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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 200809 B. Smida (SEAS) ES250 Fall 200809 1 / 18 Course information Information theory overview S
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Course Information Fall 200809 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 6174967661 MaxwellDworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 200708 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) Discretetime 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 200809 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 6174967661 MaxwellDworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 200708 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 200809 B. Smida (SEAS) ES250 Fall 200809 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 flipflops. 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 200809 B. Smida (SEAS) ES250 Fall 200809 1 / 18 Course information Information theory overview S
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Course Information Fall 200809 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 6174967661 MaxwellDworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 200708 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) Discretetime 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 flipflops. 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 200809 Hours and location Lectures Problem sessions TTh 12:30pm, Cruft 319 TBA Teaching sta Instructor Besma Smida bsmida@seas.harvard.edu 6174967661 MaxwellDworkin 117 Oce Hours: Wed
School: Harvard
Course: Information Theory
Harvard SEAS ES250 Information Theory ES250 Project Description Fall 200708 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 200809 B. Smida (SEAS) ES250 Fall 200809 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 flipflops. Background: The exercises are divided into two main sections each with several parts. Section on