𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Pseudo Random Signal Processing: Theory and Application

✍ Scribed by Hans-Jurgen Zepernick, Adolf Finger


Publisher
Wiley
Year
2005
Tongue
English
Leaves
438
Edition
1
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis


In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal’s pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users.

Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications, Pseudo Random Signal Processing: Theory and Application:

  • sets out the mathematical foundations needed to implement powerful pseudo random signal processing techniques;
  • presents information about binary and nonbinary pseudo random sequence generation and design objectives;
  • examines the creation of system architectures, including those with microprocessors, digital signal processors, memory circuits and software suits;
  • gives a detailed discussion of sophisticated applications such as spread spectrum communications, ranging and satellite navigation systems, scrambling, system verification, and sensor and optical fibre systems.

Pseudo Random Signal Processing: Theory and Applicationis an essential introduction to the subject for practising Electronics Engineers and researchers in the fields of mobile communications, satellite navigation, signal analysis, circuit testing, cryptology, watermarking, and measurement. It is also a useful reference for graduate students taking courses in Electronics, Communications and Computer Engineering

✦ Subjects


ΠŸΡ€ΠΈΠ±ΠΎΡ€ΠΎΡΡ‚Ρ€ΠΎΠ΅Π½ΠΈΠ΅;ΠžΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠ° сигналов;


πŸ“œ SIMILAR VOLUMES


Probability, Random Variables, and Rando
✍ John J. Shynk πŸ“‚ Library πŸ“… 2012 πŸ› Wiley-Interscience 🌐 English

<p><i>Probability, Random Variables, and Random Processes</i> is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some famil

Probability, random variables, and rando
✍ Shynk, John Joseph πŸ“‚ Library πŸ“… 2013 πŸ› Wiley-Interscience 🌐 English

<p><i>Probability, Random Variables, and Random Processes</i> is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some famil

Probability and Random Processes with Ap
✍ Henry Stark, John W. Woods πŸ“‚ Library πŸ“… 2001 πŸ› Prentice Hall 🌐 English

<P><B></B> Provides users with an accessible, yet mathematically solid, treatment of probability and random processes. Many computer examples integrated throughout, including random process examples in MATLAB. <B></B> Includes expanded discussions of fundamental principles, especially basic probabil

Probability, Random Processes, and Stati
✍ Hisashi Kobayashi, Brian L. Mark, William Turin πŸ“‚ Library πŸ“… 2012 πŸ› Cambridge University Press 🌐 English

Together with the fundamentals of probability, random processes, and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities,

Probability, Random Processes, and Stati
✍ Hisashi Kobayashi, Brian L. Mark, William Turin πŸ“‚ Library πŸ“… 2012 πŸ› CUP 🌐 English

Together with the fundamentals of probability, random processes, and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities,