Imaging and nulling properties of sparse-aperture Fizeau interferometers Imaging and nulling properties of sparse-aperture Fizeau interferometers
|
|
- Bennett Eaton
- 5 years ago
- Views:
Transcription
1 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Fraçois Héault Istitut de Plaétologie et d Astrophysique de Greoble, Uiversité Joseph Fourier, CNRS, B.P. 53, Greoble Frace Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
2 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Geeral layout of a Fizeau iterferometer B P 1 P 2 (P) Telescope 1 F C Telescope 2 Relay optics 1 APS 1 APS 2 beam 1 B beam 2 Relay optics 2 Covergig optics Divergig optics Fold mirror Beamsplitter Acromatic Phase Shifter Combiig optics (P ) F Focal plae All telescopes assumed to be idetical All exit pupils optically cojugated with etrace pupils Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
3 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers V -sky agular coordiates Sky object u v U P 2 P 3 s Y Iput pupils defied by vectors P utput pupils defied by vectors P 1 N s B P 1 P 4 D Etrace pupil plae X D P 4 P 1 Y B Coordiates systems P 3 P 2 s s Exit pupil plae X F M Y M Detectio plae X Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
4 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Image of a sky object projected oto the sky Most geeral bject-image relatioship : I( s) = s T = 1 Ω ( s ) PSF ( s - s ) N a exp [ iφ ] exp[ ikξ( s, s) ] 2 dω with ξ ( s, s ) = s P s' P' / m PSF T (s) : PSF of a idividual collectig telescope, projected back oto the sky a : amplitude trasmissio factor of the th telescope ϕ : phase-shift alog the th iterferometer arm for cophasig or ullig purpose k = 2/λ : waveumber of moochromatic electro-magetic field m : optical compressio factor betwee telescopes ad their relay optics Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
5 First-order approximatio Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Golde rule of Fizeau iterferometers Necessary coditio : P = m P bject-image relatioship [ PSF ( s) F( s) ] ( ) I( s) = T s Ivariat PSF over the Field of view (FoV) Pupil I Pupil ut N = PSFT ( s) a exp = 1 F( s) [ ] [ ] 2 iφ exp i k sp Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
6 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Examples of applicatio Effect of pupil aberratios Deviatios from the golde rule : ohomothetic exit pupil combiers Simulatio of images i ullig mode Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
7 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Effect of pupil aberratios Develop all vectors at 2 d -order, e.g. : si u u ' x ' ( 1+ dz F' ) ' ' s = cos u si v v = y ( 1+ dz F' ) cos u cos v 1 u 2 v Isert ito the PD : ξ Use geeral bject-image relatio : No loger a covolutio operator! ' P ' ' ' ' ' (, s ) dz dz m + u x + v y ( u x + v y )( 1+ dz F' ) s I( s) = s 0 T = 1 Ω ( s ) PSF ( s - s ) N 0 dz a dz 2 2 ' 2 2 ( u + v ) 2 dz ( u + v ) 2m 0 exp 0 [ iφ ] exp[ ikξ( s, s) ] ' 2 dω m B B Flat wavefrot Flat wavefrot P 1 P 1 dz 1 dz 1 (P) Iput pupils dz 2 P 2 Collectig telescopes utput pupils (P ) dz 2 P 2 Multi-axial combier (exit pupil plae) F F Beam compressors X Focal plae Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
8 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Pupil aberratio: 2 telescopes Achievable FoV PSF at FoV cetre PSF at 0.3 arcsec PSF at 0.6 arcsec Aberrated pupil Case 2 Aberrated pupil Case 1 0 No pupil aberratio Ivariat PSF Curved friges, chagig PSF Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
9 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Pupil aberratio: 8 telescopes Achievable FoV PSF at FoV cetre PSF at 0.3 arcsec PSF at 0.6 arcsec Aberrated pupil Case 2 Aberrated pupil Case No pupil aberratio Ivariat PSF Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
10 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Differet combiig schemes From collectig telescopes From collectig telescopes B B APS 1 APS 2 beam 1 Axial combier F Frige tracker (P ) Focal plae beam 2 beams 1-4 beams 2-3 Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui B F (P ) Focal plae Crossedcubes uller
11 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Axially Combied Iterferometer (ACI) Telescope 1 Relay optics 1 P 1 beam 1 Axial beam combier F B Telescope 2 APS 1 APS 2 Frige tracker (P ) Focal plae beam 2 Ι( s) = P 2 Relay optics 2 PSF Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui T (P) ( s) * Co-axial combiatio by meas of a balaced set of beamsplitters Extiguishes all diffracted light origiatig from cetral star ly leaves plaet photos Specific bject-image relatioship N = 1 a exp [ iφ ] exp[ iksp ] 2 ( s)
