The Art of Randomness: Randomized Algorithms in the Real World

Cover Page
Title Page
Copyright Page
Dedication Page
About the Author
About the Technical Reviewer
BRIEF CONTENTS
CONTENTS IN DETAIL
FOREWORD
ACKNOWLEDGMENTS
INTRODUCTION
	Who Is This Book For?
	What Can You Expect to Learn?
	What I Expect You to Know
	How to Use This Book
1 THE NATURE OF RANDOMNESS
	Probability and Randomness
		Discrete Distributions
		Continuous Distributions
	Testing for Randomness
	Truly Random Processes
		Flipping Coins
		Rolling Dice
		Using Voltage
	Random Physical Processes
		Atmospheric Radio Frequency Noise
		Voyager Plasma and Charged Particle Data
		Radioactive Decay
	Deterministic Processes
		Pseudorandom Numbers
		Quasirandom Sequences
		Combining Deterministic and Truly Random Processes
	The Book’s Randomness Engine
		The RE Class
		RE Class Examples
	Summary
2 HIDING INFORMATION
	In Strings
		Fixed Offset
		Random Offset
	In Random Data
		How Much Can You Hide?
		The steg_random.py Code
	In an Audio File
		A Quiet Live Performance
		The steg_audio.py Code
	In an Image File
		Defining Image Formats
		Using NumPy and PIL
		Hiding Bits in Pixels
		Hiding One Image in Another
		The steg_image.py Code
	Exercises
	Summary
3 SIMULATE THE REAL WORLD
	Introduction to Models
	Estimate Pi
		Using a Dartboard
		Simulating Random Darts
		Understanding the RE Class Output
		Implementing the Darts Model
	Birthday Paradox
		Simulating 100,000 Parties
		Testing the Birthday Model
		Implementing the Birthday Model
	Simulating Evolution
		Natural Selection
		Static World
		Gradually Changing World
		Catastrophic World
		Genetic Drift
		Testing the Simulations
	Exercises
	Summary
4 OPTIMIZE THE WORLD
	Optimization with Randomness
	Fitting with Swarms
		Curves
		The curves.py Code
		The Optimization Algorithms
	Fitting Data
		Introducing Stacks and Postfix Notation
		Mapping Code to Points
		Creating gp.py
		Evolving Fit Functions
	Exercises
	Summary
5 SWARM OPTIMIZATION
	Packing Circles in a Square
		The Swarm Search
		The Code
	Placing Cell Towers
		The Swarm Search
		The Code
	Enhancing Images
		The Enhancement Function
		The Code
	Arranging a Grocery Store
		The Environment
		The Shoppers
		The Objective Function
		The Shopping Simulation
	Exercises
	Summary
6 MACHINE LEARNING
	Datasets
		Histology Slide Data
		Handwritten Digits
	Neural Networks
		Anatomy Analysis
		Randomness
		Initialization
	Extreme Learning Machines
		Implementation
		Testing
		Reckless Swarm Optimizations
	Random Forests
		Decision Trees
		Additional Randomness
		Models Combined with Voting
	Exercises
	Summary
7 ART
	Creating Random Art
		Moiré Patterns
		Random Walks
		A Grid
	Fun with Fractals
		The Chaos Game
		Iterated Function Systems
		Fractals Plotted with Points
		IFS Maps
	Exercises
	Summary
8 MUSIC
	Creating Random Sounds
		Sine Waves
		C Major Scale
	Generating Melodies
		Swarm Search
		The melody_maker.py code
		Implementation
	Exercises
	Summary
9 AUDIO SIGNALS
	Compressed Sensing
	Signal Generation
	Unraveled Images
	Compressed Sensing Applications
	Exercises
	Summary
10 EXPERIMENTAL DESIGN
	Randomization in Experiments
		Simple
		Block
		Stratified
	Defining the Simulation
	Implementing the Simulation
		Functions and Classes
		Schemes
	Exploring the Simulation
		Simple
		Block
		Stratified
	Exercises
	Summary
11 COMPUTER SCIENCE ALGORITHMS
	Las Vegas and Monte Carlo
		Permutation Sort
		Matrix Multiplication
	Counting Animals
	Testing Primality
		Modular Arithmetic
		The Miller-Rabin Test
		Non-witness Numbers
		Miller-Rabin Performance
	Working with Quicksort
		Running Quicksort in Python
		Experimenting with Quicksort
	Exercises
	Summary
12 SAMPLING
	Introduction to Sampling
		Terminology
		Bayesian Inference
	Discrete Distributions
		Sequential Search
		Fast-Loaded Dice Roller
		Runtime Performance
		Two Dimensions
		Images
	Continuous Distributions
		Inverse Transform
		Rejection
		Markov Chain Monte Carlo
	Exercises
	Summary
RESOURCES
	Random Processes
	Steganography
	Simulation and Modeling
	Metaheuristics: Swarm Intelligence and Evolutionary Algorithms
	Machine Learning
	Generative Art and Music
	Compressed Sensing
	Experimental Design
	Randomized Algorithms
	Sampling
	Videos
INDEX