Receiver Architectures for FMT Broadband Wireless Systems

Size: px
Start display at page:

Download "Receiver Architectures for FMT Broadband Wireless Systems"

Transcription

1 Rcivr Architcturs for FMT Broadband Wirlss Systms Nvio Bnvnuto, Stfano Tomasin and Luciano Tomba Dipartimnto di Elttronica Informatica, Univrsity of Padova, via Gradnigo 6/A, I-3131 Padova, Italy Abstract Orthogonal Fruncy Division Multipling (OFDM) and in particular Discrt Multiton (DMT) modulation has bn proposd for th physical layr of widband wirlss local ara ntworks As an altrnativ, Filtrd Multiton (FMT) modulation can b also considrd, sinc it hibits significantly lowr spctral ovrlapping btwn adacnt subchannls, so providing highr transmission fficincy than DMT In this contribution, w invstigat th possibl advantags of FMT ovr DMT modulation for broadband wirlss applications in vry disprsiv channls and, in particular, w prsnt som simpl and ffctiv ualization algorithms 1 Introduction In this papr w considr multicarrir (MC) systms whr th intrpolating filtrs ar fruncy shifts of a givn prototyp filtr and th spacing btwn adacnt subcarrirs is th sam for all subcarrirs In fact, only in this cas th systm may b fficintly implmntd by mans of a (invrs) fast Fourir transform ((I)FFT) and a ntwork of polyphas filtrs [1, ] Morovr, w rstrict our analysis to two cass: i) DMT, whr th prototyp filtr has an idal rctangular tim-domain amplitud charactristic, and ii) FMT, whr th prototyp filtr has a narly rctangular fruncy domain amplitud charactristic Th scond choic implis invitabl intrsymbol intrfrnc (ISI) at th rcivr, whil intrcarrir intrfrnc (ICI) btwn subchannls is almost ngligibl whn an appropriat dsign of th prototyp filtr is carrid out Anothr possibl choic of th prototyp filtr is th suar-root Nyuist shap [3] In this cas, ICI is liminatd by incrasing th spacing btwn adacnt subcarrirs, at th pns of a lowr bandwidth fficincy Th pculiarity of DMT systms is that ualization of disprsiv channls is prformd simply by multiplying th signal at th output of ach subchannl by a cofficint that is rlatd to th channl fruncy rspons Howvr, this simpl schm works only if rdundancy, in trms of a prfi 1 of suitabl lngth [4], is insrtd in th transmittd signal, which, on th othr hand, lowrs th systm s spctral fficincy For this rason FMT has bn considrd and som simpl ualization schms for wirlss applications ar invstigatd This papr is organizd as follows In Sction w brifly outlin th systm modl In Sction 3 w invstigat som possibl ualization mthods for FMT systms and lastly in Sction 4 som prformanc comparisons ar prsntd Systm Modl W considr a multicarrir schm whr data signals,,,, with symbol rat! #", ar multipld in fruncy by using a bank of bandpass $!%'& finit impuls rspons (FIR) intrpolating filtrs )( +*,-, *, to produc th transmittd signal / +1, 134, at tim 1"768917: ; In particular th critically sampld filtr bank modulation [1, ] is dscribd; hnc th subcarrir spacing is ual $=& to! #" At th rcivr, a bank of FIR dcimation filtrs, >(?*,-, slcts $!%'& th information )( $@& for ach subchannl W assum that +*,- and )( +*,- ar non-zro only for *ACBED3F 3 Hr th transmit and rciv filtrs ar, rspctivly, th fruncy shift of two prototyp filtrs $#%?*,- and $?*,-, namly % & )(?*,GIHJLKCMON PEQ % +*,7 & >(?*,RSHJLKCMON PEQ?*,T (1) 1 Traditionally in wirlss applications, DMT with a cyclic prfi, is dnotd as orthogonal fruncy division multipling (OFDM) Notation: signals ar indicatd with lowrcas lttrs, whil thir Fourir transforms ar indicatd with th corrsponding upprcas lttrs UWV X Y, Z and [ dnot pctation, compl conugat and transposition, rspctivly; \ is th st of intgr numbrs and ]R^A_ Òa 3 Without loss of gnrality, w assum that bgc is an intgr multipl of d

2 f r ~ } ¼ k rk k fk n o p gh i u l l m v w gh i n o p t gh i s gh i t gh i s gh i { z y t g i t g i s g i y z { } } } ƒ t v w gh i s v w gh i n o p v w gh i l l m n o p gh i Figur 1 Efficint implmntation by IFFT and FFT of a MC systm basd on a uniform filtr bank Morovr, th prototyp rciv filtr is matchd to th transmit on, i +*,G %@ˆ?B D OŠ*, Fig 1 shows th fficint implmntation by IFFT and FFT of a MC systm $ $#%Œ basd on a uniform filtr bank, whr +A- and? -, 1)Ž, Ž CB S, ar th polyphas componnts $#% $#% of?*,- $ and?*,-, rspctivly Th choic of?*,- dtrmins th particular typ of multicarrir systm; in particular, whn it is an idal rctangular $#% puls th systm is calld DMT [4] Instad, whn?*,- is dsignd to minimiz th ovrlap btwn th fruncy rsponss of two adacnt subchannls, th corrsponding systm is calld FMT [1] In this systm ngligibl ICI is prsnt at th rcivr, whatvr th transmission channl is; howvr, ISI is always prsnt and an ualizr is ndd at th rcivr W dnot by $ +1- th uivalnt discrt-tim channl impuls rspons which is th sampld vrsion of th composd channl givn by th cascad of thr filtrs: th digital-to-analog (D/A) convrtr, th analog basband uivalnt radio channl and th analog-to-digital (A/D) convrtr Th D/A and A/D convrtrs ar dsignd to approimat an idal suar-root raisd cosin shap with Nyuist fruncy # #"'6 Th channl modl w hav usd for simulation is basd on th masurmnts mad for th widband local ara systm dnotd Wind-Fl [] Ths masurmnts provid a charactrization of th indoor radio channl at 17 GHz Two scnario ar considrd: a no lin of sight scnario, with a man š!a/ dlay sprad œ ž ns and a lin of sight scnario, with Ÿ ns Fading statistics ar Rayligh in both cass In particular, w assum that +18 at most for 1GŒ LB R Additiv compl-valud zro-man whit Gaussian nois (AWGN), +1, with varianc K is assumd to b suprimposd to th rcivd signal 3 Eualization Schms In th FMT systm almost no ICI ariss whatvr th transmission channl is, whil ISI is always prsnt in ach subchannl, vn if th transmission channl is idal ± ²³ ²³ ± ²³ µ ª «µ µ ± ²³ µ ª «Figur DFME ualizr for th FMT systm Hnc, it is mandatory to fac two problms: ualization of th transmit filtrs and ualization of th transmission channl In this sction, som simplifid ualizrs ar prsntd and compard with othr known ualization procdurs Lt s introduc th -point FFT of th channl impuls rspons, i ¹»ºL¼7½ À 7Á H JLKLMON P?1TO C ÃG () Dcision fdback multichannl ualizr (DFME) Assuming no ICI, th fdforward filtrs work on a subchannl bas A gnral solution, with an fficint rcivr implmntation [1, ], is rportd in Fig, whr a DFE is insrtd at th output of ach subchannl Although this schm may not b convnint for high rat applications bcaus of its computational complity and th fact that th filtr cofficints must b updatd at last at rgular tim intrvals to cop with th tim varying natur of th channl, w now driv its uations for an uppr bound on th systm prformanc Onc dfind th ovrall impuls rspons of th -th subchannl as ¹»Å¼7½ ¹ º ¼'½ &?*,G )( 7Á?*, Ç * ½ % & )( 'Á +* ½ * Q È K +* K T $ É ÊÊ ÊÊ (3) lt s indicat with +*,-, *ÌÍ CB Î, th $ É ÊÏT fdforward filtr of th Ê Ï -th subchannl and with?*,-, *ÐÑ C LB th corrsponding fdback filtr Thn w dfin th vctor containing th fd-