12 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Crossed-cubes uller (CCN) See the Cheapest uller i the World : e talk o Thursday afteroo, 2 posters o Wedesday afteroo Cube 1 Cube 2 Y Focusig optics X " Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
13 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Pseudo-images of a compaio 20 m 10 mm Star Plaet Fake sky objects Telescope array Phase-shifts maps Star Plaet photos oly Plaet Axial combier Maximal desificatio Fizeau iterferometer Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
14 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Coclusio A simple Fourier optics formalism allows fast evaluatio of ullig Fizeau iterferometers performace Icludig PSF, achievable Field of view (FoV), ullig maps ad pseudo-images Whatever is the telescope umber N I presece of optical defects (pupil aberratios) Also applicable to o-fizeau iterferometers Simple formalism, o actual Fourier or Fresel trasforms required (gai i accuracy ad computig time) Simulatios show that that the most efficiet ullig schemes should use axial combiers or multi-axial combiers with maximal desificatio (e.g. Crossed-cubes uller) Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
15 Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Previous publicatios Fibered ullig telescope for extra-solar coroagraphy, ptics Letters vol. 34, 7, p (2009) Computig extictio maps of star ullig iterferometers, ptics Express vol. 16, (2008) Fie art of computig ullig iterferometer maps, Proceedigs of the SPIE 7013, 70131X (2008) Simple Fourier optics formalism for high agular resolutio systems ad ullig iterferometry, JSA A vol. 27, p (2010) PSF ad field of view characteristics of imagig ad ullig iterferometers, Proceedigs of the SPIE vol. 7734, (2010) Imagig power of multi-fibered ullig telescopes for extra-solar plaet characterizatio, Proceedigs of the SPIE vol. 8151, 81510A (2011) Cheapest uller i the world: crossed beamsplitter cubes, Proceedigs of the SPIE vol. 9146, this coferece Perhaps oe sythesis paper some day Coferece ptical ad Ifrared Iterferometry IV Motréal, 23 jui
PSF and Field of View characteristics of imaging and nulling interferometers
PSF ad FoV characteristics of imagig ad ullig iterferometers PSF ad Field of View characteristics of imagig ad ullig iterferometers Fraçois Héault UMR CNRS 6525 H. Fizeau UNS, CNRS, CA Aveue Nicolas Coperic
More informationImaging and nulling properties of sparse-aperture Fizeau interferometers
Imagig ad ullig properties of sparse-aperture Fizeau iterferometers Fraçois Héault Istitut de Plaétologie et d Astrophysique de Greoble Uiversité Joseph Fourier, Cetre Natioal de la Recherche Scietifique.P.
More informationPSF and field of view characteristics of imaging and nulling interferometers
PSF ad field of view characteristics of imagig ad ullig iterferometers Fraçois Héault UMR 6525 CRS H. Fizeau US, CA, Aveue icolas Coperic, 06130 Grasse Frace ASTRACT I this commuicatio are preseted some
More informationCheapest nuller in the World: Crossed beamsplitter cubes
Cheapest nuller in the World: François Hénault Institut de Planétologie et d Astrophysique de Grenoble, Université Joseph Fourier, CNRS, B.P. 53, 38041 Grenoble France Alain Spang Laboratoire Lagrange,
More informationSection 19. Dispersing Prisms
Sectio 9 Dispersig Prisms 9- Dispersig Prism 9- The et ray deviatio is the sum of the deviatios at the two surfaces. The ray deviatio as a fuctio of the iput agle : si si si cossi Prism Deviatio - Derivatio
More informationSection 19. Dispersing Prisms
19-1 Sectio 19 Dispersig Prisms Dispersig Prism 19-2 The et ray deviatio is the sum of the deviatios at the two surfaces. The ray deviatio as a fuctio of the iput agle : 1 2 2 si si si cossi Prism Deviatio
More informationFully achromatic nulling interferometer (FANI) for high SNR exoplanet characterization
Fully achromatic nulling interferometer (FANI) for high SNR exoplanet characterization François Hénault Institut de Planétologie et d Astrophysique de Grenoble Université Joseph Fourier Centre National
More informationAnalysis of azimuthal phase mask coronagraphs
Aalysis of azimuthal phase mask coroagraphs Fraçois Héault Istitut de Plaétologie et d Astrophysique de Greoble Uiversité Greoble-Alpes, Cetre Natioal de la Recherche Scietifique B.P. 53, 384 Greoble Frace
More informationComputing the output response of LTI Systems.
