๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Probability and Information Theory with Applications to Radar

โœ Scribed by P. M. Woodward, D. W. Fry and W. Higinbotham (Auth.)


Publisher
Elsevier Ltd, Pergamon Press
Year
1953
Tongue
English
Leaves
143
Edition
2Rev Ed
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Table of Contents


Content:
OTHER TITLES PUBLISHED IN THE SERIES, Page ii
Front Matter, Page iii
Copyright, Page iv
EDITOR'S PREFACE, Page ix
AUTHOR'S PREFACE, Pages ix-x
PREFACE TO SECOND EDITION, Page x
1 - AN INTRODUCTION TO PROBABILITY THEORY, Pages 1-25
2 - WAVEFORM ANALYSIS AND NOISE, Pages 26-42
3 - INFORMATION THEORY, Pages 43-61
4 - THE STATISTICAL PROBLEM OF RECEPTION, Pages 62-80
5 - SIMPLE THEORY OF RADAR RECEPTION, Pages 81-99
6 - THE MATHEMATICAL ANALYSIS OF RADAR INFORMATION, Pages 100-114
7 - THE TRANSMITTED RADAR SIGNAL, Pages 115-125
8 - DIRECT PROBABILITIES, Pages 126-133
REFERENCES, Page 133
INDEX, Pages 135-136


๐Ÿ“œ SIMILAR VOLUMES


Probability Theory with Applications
โœ Malempati M. Rao, Randall J. Swift ๐Ÿ“‚ Library ๐Ÿ“… 2006 ๐Ÿ› Springer ๐ŸŒ English

<P>This is a revised and expanded edition of a successful graduate and reference text. The book is designed for a standard graduate course on probability theory, including some important applications. The new edition offers a detailed treatment of the core area of probability, and both structural an

Probability Theory with Applications
โœ M. M. Rao, R. J. Swift (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2006 ๐Ÿ› Springer US ๐ŸŒ English

<p><P><STRONG>Probability Theory and Applications</STRONG> is a revised and expanded edition of a successful graduate and reference text. The material in the book is designed for a standard graduate course on probability theory, including some important applications. This new edition contains a deta

Probability Theory and Stochastic Proces
โœ Oliver Knill ๐Ÿ“‚ Library ๐Ÿ“… 2009 ๐Ÿ› Overseas Press ๐ŸŒ English

Chapter 1-2 of this text covers material of a basic probability course. Chapter 3 deals with discrete stochastic processes including Martingale theory. Chapter 4 covers continous time stochastic processes like Brownian motion and stochastic differential equations. The last chapter selected topics go