3 ó Ý Û B ý ö ö Q % ô " forward filtr cofficints as Ò ÊÊŒ ÔÓ É ÊÊ Õ? É ÊÊ Õ! É Ê ÊŒ ÖB Th autocorrlation matri of?*, has ntris ¹àß ß Ý Ó ÚÜÛ W ÞK 7Á?* ½ ˆ?* ½?1,âáÖL ¹ ßã ÞK Q È ½ +* K äáœåfæ ÊÊ ˆ +* K ä1tåfæ,å èç Ý K Þ is th powr of ach zro-man indpndnt and is a suitabl d- with î, th fdforward and fdback filtr can b dsignd as whr K $ idntically distributd signal Ö Œ-, æ lay From ÚÜÛ and th cross corrlation vctor éëê ntris Ó é)û ë Þ ˆ ÊÊ K æìíáö, á7lb F! ÙØ (4) É ÊÏ7?*,Rï whr *ì LB Ò Ê ÊŒ Ú ¹ ê ßß ¼'½ Ý 7Á ÊÏ ¼'½ é Û () (6) É ÊÊ?áÖ?1TåFæŽâáÖ7 (7) W point out that this schm has an high computational complity bcausêê ñ at ach ÊÊ channl stimat it ruirs th invrsion of ðb matrics Post-FFT simplifid DFME (postdfme) Lt us assum that ovr ach subchannl th fruncy rspons of th transmission channl is flat, i it has both a constant amplitud and a constant phas This condition is rlatd to th numbr of subchannls of th multicarrir systm and to th ratio btwn th š!a/ dlay sprad and " 6 Undr this assumption, from (1) and () th convolution btwn th -th transmit filtr and th transmission channl yilds 7Á +*Šä* ½ % & )(?* ½ Gò % & )( +*, HJLKLMON P Q % +*,) whr *íslbed>ä Hnc, th transmission channl can b adaptivly ualizd by a on tap pr subchannl ualizr, (8) OÂSŒ C à (9) as for DMT systms with cyclic prfi, whil th transmit filtrs can b ualizd by a static DFE Morovr, for th -th subchannl th cascad of transmit and rciv filtrs turns out to b indpndnt of th subchannl ind In fact øù û ö øù ú û þ þ þ ÿ ü ö øù û ö øù ú û Figur 3 postdfme ualizr for th FMT systm from (1) w gt %Œ +*,G % & )( 7Á +* ½ & )(?*, * ½ 7Á +* ½ +*, à * ½ T (1) $ Hnc, th fdforward and fdback filtrs ( ß ß $ +*,- and ß ã +*,- ) ar th sam for all subchannls and thy can b dsignd by using th standard DFE tchniu outlind in () (7) whr % is rplacd by Th rsulting ualization schm is rprsntd in Fig 3 for th -th subchannl W can pct to obtain som prformanc improvmnt by assuming a transmission channl with a linar phas within ach subchannl This linar trm corrsponds to th dlay of th -th subchannl $ and can b stimatd asily from th cofficints 8- As a first-ordr approimation of th dlay on th -th subchannl, w assum ½ "ìoâsœ C ÃG (11) whr dnots th angl of a compl numbr in th rang Ó O, To simplify intrpolation at th output of th FFT, ach signal is drivd at th ovrsampld rat "ë Thn it is dlayd of th uantity by a variabl phas intrpolator to yild Õ Ö " å ½ ¼ *Üå "! Ö ä*, (1) In our simulations th numbr of cofficints of th intrpolator filtr is "Õž In ordr to obtain th ovrsampld signal $# * :, th rcivr has two paralll structurs composd of a srial K&% to paralll convrtr, a filtr bank and a FFT Th input to th first structur is signal š?1 and th output yilds th vn sampls Õ Ö "ë Th input to th scond structur is a dlayd vrsion of th rcivd signal, š?1@åâ I, and th

4 C I ½ > = > * +, - / ' ( ) * * ξ 6 ; ξ = ; 79 Figur 4 prdfme ualizr for th FMT systm L Ö åï! " A rlativ output ar th odd sampls, rcivr with th addd fatur of tim intrpolator will b namd fractionally spacd (FS) ualizr Pr-FFT simplifid DFME (prdfme) In th prdfme th DFME is instad dirctly applid to th rcivd signal In this cas rciv filtrs ualiz th transmit filtrs whil th channl is ualizd by th on-tap pr subchannl structur In particular, th fdforward and fdback subchannl $BAŒÊÏT $BAŒÊÊ ÊÊ filtrs, +*,-, *ÂÑ CB ÊÏ 9, and?*,-, *AŽ CB, ar computd as DFE of th corrsponding $#% polyphas componnts of th transmit prototyp filtr, +*,- ; hnc thy ar diffrnt for ach branch of th rcivr filtr bank Th rsulting ualization $DC schm is rprsntd in Fig 4 If w dnot by Ö - $ E, 9 S, th input of th FFT, and by Õ Ö -, Î I, th FFT of th transmit data, this structur minimizs th man suar rror FHGI E è $BA ÊÊŒ L Ö KKJ, ïœ C S Th dsign of filtrs +*,- $BA ÊÏ7 L and?*,- can b ralizd using () (7) with th substitution of % with As it will b sn, for th sam filtr lngth, th prdfme is mor fficint than th postdfme, bcaus it nds to ualiz only th transmit filtrs Also for th prdfme, a FS approach can b usd 4 Prformanc Rsults Th prformanc of th various modulation and ualization tchnius hav bn tstd for th Wind-Fl scnario [] and assuming 9 ÑM and!!"'6) ž MHz Th channl impuls rspons is assumd known at th rcivr (i prfct channl stimation) and static, at last for th duration of on symbol Th avrag signal-to-nois ratio (SNR), namly th ratio btwn th powr of th signal /! +1 and th powr of th nois +1, is assumd db Th lngth of th prototyp transmit filtr is B D ODP Th prformanc is valuatd in trms of achivabl bitrat QSRUTW indicats th signal-to-disturbanc ratio at th dcision dvic for th -th subchannl Following th considrations mad in [1], th modifid SDR of th -th subchannl, QSRUTW, is givn in db by QSRT VÏ $QSRUT VÏ HW (13) whr WâXP db Th achivabl bit rat pr subchannl is givn by Y= :[Z\N] K QSRT å, ÂI, ãs ½ Á whr QSRT ïô ^K_a` Ncb d Th achivabl bit-rat for transmission is thrfor obtaind by summing up th Y= valus ovr th activ ; ¼7½ subchannls allocatd for transmission, i Y4Xf 7Á Y@ Th complmntary cumulativ distribution function (cdf) of Y is usd to compar th prformanc of diffrnt ó systms For DMT w hav usd a cyclic prfi [4] hg?œ!"'6i)åfž, to includ th A/D and D/A intrpolation filtrs lngth, and th rsulting systm is indicatd with DMT-CP For FMT th numbr Ê Ê of cofficintsêïof th fdforward and fdback filtr is B ÔD and B ïd, rspctivly In ordr to obtain a fair comparison with th simplifid FSprDFME and FSpostDFME, th FSDFME is also considrd Bfor rporting thir prformanc, w rcall th maor faturs of th various schms Firstly, FMT has a bttr bandwidth fficincy than DMT-CP, bcaus it dos not us any cyclic prfi Morovr, th FMT nds fwr virtual carrirs than DMT, sinc in this cas th spctrum of th transmittd signal is lss distortd by th filtr includd in th D/A convrtr, as obsrvd in [7] On th othr hand, FMT ualization, both with prdfme and postdfme, is basd on th assumption of subchannl flatnss Hnc ths schms show a prformanc dgradation for highr valus of th ratio!" 6 Fig and 6 rport th prformanc rsults of both DMT and FMT with diffrnt ualizr structurs in th two Wind-Fl scnarios Th bst prformanc is obviously achivd whn a DFME is implmntd Howvr, this rsult is usful only as a bnchmark sinc a similar

