Nuclear reactions generate energy create new isotopes and elements. Notation for stellar rates: p 12

C(p, ) 13 N. Nuclear reactions generate energy create new isotopes and elements. Notation for stellar rates: p 12 Iroducio o sellar reacio raes Nuclear reacios geerae eergy creae ew isoopes ad elemes Noaio for sellar raes: p C 3 N C(p,) 3 N The heavier arge ucleus (Lab: arge) he ligher icomig projecile (Lab: beam)

More information

ECE 340 Lecture 19 : Steady State Carrier Injection Class Outline:

ECE 340 Lecture 19 : Steady State Carrier Injection Class Outline: ECE 340 ecure 19 : Seady Sae Carrier Ijecio Class Oulie: iffusio ad Recombiaio Seady Sae Carrier Ijecio Thigs you should kow whe you leave Key Quesios Wha are he major mechaisms of recombiaio? How do we

More information

David Randall. ( )e ikx. k = u x,t. u( x,t)e ikx dx L. x L /2. Recall that the proof of (1) and (2) involves use of the orthogonality condition.

David Randall. ( )e ikx. k = u x,t. u( x,t)e ikx dx L. x L /2. Recall that the proof of (1) and (2) involves use of the orthogonality condition. ! Revised April 21, 2010 1:27 P! 1 Fourier Series David Radall Assume ha u( x,) is real ad iegrable If he domai is periodic, wih period L, we ca express u( x,) exacly by a Fourier series expasio: ( ) =

More information

CSE 241 Algorithms and Data Structures 10/14/2015. Skip Lists

CSE 241 Algorithms and Data Structures 10/14/2015. Skip Lists CSE 41 Algorihms ad Daa Srucures 10/14/015 Skip Liss This hadou gives he skip lis mehods ha we discussed i class. A skip lis is a ordered, doublyliked lis wih some exra poiers ha allow us o jump over muliple

More information

Extremal graph theory II: K t and K t,t

Extremal graph theory II: K t and K t,t Exremal graph heory II: K ad K, Lecure Graph Theory 06 EPFL Frak de Zeeuw I his lecure, we geeralize he wo mai heorems from he las lecure, from riagles K 3 o complee graphs K, ad from squares K, o complee

More information

ME 321 Kinematics and Dynamics of Machines S. Lambert Winter 2002

ME 321 Kinematics and Dynamics of Machines S. Lambert Winter 2002 ME 31 Kiemaic ad Dyamic o Machie S. Lamber Wier 6.. Forced Vibraio wih Dampig Coider ow he cae o orced vibraio wih dampig. Recall ha he goverig diereial equaio i: m && c& k F() ad ha we will aume ha he

More information

12 Getting Started With Fourier Analysis

12 Getting Started With Fourier Analysis Commuicaios Egieerig MSc - Prelimiary Readig Geig Sared Wih Fourier Aalysis Fourier aalysis is cocered wih he represeaio of sigals i erms of he sums of sie, cosie or complex oscillaio waveforms. We ll

More information

Three Point Bending Analysis of a Mobile Phone Using LS-DYNA Explicit Integration Method

Three Point Bending Analysis of a Mobile Phone Using LS-DYNA Explicit Integration Method 9 h Ieraioal LS-DYNA Users Coerece Simulaio Techology (3) Three Poi Bedig Aalysis o a Mobile Phoe Usig LS-DYNA Explici Iegraio Mehod Feixia Pa, Jiase Zhu, Ai O. Helmie, Rami Vaaparas NOKIA Ic. Absrac I

More information

Economics 8723 Macroeconomic Theory Problem Set 2 Professor Sanjay Chugh Spring 2017

Economics 8723 Macroeconomic Theory Problem Set 2 Professor Sanjay Chugh Spring 2017 Deparme of Ecoomics The Ohio Sae Uiversiy Ecoomics 8723 Macroecoomic Theory Problem Se 2 Professor Sajay Chugh Sprig 207 Labor Icome Taxes, Nash-Bargaied Wages, ad Proporioally-Bargaied Wages. I a ecoomy

More information

A Two-Level Quantum Analysis of ERP Data for Mock-Interrogation Trials. Michael Schillaci Jennifer Vendemia Robert Buzan Eric Green

