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School: Harvard
Course: Information Theory
Course information Information theory overview Some terms and concepts Entropy ES250 Information Theory Besma SMIDA Tuesday/Thursday 12:30pm, Cruft 319 Fall 2008-09 B. Smida (SEAS) ES250 Fall 2008-09 1 / 18 Course information Information theory overview S
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Course Information Fall 2008-09 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 617-496-7661 Maxwell-Dworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 2007-08 The goal of this project is for you to explore an area of contemporary information theory to complement materials in class. Since information theory is a relatively young and evo
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Gaussian Channel 1 Denitions Denition (Gaussian channel) Discrete-time channel with input Xi , noise Zi , and output Yi at time i. This is Yi = Xi + Zi , where the noise Zi is drawn i.i.d. from N (0, N ) and assumed t
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Channel Capacity 1 1.1 Preliminaries and Denitions Preliminaries and Examples Communication between A (the sender) and B (the receiver) is succesful when both A and B agree on the content of the message. A communicat
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Gambling and Data Compression 1 1.1 Gambling Horse Race Denition The wealth relative S (X ) = b(X )o(X ) is the factor by which the gamblers wealth grows if horse X wins the race, where b(X ) is the fraction of the ga
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Course Information Fall 2008-09 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 617-496-7661 Maxwell-Dworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 2007-08 The goal of this project is for you to explore an area of contemporary information theory to complement materials in class. Since information theory is a relatively young and evo
School: Harvard
Course: Information Theory
Course information Information theory overview Some terms and concepts Entropy ES250 Information Theory Besma SMIDA Tuesday/Thursday 12:30pm, Cruft 319 Fall 2008-09 B. Smida (SEAS) ES250 Fall 2008-09 1 / 18 Course information Information theory overview S
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Midterm Exam Solutions 1. (15 points) Let X be the waiting time for the rst heads to appear in successive ips of a fair coin. Thus, for example, Prcfw_X = 3 = ( 1 )3 . 2 (a) (5 points) Find H (X ). (b) (5 points) Find
School: Harvard
Engineering Sciences 50 Laboratory 3 Purpose: These exercises are meant to acquaint you with the characteristivs and typical applications of flip-flops. Background: The exercises are divided into two main sections each with several parts. Section on
School: Harvard
Course: Information Theory
Course information Information theory overview Some terms and concepts Entropy ES250 Information Theory Besma SMIDA Tuesday/Thursday 12:30pm, Cruft 319 Fall 2008-09 B. Smida (SEAS) ES250 Fall 2008-09 1 / 18 Course information Information theory overview S
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Course Information Fall 2008-09 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 617-496-7661 Maxwell-Dworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 2007-08 The goal of this project is for you to explore an area of contemporary information theory to complement materials in class. Since information theory is a relatively young and evo
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Gaussian Channel 1 Denitions Denition (Gaussian channel) Discrete-time channel with input Xi , noise Zi , and output Yi at time i. This is Yi = Xi + Zi , where the noise Zi is drawn i.i.d. from N (0, N ) and assumed t
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Channel Capacity 1 1.1 Preliminaries and Denitions Preliminaries and Examples Communication between A (the sender) and B (the receiver) is succesful when both A and B agree on the content of the message. A communicat
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Gambling and Data Compression 1 1.1 Gambling Horse Race Denition The wealth relative S (X ) = b(X )o(X ) is the factor by which the gamblers wealth grows if horse X wins the race, where b(X ) is the fraction of the ga
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Midterm Exam Solutions 1. (15 points) Let X be the waiting time for the rst heads to appear in successive ips of a fair coin. Thus, for example, Prcfw_X = 3 = ( 1 )3 . 2 (a) (5 points) Find H (X ). (b) (5 points) Find
School: Harvard
Engineering Sciences 50 Laboratory 3 Purpose: These exercises are meant to acquaint you with the characteristivs and typical applications of flip-flops. Background: The exercises are divided into two main sections each with several parts. Section on
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Course Information Fall 2008-09 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 617-496-7661 Maxwell-Dworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 2007-08 The goal of this project is for you to explore an area of contemporary information theory to complement materials in class. Since information theory is a relatively young and evo
School: Harvard
Course: Information Theory
Course information Information theory overview Some terms and concepts Entropy ES250 Information Theory Besma SMIDA Tuesday/Thursday 12:30pm, Cruft 319 Fall 2008-09 B. Smida (SEAS) ES250 Fall 2008-09 1 / 18 Course information Information theory overview S
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory Midterm Exam Solutions 1. (15 points) Let X be the waiting time for the rst heads to appear in successive ips of a fair coin. Thus, for example, Prcfw_X = 3 = ( 1 )3 . 2 (a) (5 points) Find H (X ). (b) (5 points) Find
School: Harvard
Engineering Sciences 50 Laboratory 3 Purpose: These exercises are meant to acquaint you with the characteristivs and typical applications of flip-flops. Background: The exercises are divided into two main sections each with several parts. Section on