'Source coding' diaporamas de présentation

Rate-distortion Theory for Secrecy Systems

Rate-distortion Theory for Secrecy Systems. Paul Cuff Electrical Engineering Princeton University. Information Theory. Channel Coding. Source Coding. Secrecy. Secrecy. Channel. Source. Source Coding. Describe an information signal ( source ) with a message. Information.

818 views • 66 slides

Distributed network signal processing

Distributed network signal processing. Sensorwebs group. http://basics.eecs.berkeley.edu/sensorwebs. Kannan Ramchandran ( Pister, Sastry,Anantharam,Jordan,Malik) Electrical Engineering and Computer Science University of California at Berkeley. kannanr@eecs.berkeley.edu

466 views • 39 slides

Paper Presentation Channel Coding and Transmission Aspects for Wireless Multimedia

Paper Presentation Channel Coding and Transmission Aspects for Wireless Multimedia. Authors: Joachim Hagenauer, Thomas Stochhammer Source: Proceedings of the IEEE , Volume: 87 Issue: 10 , Oct 1999, pp. 1764 -1777 Originally Presented by Hong Hong Chang, Feb 17, 2003. Overview. Introduction

562 views • 36 slides

Kommunikatsiooniteenuste arendus IRT0080

430 views • 30 slides

Digital Communications

Source Encode r. Channel Encoder. Digital Modulator. Source. Channel. Digital Demodulator. Sink. Source Decoder. Channel Decoder. Digital Communications. Digital Comm Functional Blocks. Source coding converts message to bits; compression Remove redundancy from data source

449 views • 24 slides

Source Coding

Source Coding. Source Coding. The purpose of source coding is to reduce the number of bits required to convey the information provided by the information source. For the file of the source data this means compression For the transmission, this is a bit rate reduction. Classification.

2.38k views • 22 slides

ETSI STF386 on Cognitive PMSE Chairmen: Wolfgang Bilz & Prof. Georg Fischer

GSC16-GRSC9-09a2. ETSI STF386 on Cognitive PMSE Chairmen: Wolfgang Bilz & Prof. Georg Fischer. Status and Next Steps Input to Global Standards Collaboration (GSC). Agenda. STF386 Status Alignment with German C-PMSE Project Next Steps. STF386 Status. 1. STF386 Status Team.

303 views • 21 slides

Information theory

Information theory. Multi-user information theory Part 3: Slepian Wolf Source Coding A.J. Han Vinck Essen, 2002. content. Source coding for dependent sources that are separated. Goal of the lecture:. Explain the idea of independent source coding for dependent source.

344 views • 21 slides

The NEWCOM Network of Excellence

329 views • 20 slides

Xin Li LDCSEE, WVU Email: xin.li@ieee

361 views • 19 slides

Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding

Energy Efficient Wireless Sensor Networks using Asymmetric Distributed Source Coding. O BJECTIVE. Model WSN Use Distributed Source Coding - Remove spatial redundancy Reduce bandwidth, energy consumption. M OTIVATION. The MIT Technology Review - number one emerging technology

350 views • 18 slides

Source Coding Procedure:

273 views • 15 slides

Recursively Indexed Quantization of Memoryless Sources

Recursively Indexed Quantization of Memoryless Sources. Author: Khalid Sayood, member IEEE Sangsin Na, member IEEE IEEE Transactions of Information theory Vol. 38, No. 5, Sep. 92 Reporter: ChiaHsing Lee, 8817586 NCTU CSIE. Outline. Source coding scheme Recursive indexing scheme

617 views • 14 slides

Outline

Outline. Transmitters (Chapters 3 and 4, Source Coding and Modulation) (week 1 and 2) Receivers (Chapter 5) (week 3 and 4) Received Signal Synchronization (Chapter 6) (week 5) Channel Capacity (Chapter 7) (week 6) Error Correction Codes (Chapter 8) (week 7 and 8)

276 views • 13 slides

Information theory

Information theory. Multi-user information theory Part 3: Slepian Wolf Source Coding A.J. Han Vinck Essen, 2002. content. Source coding for dependent sources that are separated. Goal of the lecture:. Explain the idea of independent source coding for dependent source.

307 views • 13 slides

Joint Data Hiding & Source Coding with Partially Available Side Information

226 views • 13 slides

Digital Transmission Lecture o4 Advanced Computer Networks (ACN) 545

Mr. Thilak de Silva. BSc. Eng., MSc, CEng, FIE(SL), FIET(UK), CITP(UK), MBCS(UK), MIEEE (USA). Digital Transmission Lecture o4 Advanced Computer Networks (ACN) 545. Today's Agenda. Source coding methods Channel coding methods Data Compression Data Encryption Channelization Protocols

220 views • 12 slides

Outline

Outline. Transmitters (Chapters 3 and 4, Source Coding and Modulation) (week 1 and 2) Receivers (Chapter 5) (week 3 and 4) Received Signal Synchronization (Chapter 6) (week 5) Channel Capacity (Chapter 7) (week 6) Error Correction Codes (Chapter 8) (week 7 and 8)

191 views • 9 slides

Coding Theory, Compression, and Cryptography

Coding Theory, Compression, and Cryptography. Trevor Olson. Coding Theory. Approach to various science disciplines Information Theory, Electrical Engineering, Data Transmission, Math, Computer Science Create efficient and reliable transmission methods Remove Redundancy, Correct Errors

279 views • 9 slides

Mesh Capacity WG

Mesh Capacity WG. Outline. Technologies What band(s) should we use? What antennas should we use? What architecture should we use? Closed platforms are a pressing problem Goals: What do we need? Evaluation Repeatability is a major concern What should we be repeating?. Frequency choice.

163 views • 8 slides