A Two-Level Quantum Analysis of ERP Data for Mock-Interrogation Trials. Michael Schillaci Jennifer Vendemia Robert Buzan Eric Green A Two-Level Quaum Aalysis of ERP Daa for Mock-Ierrogaio Trials Michael Schillaci Jeifer Vedemia Rober Buza Eric Gree Oulie Experimeal Paradigm 4 Low Workload; Sigle Sessio; 39 8 High Workload; Muliple

More information

Actuarial Society of India

Actuarial Society of India Acuarial Sociey of Idia EXAMINAIONS Jue 5 C4 (3) Models oal Marks - 5 Idicaive Soluio Q. (i) a) Le U deoe he process described by 3 ad V deoe he process described by 4. he 5 e 5 PU [ ] PV [ ] ( e ).538!

More information

Discrete-Time Signals and Systems. Introduction to Digital Signal Processing. Independent Variable. What is a Signal? What is a System?

Discrete-Time Signals and Systems. Introduction to Digital Signal Processing. Independent Variable. What is a Signal? What is a System? Discree-Time Sigals ad Sysems Iroducio o Digial Sigal Processig Professor Deepa Kudur Uiversiy of Toroo Referece: Secios. -.4 of Joh G. Proakis ad Dimiris G. Maolakis, Digial Sigal Processig: Priciples,

More information

Let s express the absorption of radiation by dipoles as a dipole correlation function.

Let s express the absorption of radiation by dipoles as a dipole correlation function. MIT Deparme of Chemisry 5.74, Sprig 004: Iroducory Quaum Mechaics II Isrucor: Prof. Adrei Tokmakoff p. 81 Time-Correlaio Fucio Descripio of Absorpio Lieshape Le s express he absorpio of radiaio by dipoles

More information

MATH 507a ASSIGNMENT 4 SOLUTIONS FALL 2018 Prof. Alexander. g (x) dx = g(b) g(0) = g(b),

MATH 507a ASSIGNMENT 4 SOLUTIONS FALL 2018 Prof. Alexander. g (x) dx = g(b) g(0) = g(b), MATH 57a ASSIGNMENT 4 SOLUTIONS FALL 28 Prof. Alexader (2.3.8)(a) Le g(x) = x/( + x) for x. The g (x) = /( + x) 2 is decreasig, so for a, b, g(a + b) g(a) = a+b a g (x) dx b so g(a + b) g(a) + g(b). Sice

More information

N! AND THE GAMMA FUNCTION

N! AND THE GAMMA FUNCTION N! AND THE GAMMA FUNCTION Cosider he produc of he firs posiive iegers- 3 4 5 6 (-) =! Oe calls his produc he facorial ad has ha produc of he firs five iegers equals 5!=0. Direcly relaed o he discree! fucio

More information

EGR 544 Communication Theory

EGR 544 Communication Theory EGR 544 Commuicaio heory 7. Represeaio of Digially Modulaed Sigals II Z. Aliyazicioglu Elecrical ad Compuer Egieerig Deparme Cal Poly Pomoa Represeaio of Digial Modulaio wih Memory Liear Digial Modulaio

More information

Available online at J. Math. Comput. Sci. 4 (2014), No. 4, ISSN:

Available online at   J. Math. Comput. Sci. 4 (2014), No. 4, ISSN: Available olie a hp://sci.org J. Mah. Compu. Sci. 4 (2014), No. 4, 716-727 ISSN: 1927-5307 ON ITERATIVE TECHNIQUES FOR NUMERICAL SOLUTIONS OF LINEAR AND NONLINEAR DIFFERENTIAL EQUATIONS S.O. EDEKI *, A.A.

More information

A Probabilistic Nearest Neighbor Filter for m Validated Measurements.