5 ualizr is impractical for radio applications Roughly th sam prformanc of DFME is achivd by mor practical ualizrs lik FSprDFME and prdfme Prformanc dgrads whn th FSpostDFME and th postdfme ar usd Indd th introduction of th subchannl dlay rcovry, both in FSprDFME and in FSpostDFME, allows for a slight prformanc improvmnt with rspct to th simplr prdfme and postdfme schms In any cas th prformanc is bttr than th DMT-CP schm Conclusions complmntary cdf FMT: FSpostDFME FMT: FSprDFME FMT: postdfme FMT: prdfme FMT: DFME DMT CP In this papr w hav prsntd ualization tchnius for wirlss FMT systms From th numrical rsults w may conclud that FMT-FSprDFME yilds bttr prformanc (in trms of achivabl bit rat) than DMT-CP and also than FMT-FSpostDFME Hnc, although FMT ruirs a modratly highr computational complity than DMT, it may b considrd as a possibl candidat for high spd transmission in disprsiv indoor/outdoor wirlss channls Howvr, whn th numbr of subcarrirs is vry high (g 6 or mor), th rcivr must b vry simpl (g for consumr lctronics), and th whol systm is synchronous, thn DMT with cyclic prfi may still rprsnt th most convnint solution complmntary cdf FMT: FSpostDFME FMT: FSprDFME FMT: postdfme FMT: prdfme FMT: DFME DMT CP ABR [Mbit/s] Figur Prformanc of DMT and FMT for diffrnt ualizr structurs: 9 ÑM, kgbmlï db, no lin of sight channl ABR [Mbit/s] Figur 6 Prformanc of DMT and FMT for diffrnt ualizr structurs: 9! M, kobml db, lin of sight channl digital subscribr lin IEEE Commun Mag, 38(): 98 14, May [] P P Vaidyanathan, Multirat systms and filtr banks, Englwood Cliffs, Prntic Hall, 1993 [3] S Kondo and L B Milstin Prformanc of multicarrir DS CDMA systms IEEE Trans on Commun, 44(): 38 46, Fbruary 1996 [4] JAC Bingham Multicarrir modulation for data transmission: an ida whos tim has com IEEE Commun Mag, 8(): 14, May 199 [] J L Garcia, M Lobria Channl charactrization and modl Wind-Fl Rport IST , procts/windfldlivrablshtm, DIII1, Dcmbr [6] PJW Mlsa, RC Younc and CE Rohrs Impuls rspons shortning for discrt multiton transcivrs IEEE Trans on Commun, 44(1): , Dcmbr 1996 [7] M Faulknr and S HTh ffct of filtring on th prformanc of OFDM systms In Proc ACTS 98 Summit, Rhods (Grc): 817 8, Jun 1998 Rfrncs [1] G Chrubini, E Elfthriou, S Ölçr and JM Cioffi Filtr bank modulation tchnius for vry high spd

ANALYSIS IN THE FREQUENCY DOMAIN

ANALYSIS IN THE FREQUENCY DOMAIN ANALYSIS IN THE FREQUENCY DOMAIN SPECTRAL DENSITY Dfinition Th spctral dnsit of a S.S.P. t also calld th spctrum of t is dfind as: + { γ }. jτ γ τ F τ τ In othr words, of th covarianc function. is dfind

More information

Communication Technologies

Communication Technologies Communication Tchnologis. Principls of Digital Transmission. Structur of Data Transmission.2 Spctrum of a Data Signal 2. Digital Modulation 2. Linar Modulation Mthods 2.2 Nonlinar Modulations (CPM-Signals)

More information

SER/BER in a Fading Channel

SER/BER in a Fading Channel SER/BER in a Fading Channl Major points for a fading channl: * SNR is a R.V. or R.P. * SER(BER) dpnds on th SNR conditional SER(BER). * Two prformanc masurs: outag probability and avrag SER(BER). * Ovrall,

More information

Gaussian and Flat Rayleigh Fading Channel Influences on PAPR Distribution in MIMO-OFDM Systems

Gaussian and Flat Rayleigh Fading Channel Influences on PAPR Distribution in MIMO-OFDM Systems Gaussian and Flat Rayligh Fading Channl Influncs on PAPR Distribution in MIMO-OFDM Systms Basl Rihawi and Yvs Louët IETR/Supélc - Campus d Rnns Avnu d la Boulai, BP 87, 355 Csson-Sévigné, Franc Tlphon:

More information

10. The Discrete-Time Fourier Transform (DTFT)

10. The Discrete-Time Fourier Transform (DTFT) Th Discrt-Tim Fourir Transform (DTFT Dfinition of th discrt-tim Fourir transform Th Fourir rprsntation of signals plays an important rol in both continuous and discrt signal procssing In this sction w

More information

A Sub-Optimal Log-Domain Decoding Algorithm for Non-Binary LDPC Codes

A Sub-Optimal Log-Domain Decoding Algorithm for Non-Binary LDPC Codes Procdings of th 9th WSEAS Intrnational Confrnc on APPLICATIONS of COMPUTER ENGINEERING A Sub-Optimal Log-Domain Dcoding Algorithm for Non-Binary LDPC Cods CHIRAG DADLANI and RANJAN BOSE Dpartmnt of Elctrical

More information

Supplementary Materials

Supplementary Materials 6 Supplmntary Matrials APPENDIX A PHYSICAL INTERPRETATION OF FUEL-RATE-SPEED FUNCTION A truck running on a road with grad/slop θ positiv if moving up and ngativ if moving down facs thr rsistancs: arodynamic

More information

Types of Transfer Functions. Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters

Types of Transfer Functions. Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters Typs of Transfr Typs of Transfr x[n] X( LTI h[n] H( y[n] Y( y [ n] h[ k] x[ n k] k Y ( H ( X ( Th tim-domain classification of an LTI digital transfr function is basd on th lngth of its impuls rspons h[n]:

More information

Search sequence databases 3 10/25/2016

Search sequence databases 3 10/25/2016 Sarch squnc databass 3 10/25/2016 Etrm valu distribution Ø Suppos X is a random variabl with probability dnsity function p(, w sampl a larg numbr S of indpndnt valus of X from this distribution for an

More information

Problem Set #2 Due: Friday April 20, 2018 at 5 PM.

