Particle Filters (and Navigation)
$49
ENROLL NOWCourse Overview
As the final course in the Applied Kalman Filtering specialization, you will learn how to develop the particle filter for solving strongly nonlinear state-estimation problems. You will learn about the Monte-Carlo integration and the importance density. You will see how to derive the sequential importance sampling method to estimate the posterior probability density function of a system’s state. You will encounter the degeneracy problem for this method and learn how to solve it via resampling. You will learn how to implement a robust particle-filter in Octave code and will apply it to an indoor-navigation problem.
Course FAQs
What are the prerequisites for 'Particle Filters (and Navigation)'?
Prerequisites for this continuing education class are set by University of Colorado System. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.
Will I receive a certificate for this CE class?
Yes, upon successful completion, University of Colorado System typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.
How long does this online course take to complete?
Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.