Computig the output respose of LTI Systems. By breaig or decomposig ad represetig the iput sigal to the LTI system ito terms of a liear combiatio of a set of basic sigals. Usig the superpositio property
More informationFizeau s Experiment with Moving Water. New Explanation. Gennady Sokolov, Vitali Sokolov
Fizeau s Experimet with Movig Water New Explaatio Geady Sokolov, itali Sokolov Email: sokolov@vitalipropertiescom The iterferece experimet with movig water carried out by Fizeau i 85 is oe of the mai cofirmatios
More informationADVANCED DIGITAL SIGNAL PROCESSING
ADVANCED DIGITAL SIGNAL PROCESSING PROF. S. C. CHAN (email : sccha@eee.hku.hk, Rm. CYC-702) DISCRETE-TIME SIGNALS AND SYSTEMS MULTI-DIMENSIONAL SIGNALS AND SYSTEMS RANDOM PROCESSES AND APPLICATIONS ADAPTIVE
More informationMulti-spectral piston sensor for co-phasing giant segmented mirrors and multi-aperture interferometric arrays
Multi-spectral pisto sesor for co-phasig giat segmeted mirrors Multi-spectral pisto sesor for co-phasig giat segmeted mirrors ad multi-aperture iterferometric arrays Fraçois Héault UMR 6525 CRS H. Fizeau
More informationOverview of Aberrations
Overview of Aberratios Les Desig OPTI 57 Aberratio From the Lati, aberrare, to wader from; Lati, ab, away, errare, to wader. Symmetry properties Overview of Aberratios (Departures from ideal behavior)
More informationThe Fizeau Experiment with Moving Water. Sokolov Gennadiy, Sokolov Vitali
The Fizeau Experimet with Movig Water. Sokolov Geadiy, Sokolov itali geadiy@vtmedicalstaffig.com I all papers o the Fizeau experimet with movig water, a aalysis cotais the statemet: "The beams travel relative
More informationRay Optics Theory and Mode Theory. Dr. Mohammad Faisal Dept. of EEE, BUET
Ray Optics Theory ad Mode Theory Dr. Mohammad Faisal Dept. of, BUT Optical Fiber WG For light to be trasmitted through fiber core, i.e., for total iteral reflectio i medium, > Ray Theory Trasmissio Ray
More informationProbability of error for LDPC OC with one co-channel Interferer over i.i.d Rayleigh Fading
IOSR Joural of Electroics ad Commuicatio Egieerig (IOSR-JECE) e-issn: 2278-2834,p- ISSN: 2278-8735.Volume 9, Issue 4, Ver. III (Jul - Aug. 24), PP 59-63 Probability of error for LDPC OC with oe co-chael
More informationFree Space Optical Wireless Communications under Turbulence Channel Effect
IOSR Joural of Electroics ad Commuicatio Egieerig (IOSR-JECE) e-issn: 78-834,p- ISSN: 78-8735.Volume 9, Issue 3, Ver. III (May - Ju. 014), PP 01-08 Free Space Optical Wireless Commuicatios uder Turbulece
More informationSignal Processing in Mechatronics. Lecture 3, Convolution, Fourier Series and Fourier Transform
Sigal Processig i Mechatroics Summer semester, 1 Lecture 3, Covolutio, Fourier Series ad Fourier rasform Dr. Zhu K.P. AIS, UM 1 1. Covolutio Covolutio Descriptio of LI Systems he mai premise is that the
More informationFall 2011, EE123 Digital Signal Processing
Lecture 5 Miki Lustig, UCB September 14, 211 Miki Lustig, UCB Motivatios for Discrete Fourier Trasform Sampled represetatio i time ad frequecy umerical Fourier aalysis requires a Fourier represetatio that
More informationOlli Simula T / Chapter 1 3. Olli Simula T / Chapter 1 5
Sigals ad Systems Sigals ad Systems Sigals are variables that carry iformatio Systemstake sigals as iputs ad produce sigals as outputs The course deals with the passage of sigals through systems T-6.4
More informationCork Institute of Technology Bachelor of Science (Honours) in Applied Physics and Instrumentation-Award - (NFQ Level 8)
ork Istitute of Techology Bachelor of Sciece (Hoours) i Applied Physics ad Istrumetatio-Award - (NFQ Level 8) Istructios Aswer Four questios, at least TWO questios from each Sectio. Use separate aswer
More informationSignal Processing. Lecture 02: Discrete Time Signals and Systems. Ahmet Taha Koru, Ph. D. Yildiz Technical University.