Problem Set #2 Due: Friday April 20, 2018 at 5 PM. 1 EE102B Spring 2018 Signal Procssing and Linar Systms II Goldsmith Problm St #2 Du: Friday April 20, 2018 at 5 PM. 1. Non-idal sampling and rcovry of idal sampls by discrt-tim filtring 30 pts) Considr

More information

Bit-Loading Algorithms for OFDM with Adaptive Cyclic Prefix Length in PLC Channels

Bit-Loading Algorithms for OFDM with Adaptive Cyclic Prefix Length in PLC Channels Bit-Loading Algorithms for OFD with Adaptiv Cyclic Prfix Lngth in PLC Channls Salvator D Alssandro (), Andra. Tonllo (), and Lutz Lamp (3) (,) DIEG - Univrsità di Udin, Udin, Italy, -mail: salvator.dalssandro@uniud.it,

More information

Linear-Phase FIR Transfer Functions. Functions. Functions. Functions. Functions. Functions. Let

Linear-Phase FIR Transfer Functions. Functions. Functions. Functions. Functions. Functions. Let It is impossibl to dsign an IIR transfr function with an xact linar-phas It is always possibl to dsign an FIR transfr function with an xact linar-phas rspons W now dvlop th forms of th linarphas FIR transfr

More information

THE IMPACT OF A PRIORI INFORMATION ON THE MAP EQUALIZER PERFORMANCE WITH M-PSK MODULATION

THE IMPACT OF A PRIORI INFORMATION ON THE MAP EQUALIZER PERFORMANCE WITH M-PSK MODULATION 5th Europan Signal Procssing Confrnc (EUSIPCO 007), Poznan, Poland, Sptmbr 3-7, 007, copyright by EURASIP THE IMPACT OF A PRIORI INFORMATION ON THE MAP EQUALIZER PERFORMANCE WITH M-PSK MODULATION Chaabouni

More information

Chapter 6. The Discrete Fourier Transform and The Fast Fourier Transform

Chapter 6. The Discrete Fourier Transform and The Fast Fourier Transform Pusan ational Univrsity Chaptr 6. Th Discrt Fourir Transform and Th Fast Fourir Transform 6. Introduction Frquncy rsponss of discrt linar tim invariant systms ar rprsntd by Fourir transform or z-transforms.

More information

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation.

Fourier Transforms and the Wave Equation. Key Mathematics: More Fourier transform theory, especially as applied to solving the wave equation. Lur 7 Fourir Transforms and th Wav Euation Ovrviw and Motivation: W first discuss a fw faturs of th Fourir transform (FT), and thn w solv th initial-valu problm for th wav uation using th Fourir transform

More information

Higher order derivatives

Higher order derivatives Robrto s Nots on Diffrntial Calculus Chaptr 4: Basic diffrntiation ruls Sction 7 Highr ordr drivativs What you nd to know alrady: Basic diffrntiation ruls. What you can larn hr: How to rpat th procss of

More information

Construction of asymmetric orthogonal arrays of strength three via a replacement method

Construction of asymmetric orthogonal arrays of strength three via a replacement method isid/ms/26/2 Fbruary, 26 http://www.isid.ac.in/ statmath/indx.php?modul=prprint Construction of asymmtric orthogonal arrays of strngth thr via a rplacmnt mthod Tian-fang Zhang, Qiaoling Dng and Alok Dy

More information

A Low-Cost and High Performance Solution to Frequency Estimation for GSM/EDGE

A Low-Cost and High Performance Solution to Frequency Estimation for GSM/EDGE A Low-Cost and High Prformanc Solution to Frquncy Estimation for GSM/EDGE Wizhong Chn Lo Dhnr fwc@frscal.com ld@frscal.com 5-996- 5-996-75 77 Wst Parmr Ln 77 Wst Parmr Ln Austin, TX7879 Austin, TX7879

More information

Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters. Ideal Filters

Types of Transfer Functions. Types of Transfer Functions. Ideal Filters. Ideal Filters. Ideal Filters Typs of Transfr Typs of Transfr Th tim-domain classification of an LTI digital transfr function squnc is basd on th lngth of its impuls rspons: - Finit impuls rspons (FIR) transfr function - Infinit impuls

More information

Computing and Communications -- Network Coding

Computing and Communications -- Network Coding 89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc

More information

Einstein Equations for Tetrad Fields

Einstein Equations for Tetrad Fields Apiron, Vol 13, No, Octobr 006 6 Einstin Equations for Ttrad Filds Ali Rıza ŞAHİN, R T L Istanbul (Turky) Evry mtric tnsor can b xprssd by th innr product of ttrad filds W prov that Einstin quations for

More information

Frequency Correction

Frequency Correction Chaptr 4 Frquncy Corrction Dariush Divsalar Ovr th yars, much ffort has bn spnt in th sarch for optimum synchronizion schms th ar robust and simpl to implmnt [1,2]. Ths schms wr drivd basd on maximum-liklihood

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

Image Filtering: Noise Removal, Sharpening, Deblurring. Yao Wang Polytechnic University, Brooklyn, NY11201

Image Filtering: Noise Removal, Sharpening, Deblurring. Yao Wang Polytechnic University, Brooklyn, NY11201 Imag Filtring: Nois Rmoval, Sharpning, Dblurring Yao Wang Polytchnic Univrsity, Brooklyn, NY http://wb.poly.du/~yao Outlin Nois rmoval by avraging iltr Nois rmoval by mdian iltr Sharpning Edg nhancmnt

More information

Volterra Kernel Estimation for Nonlinear Communication Channels Using Deterministic Sequences

Volterra Kernel Estimation for Nonlinear Communication Channels Using Deterministic Sequences 1 Voltrra Krnl Estimation for Nonlinar Communication Channls Using Dtrministic Squncs Endr M. Ekşioğlu and Ahmt H. Kayran Dpartmnt of Elctrical and Elctronics Enginring, Istanbul Tchnical Univrsity, Istanbul,

More information

Lecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac.