A Probabilistic Nearest Neighbor Filter for m Validated Measurements. A Probabilisic Neares Neighbor iler for m Validaed Measuremes. ae Lyul Sog ad Sag Ji Shi ep. of Corol ad Isrumeaio Egieerig, Hayag Uiversiy, Sa-og 7, Asa, Kyuggi-do, 45-79, Korea Absrac - he simples approach

More information

A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY

A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY U.P.B. Sci. Bull., Series A, Vol. 78, Iss. 2, 206 ISSN 223-7027 A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY İbrahim Çaak I his paper we obai a Tauberia codiio i erms of he weighed classical

More information

Communication Systems Lecture 25. Dong In Kim School of Info/Comm Engineering Sungkyunkwan University

Communication Systems Lecture 25. Dong In Kim School of Info/Comm Engineering Sungkyunkwan University Commuiaio Sysems Leure 5 Dog I Kim Shool o Io/Comm Egieerig Sugkyukwa Uiversiy 1 Oulie Noise i Agle Modulaio Phase deviaio Large SNR Small SNR Oupu SNR PM FM Review o Agle Modulaio Geeral orm o agle modulaed

More information

14.02 Principles of Macroeconomics Fall 2005

14.02 Principles of Macroeconomics Fall 2005 14.02 Priciples of Macroecoomics Fall 2005 Quiz 2 Tuesday, November 8, 2005 7:30 PM 9 PM Please, aswer he followig quesios. Wrie your aswers direcly o he quiz. You ca achieve a oal of 100 pois. There are

More information

Comparisons Between RV, ARV and WRV

Comparisons Between RV, ARV and WRV Comparisos Bewee RV, ARV ad WRV Cao Gag,Guo Migyua School of Maageme ad Ecoomics, Tiaji Uiversiy, Tiaji,30007 Absrac: Realized Volailiy (RV) have bee widely used sice i was pu forward by Aderso ad Bollerslev

More information

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws.

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws. Limi of a fucio.. Oe-Sided..... Ifiie limis Verical Asympoes... Calculaig Usig he Limi Laws.5 The Squeeze Theorem.6 The Precise Defiiio of a Limi......7 Coiuiy.8 Iermediae Value Theorem..9 Refereces..

More information

INVESTMENT PROJECT EFFICIENCY EVALUATION

INVESTMENT PROJECT EFFICIENCY EVALUATION 368 Miljeko Crjac Domiika Crjac INVESTMENT PROJECT EFFICIENCY EVALUATION Miljeko Crjac Professor Faculy of Ecoomics Drsc Domiika Crjac Faculy of Elecrical Egieerig Osijek Summary Fiacial efficiecy of ivesme

More information

Comparison between Fourier and Corrected Fourier Series Methods

Comparison between Fourier and Corrected Fourier Series Methods Malaysia Joural of Mahemaical Scieces 7(): 73-8 (13) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES Joural homepage: hp://eispem.upm.edu.my/oural Compariso bewee Fourier ad Correced Fourier Series Mehods 1

More information

1.225J J (ESD 205) Transportation Flow Systems

1.225J J (ESD 205) Transportation Flow Systems .5J J ESD 5 Trasporaio Flow Sysems Lecre 3 Modelig Road Traffic Flow o a Li Prof. Ismail Chabii ad Prof. Amedeo Odoi Lecre 3 Olie Time-Space Diagrams ad Traffic Flow Variables Irodcio o Li Performace Models

More information

Theoretical Physics Prof. Ruiz, UNC Asheville, doctorphys on YouTube Chapter R Notes. Convolution

Theoretical Physics Prof. Ruiz, UNC Asheville, doctorphys on YouTube Chapter R Notes. Convolution Theoreical Physics Prof Ruiz, UNC Asheville, docorphys o YouTube Chaper R Noes Covoluio R1 Review of he RC Circui The covoluio is a "difficul" cocep o grasp So we will begi his chaper wih a review of he

More information

S n. = n. Sum of first n terms of an A. P is

S n. = n. Sum of first n terms of an A. P is PROGREION I his secio we discuss hree impora series amely ) Arihmeic Progressio (A.P), ) Geomeric Progressio (G.P), ad 3) Harmoic Progressio (H.P) Which are very widely used i biological scieces ad humaiies.

