Get Free Shipping on orders over $79
System Identification Using Regular and Quantized Observations : Applications of Large Deviations Principles - Qi He

System Identification Using Regular and Quantized Observations

Applications of Large Deviations Principles

By: Qi He, Le Yi Wang, George G. Yin

eText | 11 February 2013

At a Glance

eText


$84.99

or 4 interest-free payments of $21.25 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

This brief presents characterizations of identification errors under a probabilistic framework when output sensors are binary, quantized, or regular. By considering both space complexity in terms of signal quantization and time complexity with respect to data window sizes, this study provides a new perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, computational complexity in algorithms, sample sizes in statistical analysis and channel bandwidths in communications.

on
Desktop
Tablet
Mobile

More in Cybernetics & Systems Theory

The Science of Happy - King Poet

eBOOK

The Unity of Forces - manoranjan ghoshal

eBOOK

AI The Gift of a Lifetime - Loïc Molla

eBOOK

Life is a wave function - Abhay Kulkarni

eBOOK