Lecture 2: Discrete-Time Signals & Systems. Reza Mohammadkhani, Digital Signal Processing, 2015 University of Kurdistan eng.uok.ac. Lctur 2: Discrt-Tim Signals & Systms Rza Mohammadkhani, Digital Signal Procssing, 2015 Univrsity of Kurdistan ng.uok.ac.ir/mohammadkhani 1 Signal Dfinition and Exampls 2 Signal: any physical quantity that

More information

What are those βs anyway? Understanding Design Matrix & Odds ratios

What are those βs anyway? Understanding Design Matrix & Odds ratios Ral paramtr stimat WILD 750 - Wildlif Population Analysis of 6 What ar thos βs anyway? Undrsting Dsign Matrix & Odds ratios Rfrncs Hosmr D.W.. Lmshow. 000. Applid logistic rgrssion. John Wily & ons Inc.

More information

That is, we start with a general matrix: And end with a simpler matrix:

That is, we start with a general matrix: And end with a simpler matrix: DIAGON ALIZATION OF THE STR ESS TEN SOR INTRO DUCTIO N By th us of Cauchy s thorm w ar abl to rduc th numbr of strss componnts in th strss tnsor to only nin valus. An additional simplification of th strss

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

Numbering Systems Basic Building Blocks Scaling and Round-off Noise. Number Representation. Floating vs. Fixed point. DSP Design.

Numbering Systems Basic Building Blocks Scaling and Round-off Noise. Number Representation. Floating vs. Fixed point. DSP Design. Numbring Systms Basic Building Blocks Scaling and Round-off Nois Numbr Rprsntation Viktor Öwall viktor.owall@it.lth.s Floating vs. Fixd point In floating point a valu is rprsntd by mantissa dtrmining th

More information

EXST Regression Techniques Page 1

EXST Regression Techniques Page 1 EXST704 - Rgrssion Tchniqus Pag 1 Masurmnt rrors in X W hav assumd that all variation is in Y. Masurmnt rror in this variabl will not ffct th rsults, as long as thy ar uncorrlatd and unbiasd, sinc thy

More information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Procssing Prof. Mark Fowlr Dtails of th ot St #19 Rading Assignmnt: Sct. 7.1.2, 7.1.3, & 7.2 of Proakis & Manolakis Dfinition of th So Givn signal data points x[n] for n = 0,, -1

More information

SCALING OF SYNCHROTRON RADIATION WITH MULTIPOLE ORDER. J. C. Sprott

SCALING OF SYNCHROTRON RADIATION WITH MULTIPOLE ORDER. J. C. Sprott SCALING OF SYNCHROTRON RADIATION WITH MULTIPOLE ORDER J. C. Sprott PLP 821 Novmbr 1979 Plasma Studis Univrsity of Wisconsin Ths PLP Rports ar informal and prliminary and as such may contain rrors not yt

More information

GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES. Eduard N. Klenov* Rostov-on-Don, Russia

GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES. Eduard N. Klenov* Rostov-on-Don, Russia GEOMETRICAL PHENOMENA IN THE PHYSICS OF SUBATOMIC PARTICLES Eduard N. Klnov* Rostov-on-Don, Russia Th articl considrs phnomnal gomtry figurs bing th carrirs of valu spctra for th pairs of th rmaining additiv

More information

Basic Polyhedral theory

Basic Polyhedral theory Basic Polyhdral thory Th st P = { A b} is calld a polyhdron. Lmma 1. Eithr th systm A = b, b 0, 0 has a solution or thr is a vctorπ such that π A 0, πb < 0 Thr cass, if solution in top row dos not ist

More information

Carrier frequency estimation. ELEC-E5410 Signal processing for communications

Carrier frequency estimation. ELEC-E5410 Signal processing for communications Carrir frquncy stimation ELEC-E54 Signal procssing for communications Contnts. Basic systm assumptions. Data-aidd DA: Maximum-lilihood ML stimation of carrir frquncy 3. Data-aidd: Practical algorithms

More information

High-Performance WLAN Architectures Using MIMO Technology in Line-of-Sight

High-Performance WLAN Architectures Using MIMO Technology in Line-of-Sight igh-prformanc WLAN Architcturs Using MIMO Tchnology in Lin-of-Sight Ioannis Sarris, Angla Doufxi, and Andrw R. Nix Abstract This papr invstigats th Packt-Error-Rat () and throughput prformanc of WLANs

More information

Unquantized and Uncoded Channel State Information Feedback on Wireless Channels

Unquantized and Uncoded Channel State Information Feedback on Wireless Channels Unquantizd and Uncodd Channl Stat Information Fdback on Wirlss Channls Dragan Samardzija Bll Labs, Lucnt Tchnologis 791 Holmdl-Kyport Road, Holmdl, J 07733, USA Email: dragan@bll-labscom arayan Mandayam

More information

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches. Subjct Chmistry Papr No and Titl Modul No and Titl Modul Tag 8/ Physical Spctroscopy / Brakdown of th Born-Oppnhimr approximation. Slction ruls for rotational-vibrational transitions. P, R branchs. CHE_P8_M

More information

Recursive Estimation of Dynamic Time-Varying Demand Models

Recursive Estimation of Dynamic Time-Varying Demand Models Intrnational Confrnc on Computr Systms and chnologis - CompSysch 06 Rcursiv Estimation of Dynamic im-varying Dmand Modls Alxandr Efrmov Abstract: h papr prsnts an implmntation of a st of rcursiv algorithms

More information

Uplink channel estimation for multi-user OFDM-based systems

Uplink channel estimation for multi-user OFDM-based systems plink channl stimation for multi-usr OFDM-basd systms Carlos Ribiro *, M. Julia Frnándz-Gtino García, Víctor P. Gil Jiménz Atílio Gamiro* and Ana García Armada Instituto Politécnico d Liria, Morro do Lna,

More information

Symmetric centrosymmetric matrix vector multiplication

Symmetric centrosymmetric matrix vector multiplication Linar Algbra and its Applications 320 (2000) 193 198 www.lsvir.com/locat/laa Symmtric cntrosymmtric matrix vctor multiplication A. Mlman 1 Dpartmnt of Mathmatics, Univrsity of San Francisco, San Francisco,

More information

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS

Slide 1. Slide 2. Slide 3 DIGITAL SIGNAL PROCESSING CLASSIFICATION OF SIGNALS Slid DIGITAL SIGAL PROCESSIG UIT I DISCRETE TIME SIGALS AD SYSTEM Slid Rviw of discrt-tim signals & systms Signal:- A signal is dfind as any physical quantity that varis with tim, spac or any othr indpndnt

More information

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK

Data Assimilation 1. Alan O Neill National Centre for Earth Observation UK Data Assimilation 1 Alan O Nill National Cntr for Earth Obsrvation UK Plan Motivation & basic idas Univariat (scalar) data assimilation Multivariat (vctor) data assimilation 3d-Variational Mthod (& optimal

More information

Sliding Mode Flow Rate Observer Design

Sliding Mode Flow Rate Observer Design Sliding Mod Flow Rat Obsrvr Dsign Song Liu and Bin Yao School of Mchanical Enginring, Purdu Univrsity, Wst Lafaytt, IN797, USA liu(byao)@purdudu Abstract Dynamic flow rat information is ndd in a lot of