More information

Institute of Actuaries of India

Institute of Actuaries of India Isiue of cuaries of Idia Subjec CT3-robabiliy ad Mahemaical Saisics May 008 Eamiaio INDICTIVE SOLUTION Iroducio The idicaive soluio has bee wrie by he Eamiers wih he aim of helig cadidaes. The soluios

More information

EE100 Lab 3 Experiment Guide: RC Circuits

EE100 Lab 3 Experiment Guide: RC Circuits I. Inroducion EE100 Lab 3 Experimen Guide: A. apaciors A capacior is a passive elecronic componen ha sores energy in he form of an elecrosaic field. The uni of capaciance is he farad (coulomb/vol). Pracical

More information

th m m m m central moment : E[( X X) ] ( X X) ( x X) f ( x)

th m m m m central moment : E[( X X) ] ( X X) ( x X) f ( x) 1 Trasform Techiques h m m m m mome : E[ ] x f ( x) dx h m m m m ceral mome : E[( ) ] ( ) ( x) f ( x) dx A coveie wa of fidig he momes of a radom variable is he mome geeraig fucio (MGF). Oher rasform echiques

More information

ODEs II, Supplement to Lectures 6 & 7: The Jordan Normal Form: Solving Autonomous, Homogeneous Linear Systems. April 2, 2003

ODEs II, Supplement to Lectures 6 & 7: The Jordan Normal Form: Solving Autonomous, Homogeneous Linear Systems. April 2, 2003 ODEs II, Suppleme o Lecures 6 & 7: The Jorda Normal Form: Solvig Auoomous, Homogeeous Liear Sysems April 2, 23 I his oe, we describe he Jorda ormal form of a marix ad use i o solve a geeral homogeeous

More information

MOSFET device models and conventions

MOSFET device models and conventions MOFET device odels ad coveios ybols: V hreshold volae; V T kt/q, W µ OX. W W W, L L L L µ elecro obiliy i he MOFET chael (ca be uch lower ha he obiliy i bulk silico). 1. RA URRET ro versio: V -V >>4V T

More information

Series Expansion with Wavelets

Series Expansion with Wavelets Series Expasio wih Waveles Advaced Sigal Processig 7 Berhard Reiisch Georg Teicheiser SERIES EXPANSION WITH WAVELETS... ADVANCED SIGNAL PROCESSING 7... INTRODUCTION... SIGNAL REPRESENTATION.... TIME DOMAIN

More information

B. Maddah INDE 504 Simulation 09/02/17

B. Maddah INDE 504 Simulation 09/02/17 B. Maddah INDE 54 Simulaio 9/2/7 Queueig Primer Wha is a queueig sysem? A queueig sysem cosiss of servers (resources) ha provide service o cusomers (eiies). A Cusomer requesig service will sar service

More information

Dynamic h-index: the Hirsch index in function of time

Dynamic h-index: the Hirsch index in function of time Dyamic h-idex: he Hirsch idex i fucio of ime by L. Egghe Uiversiei Hassel (UHassel), Campus Diepebeek, Agoralaa, B-3590 Diepebeek, Belgium ad Uiversiei Awerpe (UA), Campus Drie Eike, Uiversieisplei, B-260

More information

Update. Continuous-Time Frequency Analysis. Frequency Analysis. Frequency Synthesis. prism. white light. spectrum. Coverage:

Update. Continuous-Time Frequency Analysis. Frequency Analysis. Frequency Synthesis. prism. white light. spectrum. Coverage: Updae Coiuous-Time requecy alysis Professor Deepa Kudur Uiversiy of Toroo Coverage: Before Readig Wee: 41 Wih Ema: 42, 43, 44, 51 Today ad Wed: Brief Rev of 41, 42, 43, 44, 51 ad Secios 52, 54, 55 Joh

More information

LabQuest 24. Capacitors

LabQuest 24. Capacitors Capaciors LabQues 24 The charge q on a capacior s plae is proporional o he poenial difference V across he capacior. We express his wih q V = C where C is a proporionaliy consan known as he capaciance.

