Coherent PSK. The functional model of passband data transmission system is. Signal transmission encoder. x Signal. decoder.
|
|
- Griselda Barker
- 5 years ago
- Views:
Transcription
1 Cheren PSK he funcinal mdel f passand daa ransmissin sysem is m i Signal ransmissin encder si s i Signal Mdular Channel Deecr ransmissin decder mˆ Carrier signal m i is a sequence f syml emied frm a message surce. he channel is linear, wih a andwidh ha is wide enugh ransmi he mdulaed signal and he channel nise is Gaussian disriued wih zer mean and pwer specral densiy /. PB.9
2 Cheren PSK he fllwing parameers are cnsidered fr a signaling scheme: Prailiy f errr A majr gal f passand daa ransmissin sysems is he pimum design f he receiver s as minimize he average prailiy f syml errr in he presence f addiive whie Gaussian nise AWG P e PB.
3 Cheren PSK Pwer specra Use deermine he signal andwidh and c-channel inerference in mulipleed sysems. Mulipleer inerference In pracice, he signalings are linear perain, herefre, i is sufficien evaluae he aseand pwer specral densiy. B B PB.
4 Cheren PSK ample: Raised csine specrum α.5 Binary Phase shif keying BPSK +αr.5r R PB.
5 Bandwidh fficiency Cheren PSK R Bandwidh efficiency ρ is/s/hz B where R is he daa rae and B is he used channel andwidh. ample: yquis channel fr aseand daa ransmissin Bandwidh B W /. ρ R B / / is/s/hz W PB.3
6 Cheren PSK In a cheren inary PSK sysem, he pair f signals s and s used represen inary symls and, respecively, is defined y s csπf c s csπf c + π csπf c where per i, and is he ransmied signal energy PB.4
7 Cheren PSK ample: [ ] s d cs πf c d ensure ha each ransmied i cnains an inegral numer f cycles f he carrier wave, he carrier frequency f c is chsen equal n / fr sme fied ineger n. / f c PB.5
8 Cheren PSK he ransmied signal can e wrien as s φ s φ and where φ csπf c < e : φ csπf c d PB.6
9 Generain f cheren inary PSK signals generae a inary PSK signal, he firs sep is represening he inpu inary sequence in plar frm wih symls and represened y cnsan ampliude levels f and, respecively. his signal ransmissin encder is perfrmed y a plar nnreurn--zer RZ encder. s i + inpu syml is inpu symlis Signal ransmissin si encder PB.7
10 Generain f cheren inary PSK signals he secnd sep is muliplying he carrier encder upu wih he carrier s i s s f n / c csπf c csπf c if if s i s s i i Prduc Mdular φ csπf c s i PB.8
11 Deecin f cheren inary PSK signals deec he riginal inary sequence f s and s, we apply he nisy PSK signal a crrelar. he crrelar upu is cmpared wih a hreshld f zer vls. X Decisin device if if > < φ Crrelar PB.9
12 PB.3 Deecin f cheren inary PSK signals ample If he ransmied syml is, and he crrelar upu is Similarly, if he ransmied syml is,. cs f c π c c c d f d f f d cs cs cs π π π φ
13 rrr prailiy f inary PSK We can represen a cheren inary sysem wih a signal cnsellain cnsising f w message pins. he crdinaes f he message pins are all he pssile crrelar upu under a niseless cndiin. he crdinaes fr BPSK are Decisin undary and. φ PB.3
14 rrr prailiy f inary PSK here are w pssile kinds f errneus decisin: Signal s is ransmied, u he nise is such ha he received signal pin inside regin wih > and s he receiver decides in favr f signal. s s Signal is ransmied, u he nise is such ha he received signal pin inside regin wih < and s he receiver decides in favr f signal s. s i + w X Decisin device if if > < φ PB.3
15 rrr prailiy f inary PSK Fr he firs case, he servale elemen is relaed he received signal y [ s + w ] i φ d + φ d w φ d is a Gaussian prcess wih mean : i [ i [ ] + w φ d] PB.33
16 PB.34 rrr prailiy f inary PSK Variance is ] [ ] [ i i d ddu u u ddu u w u w ddu u w u w d w φ φ φ δ φ φ φ φ φ σ
17 PB.35 rrr prailiy f inary PSK herefre, he cndiinal prailiy densiy funcin f, given ha syml was ransmied is + f ep ep π σ πσ
18 rrr prailiy f inary PSK and he prailiy f errr is p f π d + ep Puing z +, we have p π erfc / ep [ z ] dz d PB.36
19 PB.37 rrr prailiy f inary PSK Similarly, he errr f he secnd kind p p erfc and hence e p erfc
20 PB.38 rrr prailiy he prailiy f i errr rae is prprinal he disance eween he clses pins in he cnsellain. BPSK Binary FSK e d erfc erfc P e d erfc erfc P d d
