We can't find the internet
Attempting to reconnect
Something went wrong
Hang in there while we get back on track
£39.77
Springer Kalman Filtering: with Real-Time Applications Book
Price data last checked 53 day(s) ago - refreshing...
We'll watch every seller, every day. One email when your price arrives.
This is the most expensive it has ever been. Walk away.
£40 today · previous high £40 · all-time low £40
NEW HERE?
Amazon shows you one price. We show you all of them.
Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.
WHAT'S ON THIS PAGE
when this has been cheap or pricey
where the price is heading next
all-time high & low, recent range
name your number, we'll email you
Price History & Forecast
Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.
Last 38 days · 38 data points (no recent data)
Price Distribution
Price distribution over 38 days • 1 price levels
Price Analysis
Most common price: £40 (38 days, 100.0%)
Price range: £40 - £40
Price levels: 1 different prices over 38 days
Description
Key Features
This Springer publication offers a thorough discussion of mathematical theory and computational schemes for Kalman filtering.
The text explains algorithm derivation using direct methods consisting of elementary steps and indirect methods via innovation projection.
Learn to apply Kalman filtering to systems characterized by correlated noise or colored noise.
Study extended Kalman filtering techniques specifically designed for nonlinear systems.
The book covers interval Kalman filtering for uncertain systems and wavelet Kalman filtering for multiresolution analysis.
Gain insights into limiting Kalman filtering specifically for time-invariant systems.
Product Specifications
- Brand
- Springer
- Format
- paperback
- ASIN
- 331983780X
- Domain
- Amazon UK
- Release Date
- 20 July 2018
- Listed Since
- 20 July 2018
Barcode
No barcode data available
Similar Products You Might Like
Kalman Filter for Beginners: with MATLAB Examples
CREATESPACE
Primer to Kalman Filtering: A Physicist Perspective (Engineering Tools, Techniques and Tables)
Kalman Filtering: Theory and Practice with MATLAB (IEEE Press)
Wiley
Kalman Filter Made Easy - Beginner's Guide with Python
Price unavailable
Unscented Kalman Filter Made Easy: A Beginners Guide to Nonlinear Filtering with the Unscented Kalman Filter and MATLAB
Price unavailable
Kalman Filtering (Mathematics Research Developments: Engineering Tools, Techniques and Tables)
Wiley Kalman Filtering and Neural Networks Textbook
Wiley
Estimation, Control, and the Discrete Kalman Filter: 71 (Applied Mathematical Sciences, 71)
Springer
Intuitive Understanding of Kalman Filtering with MATLAB®
CRC Press
Intuitive Understanding of Kalman Filtering with MATLAB®
CRC Press
Fundamentals of Kalman Filtering: a Practical Approach (Progress in Astronautics & Aeronautics)
AIAA (American Institute of Aeronautics & Astronautics)
Introduction to Random Signals and Applied Kalman Filtering: With MATLAB Exercises
Wiley
The Kalman Filter in Finance: 32 (Advanced Studies in Theoretical and Applied Econometrics, 32)
Springer
Adaptive Filtering: Algorithms and Practical Implementation
Springer
Adaptive Filtering: Algorithms and Practical Implementation
Springer
Measurement Data Modeling and Parameter Estimation (Systems Evaluation, Prediction, and Decision-Making)
CRC Press
Measurement Data Modeling and Parameter Estimation - CRC Press
CRC Press
Filtering and System Identification: A Least Squares Approach
Cambridge University Press
Tracking and Kalman Filtering Made Easy
Wiley
The Kalman Filter in Finance: 32 (Advanced Studies in Theoretical and Applied Econometrics, 32)
Springer
Kalman Filtering: Theory and Practice (Prentice-Hall Information and System Sciences)
PEARSON EDUCATION
Price unavailable
Introduction to Optimal Estimation (Advanced Textbooks in Control and Signal Processing)
Springer
Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks, Series Number 3)
Cambridge University Press