More information

4037 ADDITIONAL MATHEMATICS

4037 ADDITIONAL MATHEMATICS CAMBRIDGE INTERNATIONAL EXAMINATIONS GCE Ordinary Lvl MARK SCHEME for th Octobr/Novmbr 0 sris 40 ADDITIONAL MATHEMATICS 40/ Papr, maimum raw mark 80 This mark schm is publishd as an aid to tachrs and candidats,

More information

Linear Non-Gaussian Structural Equation Models

Linear Non-Gaussian Structural Equation Models IMPS 8, Durham, NH Linar Non-Gaussian Structural Equation Modls Shohi Shimizu, Patrik Hoyr and Aapo Hyvarinn Osaka Univrsity, Japan Univrsity of Hlsinki, Finland Abstract Linar Structural Equation Modling

More information

Two Products Manufacturer s Production Decisions with Carbon Constraint

Two Products Manufacturer s Production Decisions with Carbon Constraint Managmnt Scinc and Enginring Vol 7 No 3 pp 3-34 DOI:3968/jms9335X374 ISSN 93-34 [Print] ISSN 93-35X [Onlin] wwwcscanadant wwwcscanadaorg Two Products Manufacturr s Production Dcisions with Carbon Constraint

More information

Procdings of IC-IDC0 ( and (, ( ( and (, and (f ( and (, rspctivly. If two input signals ar compltly qual, phas spctra of two signals ar qual. That is

Procdings of IC-IDC0 ( and (, ( ( and (, and (f ( and (, rspctivly. If two input signals ar compltly qual, phas spctra of two signals ar qual. That is Procdings of IC-IDC0 EFFECTS OF STOCHASTIC PHASE SPECTRUM DIFFERECES O PHASE-OLY CORRELATIO FUCTIOS PART I: STATISTICALLY COSTAT PHASE SPECTRUM DIFFERECES FOR FREQUECY IDICES Shunsu Yamai, Jun Odagiri,

More information

Spectral Properties and Interpolation Error Analysis for Variable Sample Rate Conversion Systems

Spectral Properties and Interpolation Error Analysis for Variable Sample Rate Conversion Systems Spctral Proprtis and Intrpolation Error Analysis for Variabl Sampl Rat Convrsion Systms Andr Tkacnko Signal Procssing Rsarch Group Jt Propulsion Laboratory, California Institut of Tchnology 48 Oak Grov

More information

Estimation of apparent fraction defective: A mathematical approach

Estimation of apparent fraction defective: A mathematical approach Availabl onlin at www.plagiarsarchlibrary.com Plagia Rsarch Library Advancs in Applid Scinc Rsarch, 011, (): 84-89 ISSN: 0976-8610 CODEN (USA): AASRFC Estimation of apparnt fraction dfctiv: A mathmatical

More information

Sequential Decentralized Detection under Noisy Channels

Sequential Decentralized Detection under Noisy Channels Squntial Dcntralizd Dtction undr Noisy Channls Yasin Yilmaz Elctrical Enginring Dpartmnt Columbia Univrsity Nw Yor, NY 1007 Email: yasin@.columbia.du Gorg Moustaids Dpt. of Elctrical & Computr Enginring

More information

Full Waveform Inversion Using an Energy-Based Objective Function with Efficient Calculation of the Gradient

Full Waveform Inversion Using an Energy-Based Objective Function with Efficient Calculation of the Gradient Full Wavform Invrsion Using an Enrgy-Basd Objctiv Function with Efficint Calculation of th Gradint Itm yp Confrnc Papr Authors Choi, Yun Sok; Alkhalifah, ariq Ali Citation Choi Y, Alkhalifah (217) Full

More information

Section 11.6: Directional Derivatives and the Gradient Vector

Section 11.6: Directional Derivatives and the Gradient Vector Sction.6: Dirctional Drivativs and th Gradint Vctor Practic HW rom Stwart Ttbook not to hand in p. 778 # -4 p. 799 # 4-5 7 9 9 35 37 odd Th Dirctional Drivativ Rcall that a b Slop o th tangnt lin to th

More information

Exam 1. It is important that you clearly show your work and mark the final answer clearly, closed book, closed notes, no calculator.

Exam 1. It is important that you clearly show your work and mark the final answer clearly, closed book, closed notes, no calculator. Exam N a m : _ S O L U T I O N P U I D : I n s t r u c t i o n s : It is important that you clarly show your work and mark th final answr clarly, closd book, closd nots, no calculator. T i m : h o u r

More information

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA NE APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA Mirca I CÎRNU Ph Dp o Mathmatics III Faculty o Applid Scincs Univrsity Polithnica o Bucharst Cirnumirca @yahoocom Abstract In a rcnt papr [] 5 th indinit intgrals

More information

A Cost Function Level Analysis of Autocorrelation Minimization Based Blind Adaptive Channel Shorteners

A Cost Function Level Analysis of Autocorrelation Minimization Based Blind Adaptive Channel Shorteners A Cost Function Lvl Analysis of Autocorrlation Minimization Basd Blind Adaptiv Channl Shortnrs Ciira wa Maina Dpt. of Elc. Comp. Eng. Drxl Univrsity Philadlphia, PA 94 Email: cm57@drxl.du (Invitd Papr)

More information

EEO 401 Digital Signal Processing Prof. Mark Fowler

EEO 401 Digital Signal Processing Prof. Mark Fowler EEO 401 Digital Signal Procssing Prof. Mark Fowlr ot St #18 Introduction to DFT (via th DTFT) Rading Assignmnt: Sct. 7.1 of Proakis & Manolakis 1/24 Discrt Fourir Transform (DFT) W v sn that th DTFT is

More information

Capturing. Fig. 1: Transform. transform. of two time. series. series of the. Fig. 2:

Capturing. Fig. 1: Transform. transform. of two time. series. series of the. Fig. 2: Appndix: Nots on signal procssing Capturing th Spctrum: Transform analysis: Th discrt Fourir transform A digital spch signal such as th on shown in Fig. 1 is a squnc of numbrs. Fig. 1: Transform analysis

More information

1 Minimum Cut Problem

1 Minimum Cut Problem CS 6 Lctur 6 Min Cut and argr s Algorithm Scribs: Png Hui How (05), Virginia Dat: May 4, 06 Minimum Cut Problm Today, w introduc th minimum cut problm. This problm has many motivations, on of which coms

More information

4.2 Design of Sections for Flexure

4.2 Design of Sections for Flexure 4. Dsign of Sctions for Flxur This sction covrs th following topics Prliminary Dsign Final Dsign for Typ 1 Mmbrs Spcial Cas Calculation of Momnt Dmand For simply supportd prstrssd bams, th maximum momnt

More information

Network Congestion Games

Network Congestion Games Ntwork Congstion Gams Assistant Profssor Tas A&M Univrsity Collg Station, TX TX Dallas Collg Station Austin Houston Bst rout dpnds on othrs Ntwork Congstion Gams Travl tim incrass with congstion Highway