21 ransmissin Bandwidh he pwer specral densiy PSD f he BPSK fr h recangular and raised csine rllff pulse shapes are pled. null--null andwidh R +αr.5r ρ R B R R.5 ps/hz PB.39
22 Quadriphase-shif keying QPSK QPSK has wice he andwih efficiency f BPSK, since is are ransmied in a single mdulain syml. he daa inpu d k is divided in an in-phase sream d I, and a quadraure sream. d Q d k d I : : d Q : PB.4
23 QPSK d k d I d Q PB.4
24 QPSK he phase f he carrier akes n ne f fur equally spaced values, such as π/4, 3π/4, 5π/4, and 7π/4. s i where i,,3,4. cs[πf c + i π / 4] elsewhere is he ransmied signal energy per syml; is he syml durain; f c n / ; e : PB.4
25 PB.43 QPSK he ransmied signal can e wrien as 4] / ]sin[ sin[ 4] / ]cs[ cs[ 4] / cs[ s s i f i f i f s i i c c c i φ φ π π π π π π + + where ] sin[ ]; cs[ f f c c π φ π φ
26 s / r / i s / r / i QPSK φ / / φ PB.44
27 QPSK ach pssile value f he phase crrespnds a unique dii. Fr eample: Gray cde nly a single i is change frm ne dii he ne PB.45
28 QPSK Differen QPSK ses can e derived y simply raing he cnsellain. PB.46
29 PB.47
30 Generain f cheren QPSK signals he incming inary daa sequence is firs ransfrmed in plar frm y a nnreurn--zer level encder. he inary wave is ne divided y means f a demulipleer in w separae inary sequences. he resul can e regarded as a pair f inary PSK signals, which may e deeced independenly due he rhgnaliy f φ and φ. PB.48
31 φ csπf c s i X si Plar RZ Demulipleer + s s i X φ sinπf c PB.49
32 Deecin f cheren QPSK signals X Decisin device if if < > φ In-phase channel mulipleer Quadraure channel X Decisin device if if > < φ PB.5
33 PB.5 rrr prailiy f QPSK he received signal is w s i + and he servain elemens are + ± d w d / φ φ + ± d w d / φ φ
34 As a cheren QPSK is equivalen w cheren inary PSK sysems wrking in parallel and using w carriers ha are in phase quadraure. Hence, he average prailiy f i errr in each channel f he cheren QPSK sysem is p erfc / erfc PB.5
35 PB.53 rrr prailiy f QPSK As he i errr in he in-phase and quadraure channels f he cheren QPSK sysem are saisically independen, he average prailiy f a crrec decisin resuling frm he cmined acin f he w channels is + c p p erfc 4 erfc erfc
36 PB.54 he average prailiy f syml errr fr cheren QPSK is herefre / if erfc erfc 4 erfc >> c e p p
37 In a QPSK sysem, since here are w is per syml, he ransmied signal energy per syml is wice he signal energy per i, and hen d k p e erfc d I d Q PB.55
38 Wih Gray encding, he i errr rae f QPSK is BR erfc herefre, a cheren QPSK sysem achieves he same average prailiy f i errr as a cheren inary PSK sysem fr he same i rae and he same / u uses nly half he channel andwidh. PB.56
39 PB.57 e: he prailiy f i errr rae is als prprinal he disance eween he clses pins in he cnsellain. d erfc erfc BR d / /
40 ransmissin Bandwidh Pwer specral densiy PSD f he QPSK fr h recangular and raised csine rllff pulse shapes: null--null andwidh R ρ R B R R ps/hz +αr /.75R PB.58
41 M-ary PSK During each signaling inerval f durain, ne f he M pssile signals s i is sen. π csπf c + i i,,..., M lg lg M M PB.59
42 s i M-ary PSK π π cs φ cs πf φ sin πf i φ cs i φ c c PB.6
43 M-ary PSK he signal cnsellain f M-ary PSK cnsiss f M message pins which are equally spaced n a circle f radius. Fr eample, he cnsellain f 8-ary phase-shif keying is M sin π / π / M d he average prailiy f syml errr is P e π erfc sin M 4 M d erfc PB.6
44 ransmissin Bandwidh Pwer specral densiy PSD f he M-ary PSK fr h recangular and raised csine rllff pulse shapes: PB.6
45 ransmissin Bandwidh ull--null andwidh efficiency f a M-ary PSK signal: ρ R B R / lg R M lg M ps/hz M ρ / BR PB.63
Lecture 8. Digital Communications Part III. Digital Demodulation
Lecure 8. Digial Communicaions Par III. Digial Demodulaion Binary Deecion M-ary Deecion Lin Dai (Ciy Universiy of Hong Kong) EE38 Principles of Communicaions Lecure 8 Analog Signal Source SOURCE A-D Conversion
More informationMultiphase Shift Keying (MPSK) Lecture 8. Constellation. Decision Regions. s i. 2 T cos 2π f c t iφ 0 t As iφ 1 t. t As. A c i.