Sigal Processig Lecture 02: Discrete Time Sigals ad Systems Ahmet Taha Koru, Ph. D. Yildiz Techical Uiversity 2017-2018 Fall ATK (YTU) Sigal Processig 2017-2018 Fall 1 / 51 Discrete Time Sigals Discrete
More information2D DSP Basics: 2D Systems
- Digital Image Processig ad Compressio D DSP Basics: D Systems D Systems T[ ] y = T [ ] Liearity Additivity: If T y = T [ ] The + T y = y + y Homogeeity: If The T y = T [ ] a T y = ay = at [ ] Liearity
More informationWarped, Chirp Z-Transform: Radar Signal Processing
arped, Chirp Z-Trasform: Radar Sigal Processig by Garimella Ramamurthy Report o: IIIT/TR// Cetre for Commuicatios Iteratioal Istitute of Iformatio Techology Hyderabad - 5 3, IDIA Jauary ARPED, CHIRP Z
More information8. СОВЕТУВАЊЕ. Охрид, септември ANALYSIS OF NO LOAD APPARENT POWER AND FREQUENCY SPECTRUM OF MAGNETIZING CURRENT FOR DIFFERENT CORE TYPES
8. СОВЕТУВАЊЕ Охрид, 22 24 септември Leoardo Štrac Frajo Keleme Kočar Power Trasformers Ltd. ANALYSS OF NO LOAD APPARENT POWER AND FREQENCY SPECTRM OF MAGNETZNG CRRENT FOR DFFERENT CORE TYPES ABSTRACT
More informationMeasurement uncertainty of the sound absorption
Measuremet ucertaity of the soud absorptio coefficiet Aa Izewska Buildig Research Istitute, Filtrowa Str., 00-6 Warsaw, Polad a.izewska@itb.pl 6887 The stadard ISO/IEC 705:005 o the competece of testig
More informationSeidel sums and a p p l p icat a ion o s f or o r s imp m l p e e c as a es
Seidel sums ad applicatios for simple cases Aspheric surface Geerally : o spherical rotatioally symmetric surfaces but ca be off-axis coic sectios Greatly help to improve performace, ad reduce the umber
More informationTime-Domain Representations of LTI Systems
2.1 Itroductio Objectives: 1. Impulse resposes of LTI systems 2. Liear costat-coefficiets differetial or differece equatios of LTI systems 3. Bloc diagram represetatios of LTI systems 4. State-variable
More informationx[0] x[1] x[2] Figure 2.1 Graphical representation of a discrete-time signal.
x[ ] x[ ] x[] x[] x[] x[] 9 8 7 6 5 4 3 3 4 5 6 7 8 9 Figure. Graphical represetatio of a discrete-time sigal. From Discrete-Time Sigal Processig, e by Oppeheim, Schafer, ad Buck 999- Pretice Hall, Ic.
More informationSignal Processing in Mechatronics
Sigal Processig i Mechatroics Zhu K.P. AIS, UM. Lecture, Brief itroductio to Sigals ad Systems, Review of Liear Algebra ad Sigal Processig Related Mathematics . Brief Itroductio to Sigals What is sigal
More informationSession 5. (1) Principal component analysis and Karhunen-Loève transformation
200 Autum semester Patter Iformatio Processig Topic 2 Image compressio by orthogoal trasformatio Sessio 5 () Pricipal compoet aalysis ad Karhue-Loève trasformatio Topic 2 of this course explais the image
More informationHigh-Resolution Imagers
40 Telescopes and Imagers High-Resolution Imagers High-resolution imagers look at very small fields of view with diffraction-limited angular resolution. As the field is small, intrinsic aberrations are
More informationDiscrete-Time Systems, LTI Systems, and Discrete-Time Convolution
EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [
More informationLecture 3: Divide and Conquer: Fast Fourier Transform
Lecture 3: Divide ad Coquer: Fast Fourier Trasform Polyomial Operatios vs. Represetatios Divide ad Coquer Algorithm Collapsig Samples / Roots of Uity FFT, IFFT, ad Polyomial Multiplicatio Polyomial operatios
More informationSummary of formulas Summary of optical systems
Summar of formulas Summar of optical sstems Les Desig OPTI 57 Imagig: cetral projectio X' Y' Z' a X b Y c Z d axbyczd 0 0 0 0 a X b Y c Z d axbyczd 0 0 0 0 a X byczd axbyczd 3 3 3 3 0 0 0 0 Colliear trasformatio
More informationDiscrete Orthogonal Moment Features Using Chebyshev Polynomials
Discrete Orthogoal Momet Features Usig Chebyshev Polyomials R. Mukuda, 1 S.H.Og ad P.A. Lee 3 1 Faculty of Iformatio Sciece ad Techology, Multimedia Uiversity 75450 Malacca, Malaysia. Istitute of Mathematical
More informationProbability, Expectation Value and Uncertainty
Chapter 1 Probability, Expectatio Value ad Ucertaity We have see that the physically observable properties of a quatum system are represeted by Hermitea operators (also referred to as observables ) such
More informationJournal of Ramanujan Mathematical Society, Vol. 24, No. 2 (2009)
Joural of Ramaua Mathematical Society, Vol. 4, No. (009) 199-09. IWASAWA λ-invariants AND Γ-TRANSFORMS Aupam Saikia 1 ad Rupam Barma Abstract. I this paper we study a relatio betwee the λ-ivariats of a
More informationChapter 8. DFT : The Discrete Fourier Transform
Chapter 8 DFT : The Discrete Fourier Trasform Roots of Uity Defiitio: A th root of uity is a complex umber x such that x The th roots of uity are: ω, ω,, ω - where ω e π /. Proof: (ω ) (e π / ) (e π )
More informationRobustness of spatial-coherence multiplexing under receiver misalignment
Robustess of spatial-coherece multiplexig uder receiver misaligmet Lawrece J. Pelz ad Betty Lise Aderso It has bee show previously that the spatial coherece of a source ca be modulated ad demodulated;
More informationComa aberration. Lens Design OPTI 517. Prof. Jose Sasian
Coma aberratio Les Desig OPTI 517 Coma 0.5 wave 1.0 wave.0 waves 4.0 waves Spot diagram W W W... 040 0 H,, W 4 H W 131 W 00 311 H 3 H H cos W 3 W 00 W H cos W 400 111 H H cos cos 4 Coma though focus Cases
More informationThe z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j
The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.