More information

A Propagating Wave Packet Group Velocity Dispersion

A Propagating Wave Packet Group Velocity Dispersion Lctur 8 Phys 375 A Propagating Wav Packt Group Vlocity Disprsion Ovrviw and Motivation: In th last lctur w lookd at a localizd solution t) to th 1D fr-particl Schrödingr quation (SE) that corrsponds to

More information

Homotopy perturbation technique

Homotopy perturbation technique Comput. Mthods Appl. Mch. Engrg. 178 (1999) 257±262 www.lsvir.com/locat/cma Homotopy prturbation tchniqu Ji-Huan H 1 Shanghai Univrsity, Shanghai Institut of Applid Mathmatics and Mchanics, Shanghai 272,

More information

ECE 344 Microwave Fundamentals

ECE 344 Microwave Fundamentals ECE 44 Microwav Fundamntals Lctur 08: Powr Dividrs and Couplrs Part Prpard By Dr. hrif Hkal 4/0/08 Microwav Dvics 4/0/08 Microwav Dvics 4/0/08 Powr Dividrs and Couplrs Powr dividrs, combinrs and dirctional

More information

Quaternion Fourier Transform for Colour Images

Quaternion Fourier Transform for Colour Images Vikas R. Duby / (IJCSIT) Intrnational Journal of Computr Scinc and Information Tchnologis, Vol. 5 (3), 4, 44-446 Quatrnion Fourir Transform for Colour Imags Vikas R. Duby Elctronics, Mumbai Univrsity VJTI,

More information

Mathematics. Complex Number rectangular form. Quadratic equation. Quadratic equation. Complex number Functions: sinusoids. Differentiation Integration

Mathematics. Complex Number rectangular form. Quadratic equation. Quadratic equation. Complex number Functions: sinusoids. Differentiation Integration Mathmatics Compl numbr Functions: sinusoids Sin function, cosin function Diffrntiation Intgration Quadratic quation Quadratic quations: a b c 0 Solution: b b 4ac a Eampl: 1 0 a= b=- c=1 4 1 1or 1 1 Quadratic

More information

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim. MTH rviw part b Lucian Mitroiu Th LOG and EXP functions Th ponntial function p : R, dfind as Proprtis: lim > lim p Eponntial function Y 8 6 - -8-6 - - X Th natural logarithm function ln in US- log: function

More information

2.3 Matrix Formulation

2.3 Matrix Formulation 23 Matrix Formulation 43 A mor complicatd xampl ariss for a nonlinar systm of diffrntial quations Considr th following xampl Exampl 23 x y + x( x 2 y 2 y x + y( x 2 y 2 (233 Transforming to polar coordinats,

More information

First derivative analysis

First derivative analysis Robrto s Nots on Dirntial Calculus Chaptr 8: Graphical analysis Sction First drivativ analysis What you nd to know alrady: How to us drivativs to idntiy th critical valus o a unction and its trm points

More information

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018 Propositional Logic Combinatorial Problm Solving (CPS) Albrt Olivras Enric Rodríguz-Carbonll May 17, 2018 Ovrviw of th sssion Dfinition of Propositional Logic Gnral Concpts in Logic Rduction to SAT CNFs

More information

There is an arbitrary overall complex phase that could be added to A, but since this makes no difference we set it to zero and choose A real.

There is an arbitrary overall complex phase that could be added to A, but since this makes no difference we set it to zero and choose A real. Midtrm #, Physics 37A, Spring 07. Writ your rsponss blow or on xtra pags. Show your work, and tak car to xplain what you ar doing; partial crdit will b givn for incomplt answrs that dmonstrat som concptual

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 0 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat th

More information

Difference -Analytical Method of The One-Dimensional Convection-Diffusion Equation

Difference -Analytical Method of The One-Dimensional Convection-Diffusion Equation Diffrnc -Analytical Mthod of Th On-Dimnsional Convction-Diffusion Equation Dalabav Umurdin Dpartmnt mathmatic modlling, Univrsity of orld Economy and Diplomacy, Uzbistan Abstract. An analytical diffrncing

More information

Observer Bias and Reliability By Xunchi Pu

Observer Bias and Reliability By Xunchi Pu Obsrvr Bias and Rliability By Xunchi Pu Introduction Clarly all masurmnts or obsrvations nd to b mad as accuratly as possibl and invstigators nd to pay carful attntion to chcking th rliability of thir

More information

Derangements and Applications

Derangements and Applications 2 3 47 6 23 Journal of Intgr Squncs, Vol. 6 (2003), Articl 03..2 Drangmnts and Applications Mhdi Hassani Dpartmnt of Mathmatics Institut for Advancd Studis in Basic Scincs Zanjan, Iran mhassani@iasbs.ac.ir

More information

EE140 Introduction to Communication Systems Lecture 2

EE140 Introduction to Communication Systems Lecture 2 EE40 Introduction to Communication Systms Lctur 2 Instructor: Prof. Xiliang Luo ShanghaiTch Univrsity, Spring 208 Architctur of a Digital Communication Systm Transmittr Sourc A/D convrtr Sourc ncodr Channl

More information

Outline. Image processing includes. Edge detection. Advanced Multimedia Signal Processing #8:Image Processing 2 processing

Outline. Image processing includes. Edge detection. Advanced Multimedia Signal Processing #8:Image Processing 2 processing Outlin Advancd Multimdia Signal Procssing #8:Imag Procssing procssing Intllignt Elctronic Sstms Group Dpt. of Elctronic Enginring, UEC aaui agai Imag procssing includs Imag procssing fundamntals Edg dtction

More information

Chapter 13 GMM for Linear Factor Models in Discount Factor form. GMM on the pricing errors gives a crosssectional

Chapter 13 GMM for Linear Factor Models in Discount Factor form. GMM on the pricing errors gives a crosssectional Chaptr 13 GMM for Linar Factor Modls in Discount Factor form GMM on th pricing rrors givs a crosssctional rgrssion h cas of xcss rturns Hors rac sting for charactristic sting for pricd factors: lambdas

More information

Least Favorable Distributions to Facilitate the Design of Detection Systems with Sensors at Deterministic Locations

Least Favorable Distributions to Facilitate the Design of Detection Systems with Sensors at Deterministic Locations Last Favorabl Distributions to Facilitat th Dsign o Dtction Systms with Snsors at Dtrministic Locations Bndito J. B. Fonsca Jr. Sptmbr 204 2 Motivation Rgion o intrst (city, park, stadium 3 Motivation

More information

2008 AP Calculus BC Multiple Choice Exam

2008 AP Calculus BC Multiple Choice Exam 008 AP Multipl Choic Eam Nam 008 AP Calculus BC Multipl Choic Eam Sction No Calculator Activ AP Calculus 008 BC Multipl Choic. At tim t 0, a particl moving in th -plan is th acclration vctor of th particl

More information

PHASE-ONLY CORRELATION IN FINGERPRINT DATABASE REGISTRATION AND MATCHING

PHASE-ONLY CORRELATION IN FINGERPRINT DATABASE REGISTRATION AND MATCHING Anall Univrsităţii d Vst din Timişoara Vol. LII, 2008 Sria Fizică PHASE-OLY CORRELATIO I FIGERPRIT DATABASE REGISTRATIO AD ATCHIG Alin C. Tusda, 2 Gianina Gabor Univrsity of Orada, Environmntal Faculty,