π fc uliphase Shif Keying (PSK) Goals Lecure 8 Be able o analyze PSK modualion s i Ac i Ac Pcos π f c cos π f c iφ As iφ π i p p As i sin π f c p Be able o analyze QA modualion Be able o quanify he radeoff
More informationBlock Diagram of a DCS in 411
Informaion source Forma A/D From oher sources Pulse modu. Muliplex Bandpass modu. X M h: channel impulse response m i g i s i Digial inpu Digial oupu iming and synchronizaion Digial baseband/ bandpass
More information28. Narrowband Noise Representation
Narrowband Noise Represenaion on Mac 8. Narrowband Noise Represenaion In mos communicaion sysems, we are ofen dealing wih band-pass filering of signals. Wideband noise will be shaped ino bandlimied noise.
More information10.7 Temperature-dependent Viscoelastic Materials
Secin.7.7 Temperaure-dependen Viscelasic Maerials Many maerials, fr example plymeric maerials, have a respnse which is srngly emperaure-dependen. Temperaure effecs can be incrpraed in he hery discussed
More informationEE456 Digital Communications
EE456 Digial Communicaions Professor Ha Nguyen Sepember 6 EE456 Digial Communicaions Inroducion o Basic Digial Passband Modulaion Baseband ransmission is conduced a low frequencies. Passband ransmission
More informationSolutions to the Exam Digital Communications I given on the 11th of June = 111 and g 2. c 2
Soluions o he Exam Digial Communicaions I given on he 11h of June 2007 Quesion 1 (14p) a) (2p) If X and Y are independen Gaussian variables, hen E [ XY ]=0 always. (Answer wih RUE or FALSE) ANSWER: False.
More informationAP Physics 1 MC Practice Kinematics 1D
AP Physics 1 MC Pracice Kinemaics 1D Quesins 1 3 relae w bjecs ha sar a x = 0 a = 0 and mve in ne dimensin independenly f ne anher. Graphs, f he velciy f each bjec versus ime are shwn belw Objec A Objec
More informationLecture 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 informationA First Course in Digital Communications
A Firs Course in Digial Communicaions Ha H. Nguyen and E. Shwedyk February 9 A Firs Course in Digial Communicaions /58 Block Diagram of Binary Communicaion Sysems m { b k } bk = s b = s k m ˆ { bˆ } k
More information5.1 Angles and Their Measure
5. Angles and Their Measure Secin 5. Nes Page This secin will cver hw angles are drawn and als arc lengh and rains. We will use (hea) represen an angle s measuremen. In he figure belw i describes hw yu
More informationEE3723 : Digital Communications
EE373 : Digial Communicaions Week 6-7: Deecion Error Probabiliy Signal Space Orhogonal Signal Space MAJU-Digial Comm.-Week-6-7 Deecion Mached filer reduces he received signal o a single variable zt, afer
More informationChapter 3: Signal Transmission and Filtering. A. Bruce Carlson Paul B. Crilly 2010 The McGraw-Hill Companies
Communicaion Sysems, 5e Chaper 3: Signal Transmission and Filering A. Bruce Carlson Paul B. Crilly 00 The McGraw-Hill Companies Chaper 3: Signal Transmission and Filering Response of LTI sysems Signal
More informationCHAPTER 7 CHRONOPOTENTIOMETRY. In this technique the current flowing in the cell is instantaneously stepped from
CHAPTE 7 CHONOPOTENTIOMETY In his echnique he curren flwing in he cell is insananeusly sepped frm zer sme finie value. The sluin is n sirred and a large ecess f suppring elecrlye is presen in he sluin;
More informationVisco-elastic Layers
Visc-elasic Layers Visc-elasic Sluins Sluins are bained by elasic viscelasic crrespndence principle by applying laplace ransfrm remve he ime variable Tw mehds f characerising viscelasic maerials: Mechanical
More informationBrace-Gatarek-Musiela model
Chaper 34 Brace-Gaarek-Musiela mdel 34. Review f HJM under risk-neural IP where f ( T Frward rae a ime fr brrwing a ime T df ( T ( T ( T d + ( T dw ( ( T The ineres rae is r( f (. The bnd prices saisfy
More informationSpectral Analysis. Joseph Fourier The two representations of a signal are connected via the Fourier transform. Z x(t)exp( j2πft)dt
Specral Analysis Asignalx may be represened as a funcion of ime as x() or as a funcion of frequency X(f). This is due o relaionships developed by a French mahemaician, physicis, and Egypologis, Joseph
More informationCHAPTER 2 Signals And Spectra
CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par
More informationUNIVERSITY OF CALIFORNIA College of Engineering Department of Electrical Engineering and Computer Sciences EECS 121 FINAL EXAM
Name: UNIVERSIY OF CALIFORNIA College of Engineering Deparmen of Elecrical Engineering and Compuer Sciences Professor David se EECS 121 FINAL EXAM 21 May 1997, 5:00-8:00 p.m. Please wrie answers on blank
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.265/15.070J Fall 2013 Lecture 15 10/30/2013. Ito integral for simple processes