More information

Math 6710, Fall 2016 Final Exam Solutions

Math 6710, Fall 2016 Final Exam Solutions Mah 67, Fall 6 Fial Exam Soluios. Firs, a sude poied ou a suble hig: if P (X i p >, he X + + X (X + + X / ( evaluaes o / wih probabiliy p >. This is roublesome because a radom variable is supposed o be

More information

ECE 570 Session 7 IC 752-E Computer Aided Engineering for Integrated Circuits. Transient analysis. Discuss time marching methods used in SPICE

ECE 570 Session 7 IC 752-E Computer Aided Engineering for Integrated Circuits. Transient analysis. Discuss time marching methods used in SPICE ECE 570 Sessio 7 IC 75-E Compuer Aided Egieerig for Iegraed Circuis Trasie aalysis Discuss ime marcig meods used i SPICE. Time marcig meods. Explici ad implici iegraio meods 3. Implici meods used i circui

More information

6.01: Introduction to EECS I Lecture 3 February 15, 2011

6.01: Introduction to EECS I Lecture 3 February 15, 2011 6.01: Iroducio o EECS I Lecure 3 February 15, 2011 6.01: Iroducio o EECS I Sigals ad Sysems Module 1 Summary: Sofware Egieerig Focused o absracio ad modulariy i sofware egieerig. Topics: procedures, daa

More information

2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i)

2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i) Mah PracTes Be sure o review Lab (ad all labs) There are los of good quesios o i a) Sae he Mea Value Theorem ad draw a graph ha illusraes b) Name a impora heorem where he Mea Value Theorem was used i he

More information

Characteristics of Linear System

Characteristics of Linear System Characerisics o Linear Sysem h g h : Impulse response F G : Frequency ranser uncion Represenaion o Sysem in ime an requency. Low-pass iler g h G F he requency ranser uncion is he Fourier ransorm o he impulse

More information

6/10/2014. Definition. Time series Data. Time series Graph. Components of time series. Time series Seasonal. Time series Trend

6/10/2014. Definition. Time series Data. Time series Graph. Components of time series. Time series Seasonal. Time series Trend 6//4 Defiiio Time series Daa A ime series Measures he same pheomeo a equal iervals of ime Time series Graph Compoes of ime series 5 5 5-5 7 Q 7 Q 7 Q 3 7 Q 4 8 Q 8 Q 8 Q 3 8 Q 4 9 Q 9 Q 9 Q 3 9 Q 4 Q Q

More information

Stochastic Processes Adopted From p Chapter 9 Probability, Random Variables and Stochastic Processes, 4th Edition A. Papoulis and S.

Stochastic Processes Adopted From p Chapter 9 Probability, Random Variables and Stochastic Processes, 4th Edition A. Papoulis and S. Sochasic Processes Adoped From p Chaper 9 Probabiliy, adom Variables ad Sochasic Processes, 4h Ediio A. Papoulis ad S. Pillai 9. Sochasic Processes Iroducio Le deoe he radom oucome of a experime. To every

More information

PI3B V, 16-Bit to 32-Bit FET Mux/DeMux NanoSwitch. Features. Description. Pin Configuration. Block Diagram.

PI3B V, 16-Bit to 32-Bit FET Mux/DeMux NanoSwitch. Features. Description. Pin Configuration. Block Diagram. 33V, 6-Bi o 32-Bi FET Mux/DeMux NaoSwich Feaures -ohm Swich Coecio Bewee Two Pors Near-Zero Propagaio Delay Fas Swichig Speed: 4s (max) Ulra -Low Quiesce Power (02mA yp) Ideal for oebook applicaios Idusrial

More information

6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson

6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson 6.32 Feedback Syem Phae-locked loop are a foundaional building block for analog circui deign, paricularly for communicaion circui. They provide a good example yem for hi cla becaue hey are an excellen

More information

Digital Modulation Schemes

Digital Modulation Schemes Digial Modulaio cheme Digial ramiio chai igal repreeaio ime domai Frequecy domai igal pace Liear modulaio cheme Ampliude hi Keyig (AK) Phae hi Keyig (PK) Combiaio (APK, QAM) Pule hapig Coiuou Phae Modulaio

More information

Manipulations involving the signal amplitude (dependent variable).

Manipulations involving the signal amplitude (dependent variable). Oulie Maipulaio of discree ime sigals: Maipulaios ivolvig he idepede variable : Shifed i ime Operaios. Foldig, reflecio or ime reversal. Time Scalig. Maipulaios ivolvig he sigal ampliude (depede variable).