More informationChapter 1. Complex Numbers. Dr. Pulak Sahoo
Chapter 1 Complex Numbers BY Dr. Pulak Sahoo Assistat Professor Departmet of Mathematics Uiversity Of Kalyai West Begal, Idia E-mail : sahoopulak1@gmail.com 1 Module-2: Stereographic Projectio 1 Euler
More informationSimilarity between quantum mechanics and thermodynamics: Entropy, temperature, and Carnot cycle
Similarity betwee quatum mechaics ad thermodyamics: Etropy, temperature, ad Carot cycle Sumiyoshi Abe 1,,3 ad Shiji Okuyama 1 1 Departmet of Physical Egieerig, Mie Uiversity, Mie 514-8507, Japa Istitut
More informationFormation of A Supergain Array and Its Application in Radar
Formatio of A Supergai Array ad ts Applicatio i Radar Tra Cao Quye, Do Trug Kie ad Bach Gia Duog. Research Ceter for Electroic ad Telecommuicatios, College of Techology (Coltech, Vietam atioal Uiversity,
More information: Transforms and Partial Differential Equations
Trasforms ad Partial Differetial Equatios 018 SUBJECT NAME : Trasforms ad Partial Differetial Equatios SUBJECT CODE : MA 6351 MATERIAL NAME : Part A questios REGULATION : R013 WEBSITE : wwwharigaeshcom
More informationTHE KALMAN FILTER RAUL ROJAS
THE KALMAN FILTER RAUL ROJAS Abstract. This paper provides a getle itroductio to the Kalma filter, a umerical method that ca be used for sesor fusio or for calculatio of trajectories. First, we cosider
More informationELEC1200: A System View of Communications: from Signals to Packets Lecture 3
ELEC2: A System View of Commuicatios: from Sigals to Packets Lecture 3 Commuicatio chaels Discrete time Chael Modelig the chael Liear Time Ivariat Systems Step Respose Respose to sigle bit Respose to geeral
More informationAnswers to test yourself questions
Aswers to test yourself questios Optio C C Itroductio to imagig a The focal poit of a covergig les is that poit o the pricipal axis where a ray parallel to the pricipal axis refracts through, after passage
More informationImage Segmentation on Spiral Architecture
Image Segmetatio o Spiral Architecture Qiag Wu, Xiagjia He ad Tom Hitz Departmet of Computer Systems Uiversity of Techology, Sydey PO Box 3, Broadway Street, Sydey 007, Australia {wuq,sea,hitz}@it.uts.edu.au
More informationREFLECTION AND REFRACTION
REFLECTION AND REFRACTION REFLECTION AND TRANSMISSION FOR NORMAL INCIDENCE ON A DIELECTRIC MEDIUM Assumptios: No-magetic media which meas that B H. No dampig, purely dielectric media. No free surface charges.