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.65/15.7J Fall 13 Lecure 15 1/3/13 I inegral fr simple prcesses Cnen. 1. Simple prcesses. I ismery. Firs 3 seps in cnsrucing I inegral fr general prcesses 1 I inegral
More information( ) For more files visit
SETION A (75 marks). This quesin cnsiss f TWENTYFIVE subquesins (..5) f ONE mark each. Fr each f hese subquesins, fur pssible alernaives (A,B, and D) are given, u f which ONLY ONE is crrec. Indicae he
More informationUnit-I (Feedback amplifiers) Features of feedback amplifiers. Presentation by: S.Karthie, Lecturer/ECE SSN College of Engineering
Uni-I Feedback ampliiers Feaures eedback ampliiers Presenain by: S.Karhie, Lecurer/ECE SSN Cllege Engineering OBJECTIVES T make he sudens undersand he eec negaive eedback n he llwing ampliier characerisics:
More informationELEG 635 Digital Communication Theory. Lecture 9
ELEG 635 Digital Cmmunicatin Thery Lecture 9 10501 Agenda Optimal receiver fr PSK Effects f fading n BER perfrmance Tw ray mdel Pulse shaping Rectangle Raised csine Rt raised csine Receivers and pulse
More informationThe Buck Resonant Converter
EE646 Pwer Elecrnics Chaper 6 ecure Dr. Sam Abdel-Rahman The Buck Resnan Cnverer Replacg he swich by he resnan-ype swich, ba a quasi-resnan PWM buck cnverer can be shwn ha here are fur mdes f pera under
More informationImpact Switch Study Modeling & Implications
L-3 Fuzing & Ordnance Sysems Impac Swich Sudy Mdeling & Implicains Dr. Dave Frankman May 13, 010 NDIA 54 h Annual Fuze Cnference This presenain cnsiss f L-3 Crprain general capabiliies infrmain ha des
More informationADDITIONAL PROBLEMS (a) Find the Fourier transform of the half-cosine pulse shown in Fig. 2.40(a). Additional Problems 91
ddiional Problems 9 n inverse relaionship exiss beween he ime-domain and freuency-domain descripions of a signal. Whenever an operaion is performed on he waveform of a signal in he ime domain, a corresponding
More informationThe 37th International Physics Olympiad Singapore. Experimental Competition. Wednesday, 12 July, Sample Solution
The 37h Inernainal Physics Olypiad Singapre Experienal Cpeiin Wednesday, July, 006 Saple Sluin Par a A skech f he experienal seup (n required) Receiver Raing able Gnieer Fixed ar Bea splier Gnieer Mvable
More informationVehicle Arrival Models : Headway
Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where
More informationAnswers: ( HKMO Heat Events) Created by: Mr. Francis Hung Last updated: 21 September 2018
nswers: (009-0 HKMO Hea Evens) reaed by: Mr. Francis Hung Las updaed: Sepember 08 09-0 Individual 6 7 7 0 Spare 8 9 0 08 09-0 8 0 0.8 Spare Grup 6 0000 7 09 8 00 9 0 0 Individual Evens I In hw many pssible
More informationOutline Chapter 2: Signals and Systems
Ouline Chaper 2: Signals and Sysems Signals Basics abou Signal Descripion Fourier Transform Harmonic Decomposiion of Periodic Waveforms (Fourier Analysis) Definiion and Properies of Fourier Transform Imporan
More informationDr. Kasra Etemadi February 20, 2007
Dr. Kasra Eeadi February, 7 Seady-Sae Sinusidal Analysis Sinusidal Surces: Elecric pwer disribued fr residences and businesses Radi cunicain All signal f pracical ineres are cpsed f sinusidal cpnens Furier
More information( ) = 0.43 kj = 430 J. Solutions 9 1. Solutions to Miscellaneous Exercise 9 1. Let W = work done then 0.
Soluions 9 Soluions o Miscellaneous Exercise 9. Le W work done hen.9 W PdV Using Simpson's rule (9.) we have. W { 96 + [ 58 + 6 + 77 + 5 ] + [ + 99 + 6 ]+ }. kj. Using Simpson's rule (9.) again: W.5.6
More informationPRINCE SULTAN UNIVERSITY Department of Mathematical Sciences Final Examination Second Semester (072) STAT 271.
PRINCE SULTAN UNIVERSITY Deparmen f Mahemaical Sciences Final Examinain Secnd Semeser 007 008 (07) STAT 7 Suden Name Suden Number Secin Number Teacher Name Aendance Number Time allwed is ½ hurs. Wrie dwn
More informationA Bayesian Approach to Spectral Analysis
Chirped Signals A Bayesian Approach o Specral Analysis Chirped signals are oscillaing signals wih ime variable frequencies, usually wih a linear variaion of frequency wih ime. E.g. f() = A cos(ω + α 2
More informationChapter 3 Digital Transmission Fundamentals
Chapter 3 Digital Transmissin Fundamentals Errr Detectin and Crrectin CSE 3213, Winter 2010 Instructr: Frhar Frzan Mdul-2 Arithmetic Mdul 2 arithmetic is perfrmed digit y digit n inary numers. Each digit
More information6.003 Homework #13 Solutions
6.003 Homework #3 Soluions Problems. Transformaion Consider he following ransformaion from x() o y(): x() w () w () w 3 () + y() p() cos() where p() = δ( k). Deermine an expression for y() when x() = sin(/)/().