More information

Introduction to the Fourier transform. Computer Vision & Digital Image Processing. The Fourier transform (continued) The Fourier transform (continued)

Introduction to the Fourier transform. Computer Vision & Digital Image Processing. The Fourier transform (continued) The Fourier transform (continued) Introduction to th Fourir transform Computr Vision & Digital Imag Procssing Fourir Transform Lt f(x) b a continuous function of a ral variabl x Th Fourir transform of f(x), dnotd by I {f(x)} is givn by:

More information

1 Isoparametric Concept

1 Isoparametric Concept UNIVERSITY OF CALIFORNIA BERKELEY Dpartmnt of Civil Enginring Spring 06 Structural Enginring, Mchanics and Matrials Profssor: S. Govindj Nots on D isoparamtric lmnts Isoparamtric Concpt Th isoparamtric

More information

Addition of angular momentum

Addition of angular momentum Addition of angular momntum April, 07 Oftn w nd to combin diffrnt sourcs of angular momntum to charactriz th total angular momntum of a systm, or to divid th total angular momntum into parts to valuat

More information

cycle that does not cross any edges (including its own), then it has at least

cycle that does not cross any edges (including its own), then it has at least W prov th following thorm: Thorm If a K n is drawn in th plan in such a way that it has a hamiltonian cycl that dos not cross any dgs (including its own, thn it has at last n ( 4 48 π + O(n crossings Th

More information

Discrete Hilbert Transform. Numeric Algorithms

Discrete Hilbert Transform. Numeric Algorithms Volum 49, umbr 4, 8 485 Discrt Hilbrt Transform. umric Algorithms Ghorgh TODORA, Rodica HOLOEC and Ciprian IAKAB Abstract - Th Hilbrt and Fourir transforms ar tools usd for signal analysis in th tim/frquncy

More information

3 Finite Element Parametric Geometry

3 Finite Element Parametric Geometry 3 Finit Elmnt Paramtric Gomtry 3. Introduction Th intgral of a matrix is th matrix containing th intgral of ach and vry on of its original componnts. Practical finit lmnt analysis rquirs intgrating matrics,

More information

1973 AP Calculus AB: Section I

1973 AP Calculus AB: Section I 97 AP Calculus AB: Sction I 9 Minuts No Calculator Not: In this amination, ln dnots th natural logarithm of (that is, logarithm to th bas ).. ( ) d= + C 6 + C + C + C + C. If f ( ) = + + + and ( ), g=

More information

Solution: APPM 1360 Final (150 pts) Spring (60 pts total) The following parts are not related, justify your answers:

Solution: APPM 1360 Final (150 pts) Spring (60 pts total) The following parts are not related, justify your answers: APPM 6 Final 5 pts) Spring 4. 6 pts total) Th following parts ar not rlatd, justify your answrs: a) Considr th curv rprsntd by th paramtric quations, t and y t + for t. i) 6 pts) Writ down th corrsponding

More information

2F1120 Spektrala transformer för Media Solutions to Steiglitz, Chapter 1

2F1120 Spektrala transformer för Media Solutions to Steiglitz, Chapter 1 F110 Spktrala transformr för Mdia Solutions to Stiglitz, Chaptr 1 Prfac This documnt contains solutions to slctd problms from Kn Stiglitz s book: A Digital Signal Procssing Primr publishd by Addison-Wsly.

More information

DISTRIBUTED SPATIAL DIVERSITY TECHNIQUES FOR IMPROVING MOBILE AD-HOC NETWORK PERFORMANCE

DISTRIBUTED SPATIAL DIVERSITY TECHNIQUES FOR IMPROVING MOBILE AD-HOC NETWORK PERFORMANCE DISTRIBUTD SPATIAL DIRSITY TCHNIQUS FOR IMPROING MOBIL AD-HOC NTWORK PRFORMANC J. Nicholas Lanman Grgory W. Wornll Digital Signal Procssing Group Massachustts Institut of Tchnology Cambridg, MA 239 ABSTRACT

More information

Text: WMM, Chapter 5. Sections , ,

Text: WMM, Chapter 5. Sections , , Lcturs 6 - Continuous Probabilit Distributions Tt: WMM, Chaptr 5. Sctions 6.-6.4, 6.6-6.8, 7.-7. In th prvious sction, w introduc som of th common probabilit distribution functions (PDFs) for discrt sampl

More information

Contemporary, atomic, nuclear, and particle physics

Contemporary, atomic, nuclear, and particle physics Contmporary, atomic, nuclar, and particl physics 1 Blackbody radiation as a thrmal quilibrium condition (in vacuum this is th only hat loss) Exampl-1 black plan surfac at a constant high tmpratur T h is

More information

A New Optical Waveguide for Implementation of Multi-wavelengths Narrowband Filters for DWDM Systems

A New Optical Waveguide for Implementation of Multi-wavelengths Narrowband Filters for DWDM Systems IJCSNS Intrnational Journal of Computr Scinc and Ntwork Scurity, VOL.6 No.8B, August 6 39 A Nw Optical Wavguid for Implmntation of Multi-wavlngths Narrowband Filtrs for DWDM Systms A. Rostami [a, b] a)-

More information

Quasi-Classical States of the Simple Harmonic Oscillator

Quasi-Classical States of the Simple Harmonic Oscillator Quasi-Classical Stats of th Simpl Harmonic Oscillator (Draft Vrsion) Introduction: Why Look for Eignstats of th Annihilation Oprator? Excpt for th ground stat, th corrspondnc btwn th quantum nrgy ignstats

More information

Math 34A. Final Review

Math 34A. Final Review Math A Final Rviw 1) Us th graph of y10 to find approimat valus: a) 50 0. b) y (0.65) solution for part a) first writ an quation: 50 0. now tak th logarithm of both sids: log() log(50 0. ) pand th right

More information

Extraction of Signals Buried in Noise: Non-Ergodic Processes

Extraction of Signals Buried in Noise: Non-Ergodic Processes Int J Communications Ntwor and Systm Scincs 00 3 907-95 doi:0436/ijcns0034 Publishd Onlin Dcmbr 00 (http://wwwscirporg/journal/ijcns) Extraction of Signals Burid in Nois: Non-Ergodic Procsss Abstract Nourédin

More information

Title: Vibrational structure of electronic transition

Title: Vibrational structure of electronic transition Titl: Vibrational structur of lctronic transition Pag- Th band spctrum sn in th Ultra-Violt (UV) and visibl (VIS) rgions of th lctromagntic spctrum can not intrprtd as vibrational and rotational spctrum

More information

AS 5850 Finite Element Analysis

AS 5850 Finite Element Analysis AS 5850 Finit Elmnt Analysis Two-Dimnsional Linar Elasticity Instructor Prof. IIT Madras Equations of Plan Elasticity - 1 displacmnt fild strain- displacmnt rlations (infinitsimal strain) in matrix form

More information