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This is about the "Sixth Sense" technology developed by an Indian

This is about the "Sixth Sense" technology developed by an I...by Andrea Maoro

4 Pages |7506 Views

This is about the "Sixth Sense" technology developed by an Indian studying at MIT. Extraordinary people visualize not what is possible or p...

Architecture, Ancient Rome.

Architecture, Ancient Rome.by Ricardo E. Valenzuela Ruiz

365 Views

This is a lecture about Ancient Roman Architecture released by MIT.

werden

werdenby Rose Killinger

1 Page |614 Views

Highspeed Cooking: Tomatensuppe mit Alf

Highspeed Cooking: Tomatensuppe mit Alfby Anne Hepe

478 Views

Alf kocht mit dem Eiweißshaker eine Tomatensuppe

MauveDB: Supporting Model-based User Views in Data

MauveDB: Supporting Model-based User Views in Databy Paull Shocker

29 Pages |1591 Views

MauveDB: Supporting Model-based User Views in Database Systems Amol Deshpande, University of Maryland Samuel Madden, MIT Motivation Unprecedented,...

Using Probabilistic Models for Data Management in

Using Probabilistic Models for Data Management inby Paull Shocker

32 Pages|1614 Views

Using Probabilistic Models for Data Management in Acquisitional Environments, Sam Madden MIT CSAIL, With Amol Deshpande (UMD), Carlos Guestrin (CMU),...

Rotational Motion Of Flywheels

Rotational Motion Of Flywheelsby LearnOnline Through OCW

485 Views

A car goes down the hill and loses a lot of gravitational p.e. Can this energy be stored as rotational k.e of a flywheel and used for taking the car u...

Classical Mechanics-Rotational Motion Of Flywheels

Classical Mechanics-Rotational Motion Of Flywheelsby LearnOnline Through OCW

707 Views

A car goes down the hill and loses a lot of gravitational p.e. Can this energy be stored as rotational k.e of a flywheel and used for taking the car u...

6.441-23 Channel side information, wide-band channels

6.441-23 Channel side information, wide-band channelsby LearnOnline Through OCW

13 Pages |247 Views

Lecture outline:Spreading over fading channels,Channel model,Upper bound to capacity and Interpretation.Since we have no sender channel side informati...

6.441-11 Strong coding theorem, types of errors

6.441-11 Strong coding theorem, types of errorsby LearnOnline Through OCW

15 Pages|260 Views

Lecture outline: Strong coding theorem,Revisiting channel and codes,Bound on probability of error,Error exponent.What we have done:
related the pr...

6.441-7 Shannon-Fano-Elias codes, Slepian-Wolf

6.441-7 Shannon-Fano-Elias codes, Slepian-Wolfby LearnOnline Through OCW

7 Pages |470 Views

Various topics discussed in this lecture notes are Elias codes ,Slepian-Wolf, Compression: pulling it together.Huffman codes Huffman codes are optima...

6.441-12 Strong coding theorem, error exponents

6.441-12 Strong coding theorem, error exponentsby LearnOnline Through OCW

15 Pages|168 Views

Lecture outline: Error exponent behavior 1.Expunging bad codewords,
2. Error exponent positivity and 3.Strong coding theorem.

Instructors...

6.441-13 Fano

6.441-13 Fano's inequality and the converse to the coding theoremby LearnOnline Through OCW

12 Pages |359 Views

Lecture outline:Fano’s Lemma revisited,Fano’s inequality for codewords,
Converse to the coding theorem and Consequences of the AEP: the typical se...

6.441-16 Differential entropy, maximizing entropy

6.441-16 Differential entropy, maximizing entropyby LearnOnline Through OCW

14 Pages|509 Views

This lecture explores ,Differential entropy,Entropy rate and Burg’s theorem
and AEP.Continuous random variables, Here we discussed about relation...

6.441-17 Additive Gaussian noise channel

6.441-17 Additive Gaussian noise channelby LearnOnline Through OCW

18 Pages |420 Views

The topics covered in this lecture notes are White Gaussian noise,Bandlimited WGN, Additive White Gaussian Noise (AWGN),channel
Capacity of AWGN ...

6.441-3 Different types of convergence, AEP  & typical set

6.441-3 Different types of convergence, AEP & typical setby LearnOnline Through OCW

17 Pages|291 Views

The topics covered in this lecture notes are 1.Types of convergence,2. Weak Law of Large Numbers 3. Strong Law of Large Numbers, 4. Asymptotic Equi...

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