More informationMicrowave Engineering
Micrwave Engineering Cheng-Hsing Hsu Deparmen f Elecrical Engineering Nainal Unied Universiy Ouline. Transmissin ine Thery. Transmissin ines and Waveguides eneral Sluins fr TEM, TE, and TM waves ; Parallel
More informationRandom variables. A random variable X is a function that assigns a real number, X(ζ), to each outcome ζ in the sample space of a random experiment.
Random variables Some random eperimens may yield a sample space whose elemens evens are numbers, bu some do no or mahemaical purposes, i is desirable o have numbers associaed wih he oucomes A random variable
More informationOptimization of Four-Button BPM Configuration for Small-Gap Beam Chambers
Opimizain f Fur-Bun BPM Cnfigurain fr Small-Gap Beam Chamers S. H. Kim Advanced Phn Surce Argnne Nainal Larary 9700 Suh Cass Avenue Argnne, Illinis 60439 USA Asrac. The cnfigurain f fur-un eam psiin mnirs
More informationElements of Stochastic Processes Lecture II Hamid R. Rabiee
Sochasic Processes Elemens of Sochasic Processes Lecure II Hamid R. Rabiee Overview Reading Assignmen Chaper 9 of exbook Furher Resources MIT Open Course Ware S. Karlin and H. M. Taylor, A Firs Course
More informationDetecting nonlinear processes in experimental data: Applications in Psychology and Medicine
Deecing nonlinear processes in eperimenal daa: Applicaions in Psychology and Medicine Richard A. Heah Division of Psychology, Universiy of Sunderland, UK richard.heah@sunderland.ac.uk Menu For Today Time
More informationPhase and Frequency Modulation
Angle Modulaion Phase and Frequency Modulaion Consider a signal of he form x c = A c cos 2π f c + φ θ i ( ) where A c and f c are consans. The envelope is a consan so he message canno be in he envelope.
More information51. Elektrijada, Kopaonik
may 11. 51. Elekrijada Kpanik Tes in Physics 1. A mbile is frmed by suppring fur meal buerflies f equal mass m frm a sring f lengh L. The pins f suppr are evenly spaced a disance l apar as shwn in Figure
More informationNotes 04 largely plagiarized by %khc
Noes 04 largely plagiarized by %khc Convoluion Recap Some ricks: x() () =x() x() (, 0 )=x(, 0 ) R ț x() u() = x( )d x() () =ẋ() This hen ells us ha an inegraor has impulse response h() =u(), and ha a differeniaor
More informationImpacts of both Tx and Rx IQ Imbalances on OFDM Systems - Analytical Approach
mpacs of boh Tx and Rx Q mbalances on OFD Sysems - Analyical Approach Hassan Zareian, Vahid Tabaaba Vakili ran Universiy of Science and Technology UST, Tehran, ran Faculy of he slamic Republic of ran Broadcasing
More informationThe Potential Effectiveness of the Detection of Pulsed Signals in the Non-Uniform Sampling
The Poenial Effeciveness of he Deecion of Pulsed Signals in he Non-Uniform Sampling Arhur Smirnov, Sanislav Vorobiev and Ajih Abraham 3, 4 Deparmen of Compuer Science, Universiy of Illinois a Chicago,
More informationSOLUTIONS TO ECE 3084
SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no
More informationSMKA NAIM LILBANAT KOTA BHARU KELANTAN. SEKOLAH BERPRESTASI TINGGI. Kertas soalan ini mengandungi 7 halaman bercetak.
Name : Frm :. SMKA NAIM LILBANAT 55 KOTA BHARU KELANTAN. SEKOLAH BERPRESTASI TINGGI PEPERIKSAAN PERCUBAAN SPM / ADDITIONAL MATHEMATICS Keras ½ Jam ½ Jam Unuk Kegunaan Pemeriksa Arahan:. This quesin paper
More informationCharacteristics 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 informationThe Components of Vector B. The Components of Vector B. Vector Components. Component Method of Vector Addition. Vector Components
Upcming eens in PY05 Due ASAP: PY05 prees n WebCT. Submiing i ges yu pin ward yur 5-pin Lecure grade. Please ake i seriusly, bu wha cuns is wheher r n yu submi i, n wheher yu ge hings righ r wrng. Due
More informationDigital Band-pass Modulation PROF. MICHAEL TSAI 2011/11/10
Digital Band-pass Modulation PROF. MICHAEL TSAI 211/11/1 Band-pass Signal Representation a t g t General form: 2πf c t + φ t g t = a t cos 2πf c t + φ t Envelope Phase Envelope is always non-negative,