More information

6.003: Signals and Systems

6.003: Signals and Systems 6.003: Sigals ad Sysems Lecure 8 March 2, 2010 6.003: Sigals ad Sysems Mid-erm Examiaio #1 Tomorrow, Wedesday, March 3, 7:30-9:30pm. No reciaios omorrow. Coverage: Represeaios of CT ad DT Sysems Lecures

More information

FIR Filter Design: Part I

FIR Filter Design: Part I EEL3: Discrete-Time Sigals ad Systems FIR Filter Desig: Part I. Itroductio FIR Filter Desig: Part I I this set o otes, we cotiue our exploratio o the requecy respose o FIR ilters. First, we cosider some

More information

Clock Skew and Signal Representation. Program. Timing Engineering

Clock Skew and Signal Representation. Program. Timing Engineering lock Skew ad Sigal epreseaio h. 7 IBM Power 4 hip Iroducio ad moivaio Sequeial circuis, clock imig, Basic ools for frequecy domai aalysis Fourier series sigal represeaio Periodic sigals ca be represeed

More information

PI3B

PI3B 234789023478902347890223478902347890234789022347890234789023478902234789023478902347890223478902 Feaures Near-Zero propagaio delay -ohm swiches coec ipus o oupus Fas Swichig Speed - 4s max Permis Ho Iserio

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Sysems Prof. Mark Fowler Noe Se # Wha are Coninuous-Time Signals??? /6 Coninuous-Time Signal Coninuous Time (C-T) Signal: A C-T signal is defined on he coninuum of ime values. Tha is:

More information

Phys1112: DC and RC circuits

Phys1112: DC and RC circuits Name: Group Members: Dae: TA s Name: Phys1112: DC and RC circuis Objecives: 1. To undersand curren and volage characerisics of a DC RC discharging circui. 2. To undersand he effec of he RC ime consan.

More information

O & M Cost O & M Cost

O & M Cost O & M Cost 5/5/008 Turbie Reliabiliy, Maieace ad Faul Deecio Zhe Sog, Adrew Kusiak 39 Seamas Ceer Iowa Ciy, Iowa 54-57 adrew-kusiak@uiowa.edu Tel: 39-335-5934 Fax: 39-335-5669 hp://www.icae.uiowa.edu/~akusiak Oulie

More information

Chemistry 1B, Fall 2016 Topics 21-22

Chemistry 1B, Fall 2016 Topics 21-22 Cheisry B, Fall 6 Topics - STRUCTURE ad DYNAMICS Cheisry B Fall 6 Cheisry B so far: STRUCTURE of aos ad olecules Topics - Cheical Kieics Cheisry B ow: DYNAMICS cheical kieics herodyaics (che C, 6B) ad

More information

International Journal of Multidisciplinary Approach and Studies. Channel Capacity Analysis For L-Mrc Receiver Over Η-µ Fading Channel

International Journal of Multidisciplinary Approach and Studies. Channel Capacity Analysis For L-Mrc Receiver Over Η-µ Fading Channel Chael Capaciy Aalysis For L-Mrc eceiver Over Η-µ Fadig Chael Samom Jayaada Sigh* Pallab Dua** *NEIST, Deparme of ECE, Iaagar, Aruachal Pradesh-799, Idia **Tezpur Uiversiy, Deparme of ECE, Tezpur, Assam,

More information

Lecture 8 April 18, 2018

Lecture 8 April 18, 2018 Sas 300C: Theory of Saisics Sprig 2018 Lecure 8 April 18, 2018 Prof Emmauel Cades Scribe: Emmauel Cades Oulie Ageda: Muliple Tesig Problems 1 Empirical Process Viewpoi of BHq 2 Empirical Process Viewpoi

More information

Lecture 4. Goals: Be able to determine bandwidth of digital signals. Be able to convert a signal from baseband to passband and back IV-1

Lecture 4. Goals: Be able to determine bandwidth of digital signals. Be able to convert a signal from baseband to passband and back IV-1 Lecure 4 Goals: Be able o deermine bandwidh o digial signals Be able o conver a signal rom baseband o passband and back IV-1 Bandwidh o Digial Daa Signals A digial daa signal is modeled as a random process

More information