More informationModule 5 EMBEDDED WAVELET CODING. Version 2 ECE IIT, Kharagpur
Module 5 EMBEDDED WAVELET CODING Versio ECE IIT, Kharagpur Lesso 4 SPIHT algorithm Versio ECE IIT, Kharagpur Istructioal Objectives At the ed of this lesso, the studets should be able to:. State the limitatios
More informationBHW #13 1/ Cooper. ENGR 323 Probabilistic Analysis Beautiful Homework # 13
BHW # /5 ENGR Probabilistic Aalysis Beautiful Homework # Three differet roads feed ito a particular freeway etrace. Suppose that durig a fixed time period, the umber of cars comig from each road oto the
More informationLecture 7: Fourier Series and Complex Power Series
Math 1d Istructor: Padraic Bartlett Lecture 7: Fourier Series ad Complex Power Series Week 7 Caltech 013 1 Fourier Series 1.1 Defiitios ad Motivatio Defiitio 1.1. A Fourier series is a series of fuctios
More informationMechanics Physics 151
Mechaics Physics 151 Lecture 4 Cotiuous Systems ad Fields (Chapter 13) What We Did Last Time Built Lagragia formalism for cotiuous system Lagragia L = L dxdydz d L L Lagrage s equatio = dx η, η Derived
More informationLENS ANTENNAS. Oscar Quevedo-Teruel KTH Royal Institute of Technology
LENS ANTENNAS Oscar Quevedo-Teruel KTH Royal Istitute of Techology Outlie: Les ateas Part : Itroductio. Part : Homogeeous leses: Spherical. Part 3: Homogeeous leses: No-spherical. Part 4: Limitatios: Aberratios
More informationProbabilistic analyses in Phase 2 8.0
Probability desity Probabilistic aalyses i Phase 8.0 Beoît Valley & Damie Duff - CEMI - Ceter for Excellece i Miig Iovatio "Everythig must be made as simple as possible. But ot simpler." Albert Eistei
More informationOrthogonal transformations
Orthogoal trasformatios October 12, 2014 1 Defiig property The squared legth of a vector is give by takig the dot product of a vector with itself, v 2 v v g ij v i v j A orthogoal trasformatio is a liear
More informationDESCRIPTION OF THE SYSTEM
Sychroous-Serial Iterface for absolute Ecoders SSI 1060 BE 10 / 01 DESCRIPTION OF THE SYSTEM TWK-ELEKTRONIK GmbH D-001 Düsseldorf PB 1006 Heirichstr. Tel +9/11/6067 Fax +9/11/6770 e-mail: ifo@twk.de Page
More informationA PROCEDURE TO MODIFY THE FREQUENCY AND ENVELOPE CHARACTERISTICS OF EMPIRICAL GREEN'S FUNCTION. Lin LU 1 SUMMARY
A POCEDUE TO MODIFY THE FEQUENCY AND ENVELOPE CHAACTEISTICS OF EMPIICAL GEEN'S FUNCTION Li LU SUMMAY Semi-empirical method, which divides the fault plae of large earthquake ito mets ad uses small groud
More informationAccuracy of TEXTOR He-beam diagnostics
Accuracy of TEXTOR He-beam diagostics O. Schmitz, I.L.Beigma *, L.A. Vaishtei *, A. Pospieszczyk, B. Schweer, M. Krychoviak, U. Samm ad the TEXTOR team Forschugszetrum Jülich,, Jülich, Germay *Lebedev
More informationOptics. n n. sin. 1. law of rectilinear propagation 2. law of reflection = 3. law of refraction
Optics What is light? Visible electromagetic radiatio Geometrical optics (model) Light-ray: extremely thi parallel light beam Usig this model, the explaatio of several optical pheomea ca be give as the
More informationPHYS 450 Spring semester Lecture 06: Dispersion and the Prism Spectrometer. Ron Reifenberger Birck Nanotechnology Center Purdue University
/0/07 PHYS 450 Sprig semester 07 Lecture 06: Dispersio ad the Prism Spectrometer Ro Reifeberger Birck Naotechology Ceter Purdue Uiversity Lecture 06 Prisms Dispersio of Light As early as the 3th cetury,
More informationPHYS-3301 Lecture 9. CHAPTER 5 Wave Properties of Matter and Quantum Mechanics I. 5.3: Electron Scattering. Bohr s Quantization Condition
CHAPTER 5 Wave Properties of Matter ad Quatum Mecaics I PHYS-3301 Lecture 9 Sep. 5, 018 5.1 X-Ray Scatterig 5. De Broglie Waves 5.3 Electro Scatterig 5.4 Wave Motio 5.5 Waves or Particles? 5.6 Ucertaity
More informationPhase-shifting coronagraph
Phase-shifting coronagraph François Hénault, Alexis Carlotti, Christophe Vérinaud Institut de Planétologie et d Astrophysique de Grenoble Université Grenoble-Alpes Centre National de la Recherche Scientifique
More informationFinally, we show how to determine the moments of an impulse response based on the example of the dispersion model.
5.3 Determiatio of Momets Fially, we show how to determie the momets of a impulse respose based o the example of the dispersio model. For the dispersio model we have that E θ (θ ) curve is give by eq (4).