More informationPHY305F Electronics Laboratory I. Section 2. AC Circuit Basics: Passive and Linear Components and Circuits. Basic Concepts
PHY305F Elecrnics abrary I Secin ircui Basics: Passie and inear mpnens and ircuis Basic nceps lernaing curren () circui analysis deals wih (sinusidally) ime-arying curren and lage signals whse ime aerage
More informationAn Introduction to Wavelet Analysis. with Applications to Vegetation Monitoring
An Inrducin Wavele Analysis wih Applicains Vegeain Mniring Dn Percival Applied Physics Labrary, Universiy f Washingn Seale, Washingn, USA verheads fr alk available a hp://saff.washingn.edu/dbp/alks.hml
More informationSINUSOIDAL WAVEFORMS
SINUSOIDAL WAVEFORMS The sinusoidal waveform is he only waveform whose shape is no affeced by he response characerisics of R, L, and C elemens. Enzo Paerno CIRCUIT ELEMENTS R [ Ω ] Resisance: Ω: Ohms Georg
More informationPower of Random Processes 1/40
Power of Random Processes 40 Power of a Random Process Recall : For deerminisic signals insananeous power is For a random signal, is a random variable for each ime. hus here is no single # o associae wih
More informationNMR Spectroscopy: Principles and Applications. Nagarajan Murali 2D NMR Heteronuclear 2D Lecture 7
NMR pecroscop: Principles and Applicaions Nagarajan Murali D NMR Heeronuclear D Lecure 7 Heero Nuclear D-NMR Two dimensional NMR can be used o correlae NMR signals arising from differen nuclei such as
More informationAnswers to Exercises in Chapter 7 - Correlation Functions
M J Robers - //8 Answers o Exercises in Chaper 7 - Correlaion Funcions 7- (from Papoulis and Pillai) The random variable C is uniform in he inerval (,T ) Find R, ()= u( C), ()= C (Use R (, )= R,, < or
More informationMotion Along a Straight Line
PH 1-3A Fall 010 Min Alng a Sraigh Line Lecure Chaper (Halliday/Resnick/Walker, Fundamenals f Physics 8 h ediin) Min alng a sraigh line Sudies he min f bdies Deals wih frce as he cause f changes in min
More informationCommunication System Analysis
Communicaion Sysem Analysis Communicaion Sysems A naïve, absurd communicaion sysem 12/29/10 M. J. Robers - All Righs Reserved 2 Communicaion Sysems A beer communicaion sysem using elecromagneic waves o
More informationLecture #7. EECS490: Digital Image Processing. Image Processing Example Fuzzy logic. Fourier Transform. Basics Image processing examples
Lecure #7 Image Processing Example Fuzzy logic Basics Image processing examples Fourier Transorm Inner produc, basis uncions Fourier series Image Processing Example original image Laplacian o image (c)
More informationAnalytical Analysis of Lock-on Range of Infrared Heat Seeker Missile
Ausralian Jurnal f Basic and Applied Sciences, 3(4): 3703-3713, 2009 ISSN 1991-8178 Analyical Analysis f Lck-n Range f Infrared Hea Seeker Missile Mhammad Syuhaimi Ab-Rahman and Mazen R. Hassan Cmpuer
More informationd 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3
and d = c b - b c c d = c b - b c c This process is coninued unil he nh row has been compleed. The complee array of coefficiens is riangular. Noe ha in developing he array an enire row may be divided or
More informationULTRAFAST TIME DOMAIN OPTICS OF SINGLE-CYCLE LASER PULSE INTERACTION WITH MATERIALS
Universiy f Nebraska - Lincln DigialCmmns@Universiy f Nebraska - Lincln Theses, Disserains, and Suden Research frm Elecrical & Cmpuer Engineering Elecrical & Cmpuer Engineering, Deparmen f 1-010 ULTRAFAST
More informationPhysical Layer: Outline
18-: Intrductin t Telecmmunicatin Netwrks Lectures : Physical Layer Peter Steenkiste Spring 01 www.cs.cmu.edu/~prs/nets-ece Physical Layer: Outline Digital Representatin f Infrmatin Characterizatin f Cmmunicatin
More informationProblem Formulation in Communication Systems
Problem Formulaion in Communicaion Sysems Sooyong Choi School of Elecrical and Elecronic Engineering Yonsei Universiy Inroducion Problem formulaion in communicaion sysems Simple daa ransmission sysem :
More informationGAMS Handout 2. Utah State University. Ethan Yang
Uah ae Universiy DigialCmmns@UU All ECAIC Maerials ECAIC Repsiry 2017 GAM Handu 2 Ehan Yang yey217@lehigh.edu Fllw his and addiinal wrs a: hps://digialcmmns.usu.edu/ecsaic_all Par f he Civil Engineering
More informationPT380 MULTICHANNEL TIMER SPECIFICATIONS FEATURES PRODUCT CODE MODES OF OPERATION FUNCTIONS TERMINAL CONNECTION
PT380 MULTICHANNEL TIMER 96 X 96 Mulichannel: 8 channels Channel perain mde: Parallel r Sequenial Muli range: 99.99 sec 999.9 hr Mdes : N Delay / Inerval / Cyclic N firs / Cyclic FF firs Sar up delay &
More informationRAPIDLY ADAPTIVE CFAR DETECTION BY MERGING INDIVIDUAL DECISIONS FROM TWO-STAGE ADAPTIVE DETECTORS
RAPIDLY ADAPIVE CFAR DEECION BY MERGING INDIVIDUAL DECISIONS FROM WO-SAGE ADAPIVE DEECORS Analii A. Knnv, Sung-yun Chi and Jin-a Kim Research Cener, SX Engine Yngin-si, 694 Krea kaa@ieee.rg; dkrein@nesx.cm;
More informationEELE Lecture 3,4 EE445 - Outcomes. Physically Realizable Waveforms. EELE445 Montana State University. In this lecture you:
EELE445 Monana Sae Universiy Lecure 3,4 EE445 - Oucomes EELE445-4 Lecure 3,4 Poer, Energy, ime average operaor secion. In his lecure you: be able o use he ime average operaor [] for finie ime duraion signals
More informationModule 2 F c i k c s la l w a s o s f dif di fusi s o i n
Module Fick s laws of diffusion Fick s laws of diffusion and hin film soluion Adolf Fick (1855) proposed: d J α d d d J (mole/m s) flu (m /s) diffusion coefficien and (mole/m 3 ) concenraion of ions, aoms
More informationDriver Phase Correlated Fluctuations in the Rotation of a Strongly Driven Quantum Bit
[acceped fr PRA Rapid Cmm; quan-ph/] Driver Phase Crrelaed Flucuains in he Rain f a Srngly Driven Quanum Bi M.S. Shahriar,, P. Pradhan,, and J. Mrzinski Dep. f Elecrical and Cmpuer Engineering, Nrhwesern
More informationLesson 3.1 Recursive Sequences
Lesson 3.1 Recursive Sequences 1) 1. Evaluae he epression 2(3 for each value of. a. 9 b. 2 c. 1 d. 1 2. Consider he sequence of figures made from riangles. Figure 1 Figure 2 Figure 3 Figure a. Complee
More informationTutorial Sheet #2 discrete vs. continuous functions, periodicity, sampling
2.39 Tuorial Shee #2 discree vs. coninuous uncions, periodiciy, sampling We will encouner wo classes o signals in his class, coninuous-signals and discree-signals. The disinc mahemaical properies o each,
More information( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is
UNIT IMPULSE RESPONSE, UNIT STEP RESPONSE, STABILITY. Uni impulse funcion (Dirac dela funcion, dela funcion) rigorously defined is no sricly a funcion, bu disribuion (or measure), precise reamen requires
More informationEcological Archives E A1. Meghan A. Duffy, Spencer R. Hall, Carla E. Cáceres, and Anthony R. Ives.
Ecological Archives E9-95-A1 Meghan A. Duffy, pencer R. Hall, Carla E. Cáceres, and Anhony R. ves. 29. Rapid evoluion, seasonaliy, and he erminaion of parasie epidemics. Ecology 9:1441 1448. Appendix A.
More informationSensors, 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 informationLecture 4 ( ) Some points of vertical motion: Here we assumed t 0 =0 and the y axis to be vertical.
Sme pins f erical min: Here we assumed and he y axis be erical. ( ) y g g y y y y g dwnwards 9.8 m/s g Lecure 4 Accelerain The aerage accelerain is defined by he change f elciy wih ime: a ; In analgy,
More informationPhase Noise in CMOS Differential LC Oscillators
Phase Noise in CMOS Differenial LC Oscillaors Ali Hajimiri Thomas H. Lee Sanford Universiy, Sanford, CA 94305 Ouline Inroducion and Definiions Tank Volage Noise Sources Effec of Tail Curren Source Measuremen
More informationA First Course in Digital Communications
A First Course in Digital Communications Ha H. Nguyen and E. Shwedyk February 9 A First Course in Digital Communications 1/46 Introduction There are benefits to be gained when M-ary (M = 4 signaling methods
More informationNature Neuroscience: doi: /nn Supplementary Figure 1. Spike-count autocorrelations in time.