More informationIntroduction to Computational Molecular Biology. Gibbs Sampling
18.417 Itroductio to Computatioal Molecular Biology Lecture 19: November 16, 2004 Scribe: Tushara C. Karuarata Lecturer: Ross Lippert Editor: Tushara C. Karuarata Gibbs Samplig Itroductio Let s first recall
More informationDesign of multiplexed phase diffractive optical elements for focal depth extension
Desig of multiplexed phase diffractive optical elemets for focal depth extesio Hua Liu, Zhewu Lu,,* Qiag Su ad Hu Zhag,,2 Opto_electroics techology ceter, Chagchu Istitute of Optics ad Fie Mechaics ad
More informationOptimum LMSE Discrete Transform
Image Trasformatio Two-dimesioal image trasforms are extremely importat areas of study i image processig. The image output i the trasformed space may be aalyzed, iterpreted, ad further processed for implemetig
More informationMultiple Groenewold Products: from path integrals to semiclassical correlations
Multiple Groeewold Products: from path itegrals to semiclassical correlatios 1. Traslatio ad reflectio bases for operators Traslatio operators, correspod to classical traslatios, withi the classical phase
More informationFrequency Domain Filtering
Frequecy Domai Filterig Raga Rodrigo October 19, 2010 Outlie Cotets 1 Itroductio 1 2 Fourier Represetatio of Fiite-Duratio Sequeces: The Discrete Fourier Trasform 1 3 The 2-D Discrete Fourier Trasform
More informationShocks waves and discontinuities.
Shocks waes ad discotiuities Laurece Rezeau http://www.lpp.fr/?laurece-rezeau OUTLINE Obseratios of discotiuities Jump coditios at the boudary Differet kids of discotiuities What about the boudaries aroud
More informationDiscrete-Time Signals and Systems. Signals and Systems. Digital Signals. Discrete-Time Signals. Operations on Sequences: Basic Operations
-6.3 Digital Sigal Processig ad Filterig..8 Discrete-ime Sigals ad Systems ime-domai Represetatios of Discrete-ime Sigals ad Systems ime-domai represetatio of a discrete-time sigal as a sequece of umbers
More informationPart 1 - Basic Interferometers for Optical Testing
Part 1 - Basic Interferometers for Optical Testing Two Beam Interference Fizeau and Twyman-Green interferometers Basic techniques for testing flat and spherical surfaces Mach-Zehnder Zehnder,, Scatterplate
More informationINF-GEO Solutions, Geometrical Optics, Part 1
INF-GEO430 20 Solutios, Geometrical Optics, Part Reflectio by a symmetric triagular prism Let be the agle betwee the two faces of a symmetric triagular prism. Let the edge A where the two faces meet be
More informationMAXIMALLY FLAT FIR FILTERS
MAXIMALLY FLAT FIR FILTERS This sectio describes a family of maximally flat symmetric FIR filters first itroduced by Herrma [2]. The desig of these filters is particularly simple due to the availability
More informationNotes The Incremental Motion Model:
The Icremetal Motio Model: The Jacobia Matrix I the forward kiematics model, we saw that it was possible to relate joit agles θ, to the cofiguratio of the robot ed effector T I this sectio, we will see
More informationLast time: Moments of the Poisson distribution from its generating function. Example: Using telescope to measure intensity of an object
6.3 Stochastic Estimatio ad Cotrol, Fall 004 Lecture 7 Last time: Momets of the Poisso distributio from its geeratig fuctio. Gs () e dg µ e ds dg µ ( s) µ ( s) µ ( s) µ e ds dg X µ ds X s dg dg + ds ds
More informationDiversity Combining Techniques
Diversity Combiig Techiques Whe the required sigal is a combiatio of several waves (i.e, multipath), the total sigal amplitude may experiece deep fades (i.e, Rayleigh fadig), over time or space. The major
More informationHypertelescopes without delay lines.
Hypertelescopes without delay lines. V. Borkowski 1, O. Lardière 1, J. Dejonghe 1 and H. Le Coroller 2 1 LISE-Collège de France,Observatory of Haute Provence, France 2 Keck Observatory, Kamuela, Hawaii
More informationSupport vector machine revisited
6.867 Machie learig, lecture 8 (Jaakkola) 1 Lecture topics: Support vector machie ad kerels Kerel optimizatio, selectio Support vector machie revisited Our task here is to first tur the support vector
More information6.003 Homework #12 Solutions
6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F for
More informationFast Monte Carlo Method in Stochastic Modelling of Charged Particle Multiplication
Fast Mote Carlo Method i Stochastic Modellig of Charged Particle Multiplicatio Alla V. Shymaska *, Vitali A. Babakov School of Computer ad Mathematical Scieces, Aucklad Uiversity of Techology, Private
More informationLarge Deviations Performance Analysis for Biometrics Recognition
J.A. O Sulliva, 2002 Allerto Coferece Large Deviatios erformace Aalysis for Biometrics Recogitio Joseph A. O Sulliva ad Natalia Schmid Electroic Systems ad Sigals Research Laboratory Departmet of Electrical
More information2 1. The r.s., of size n2, from population 2 will be. 2 and 2. 2) The two populations are independent. This implies that all of the n1 n2
Chapter 8 Comparig Two Treatmets Iferece about Two Populatio Meas We wat to compare the meas of two populatios to see whether they differ. There are two situatios to cosider, as show i the followig examples:
More informationA novel laser guide star: Projected Pupil Plane Pattern
A novel laser guide star: Projected Pupil Plane Pattern Huizhe Yang a, Nazim Barmal a, Richard Myers a, David F. Buscher b, Aglae Kellerer c, Tim Morris a, and Alastair Basden a a Department of Physics,
More informationApply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.
Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α
More informationM2.The Z-Transform and its Properties
M2.The Z-Trasform ad its Properties Readig Material: Page 94-126 of chapter 3 3/22/2011 I. Discrete-Time Sigals ad Systems 1 What did we talk about i MM1? MM1 - Discrete-Time Sigal ad System 3/22/2011
More informationMCT242: Electronic Instrumentation Lecture 2: Instrumentation Definitions
Faculty of Egieerig MCT242: Electroic Istrumetatio Lecture 2: Istrumetatio Defiitios Overview Measuremet Error Accuracy Precisio ad Mea Resolutio Mea Variace ad Stadard deviatio Fiesse Sesitivity Rage
More information1 Duality revisited. AM 221: Advanced Optimization Spring 2016
AM 22: Advaced Optimizatio Sprig 206 Prof. Yaro Siger Sectio 7 Wedesday, Mar. 9th Duality revisited I this sectio, we will give a slightly differet perspective o duality. optimizatio program: f(x) x R
More information6.003 Homework #12 Solutions
6.003 Homework # Solutios Problems. Which are rue? For each of the D sigals x [] through x 4 [] (below), determie whether the coditios listed i the followig table are satisfied, ad aswer for true or F
More informationStructuring Element Representation of an Image and Its Applications
Iteratioal Joural of Cotrol Structurig Automatio Elemet ad Represetatio Systems vol. of a o. Image 4 pp. ad 50955 Its Applicatios December 004 509 Structurig Elemet Represetatio of a Image ad Its Applicatios
More informationQuantum Information & Quantum Computation
CS9A, Sprig 5: Quatum Iformatio & Quatum Computatio Wim va Dam Egieerig, Room 59 vadam@cs http://www.cs.ucsb.edu/~vadam/teachig/cs9/ Admiistrivia Do the exercises. Aswers will be posted at the ed of the
More informationBivariate Sample Statistics Geog 210C Introduction to Spatial Data Analysis. Chris Funk. Lecture 7
Bivariate Sample Statistics Geog 210C Itroductio to Spatial Data Aalysis Chris Fuk Lecture 7 Overview Real statistical applicatio: Remote moitorig of east Africa log rais Lead up to Lab 5-6 Review of bivariate/multivariate
More information1 Review of Probability & Statistics
1 Review of Probability & Statistics a. I a group of 000 people, it has bee reported that there are: 61 smokers 670 over 5 960 people who imbibe (drik alcohol) 86 smokers who imbibe 90 imbibers over 5
More informationSENSOR ARRAY ABLE TO DETECT AND RECOGNISE CHEMICAL WARFARE AGENTS
Abstract SENSOR ARRAY ABLE TO DETECT AND RECOGNISE CHEMICAL WARFARE AGENTS I. Bucur, S. Serba, A. Surpateau, N. Cupcea 1 C. Viespe, C. Grigoriu 2 C. Toader, N. Grigoriu 3 I this paper we studied a device
More informationPractical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement
Practical Spectral Aaysis (cotiue) (from Boaz Porat s book) Frequecy Measuremet Oe of the most importat applicatios of the DFT is the measuremet of frequecies of periodic sigals (eg., siusoidal sigals),
More informationMatsubara-Green s Functions
Matsubara-Gree s Fuctios Time Orderig : Cosider the followig operator If H = H the we ca trivially factorise this as, E(s = e s(h+ E(s = e sh e s I geeral this is ot true. However for practical applicatio
More informationComplex Algorithms for Lattice Adaptive IIR Notch Filter
4th Iteratioal Coferece o Sigal Processig Systems (ICSPS ) IPCSIT vol. 58 () () IACSIT Press, Sigapore DOI:.7763/IPCSIT..V58. Complex Algorithms for Lattice Adaptive IIR Notch Filter Hog Liag +, Nig Jia
More informationComplex Numbers. Brief Notes. z = a + bi
Defiitios Complex Numbers Brief Notes A complex umber z is a expressio of the form: z = a + bi where a ad b are real umbers ad i is thought of as 1. We call a the real part of z, writte Re(z), ad b the
More information