Supplemenary Figure 1 Spike-coun auocorrelaions in ime. Normalized auocorrelaion marices are shown for each area in a daase. The marix shows he mean correlaion of he spike coun in each ime bin wih he spike
More informationA complex discrete (or digital) signal x(n) is defined in a
Chaper Complex Signals A number of signal processing applicaions make use of complex signals. Some examples include he characerizaion of he Fourier ransform, blood velociy esimaions, and modulaion of signals
More informationRevelation of Soft-Switching Operation for Isolated DC to Single-phase AC Converter with Power Decoupling
Revelain f Sf-Swiching Operain fr Islaed DC Single-phase AC Cnverer wih wer Decupling Nagisa Takaka, Jun-ichi Ih Dep. f Elecrical Engineering Nagaka Universiy f Technlgy Nagaka, Niigaa, Japan nakaka@sn.nagakau.ac.jp,
More informationChapter One Fourier Series and Fourier Transform
Chaper One I. Fourier Series Represenaion of Periodic Signals -Trigonomeric Fourier Series: The rigonomeric Fourier series represenaion of a periodic signal x() x( + T0 ) wih fundamenal period T0 is given
More informationEE 301 Lab 2 Convolution
EE 301 Lab 2 Convoluion 1 Inroducion In his lab we will gain some more experience wih he convoluion inegral and creae a scrip ha shows he graphical mehod of convoluion. 2 Wha you will learn This lab will
More informationEELE Lecture 8 Example of Fourier Series for a Triangle from the Fourier Transform. Homework password is: 14445
EELE445-4 Lecure 8 Eample o Fourier Series or a riangle rom he Fourier ransorm Homework password is: 4445 3 4 EELE445-4 Lecure 8 LI Sysems and Filers 5 LI Sysem 6 3 Linear ime-invarian Sysem Deiniion o
More informationShandong Qingdao , China. Shandong Qingdao, , China
2016 Inernainal Cnference n Maerials, Manufacuring and Mechanical Engineering (MMME 2016) ISB: 978-1-60595-413-4 Min Cnrl Sysem f C Turre Punch Feeding Mechanism Based n Min Cnrl Card Ai-xia CAO 1, Pei-si
More information447. Assessment of damage risk function of structural components under vibrations
447. Assessmen f damage risk funcin f srucural cmnens under virains J. Dulevičius, A. Žiliukas Kaunas Universiy f Technlgy, Kesuci s. 27, LT-4432 Kaunas, Lihuania e-mail: jnas.dulevicius@ku.l, ananas.ziliukas@ku.l
More informationInstitute for Mathematical Methods in Economics. University of Technology Vienna. Singapore, May Manfred Deistler
MULTIVARIATE TIME SERIES ANALYSIS AND FORECASTING Manfred Deisler E O S Economerics and Sysems Theory Insiue for Mahemaical Mehods in Economics Universiy of Technology Vienna Singapore, May 2004 Inroducion
More informationPhysics for Scientists & Engineers 2
Direc Curren Physics for Scieniss & Engineers 2 Spring Semeser 2005 Lecure 16 This week we will sudy charges in moion Elecric charge moving from one region o anoher is called elecric curren Curren is all
More information6.003 Homework #9 Solutions
6.003 Homework #9 Soluions Problems. Fourier varieies a. Deermine he Fourier series coefficiens of he following signal, which is periodic in 0. x () 0 3 0 a 0 5 a k a k 0 πk j3 e 0 e j πk 0 jπk πk e 0
More informationHypothesis Tests for One Population Mean
Hypthesis Tests fr One Ppulatin Mean Chapter 9 Ala Abdelbaki Objective Objective: T estimate the value f ne ppulatin mean Inferential statistics using statistics in rder t estimate parameters We will be
More informationst semester. Kei Sakaguchi
0 s semeser MIMO Communicaion Sysems #5: MIMO Channel Capaciy Kei Sakaguchi ee ac May 7, 0 Schedule ( s half Dae Tex Conens # Apr. A-, B- Inroducion # Apr. 9 B-5, B-6 Fundamenals
More informationProductivity changes of units: A directional measure of cost Malmquist index
Available nline a hp://jnrm.srbiau.ac.ir Vl.1, N.2, Summer 2015 Jurnal f New Researches in Mahemaics Science and Research Branch (IAU Prduciviy changes f unis: A direcinal measure f cs Malmquis index G.
More informationTheory of! Partial Differential Equations!
hp://www.nd.edu/~gryggva/cfd-course/! Ouline! Theory o! Parial Dierenial Equaions! Gréar Tryggvason! Spring 011! Basic Properies o PDE!! Quasi-linear Firs Order Equaions! - Characerisics! - Linear and
More information2 int T. is the Fourier transform of f(t) which is the inverse Fourier transform of f. i t e
PHYS67 Class 3 ourier Transforms In he limi T, he ourier series becomes an inegral ( nt f in T ce f n f f e d, has been replaced by ) where i f e d is he ourier ransform of f() which is he inverse ourier
More informationProblem Set #1. i z. the complex propagation constant. For the characteristic impedance:
Problem Se # Problem : a) Using phasor noaion, calculae he volage and curren waves on a ransmission line by solving he wave equaion Assume ha R, L,, G are all non-zero and independen of frequency From
More informationLi An-Ping. Beijing , P.R.China
A NEW TYPE OF CIPHER: DICING_CSB Li An-Ping Beijing 100085, P.R.China apli0001@sina.com Absrac: In his paper, we will propose a new ype of cipher named DICING_CSB, which come from our previous a synchronous
More informationLecture 2: Optics / C2: Quantum Information and Laser Science
Lecure : Opics / C: Quanum Informaion and Laser Science Ocober 9, 8 1 Fourier analysis This branch of analysis is exremely useful in dealing wih linear sysems (e.g. Maxwell s equaions for he mos par),
More informationExample: Bipolar NRZ (non-return-to-zero) signaling
Baseand Data Transmission Data are sent without using a carrier signal Example: Bipolar NRZ (non-return-to-zero signaling is represented y is represented y T A -A T : it duration is represented y BT. Passand
More informationChapter 4 The Fourier Series and Fourier Transform
Represenaion of Signals in Terms of Frequency Componens Chaper 4 The Fourier Series and Fourier Transform Consider he CT signal defined by x () = Acos( ω + θ ), = The frequencies `presen in he signal are
More information