Particle Filters (and Navigation)
$49
ENROLL NOWCourse Overview
What You'll Learn
- 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 encounter the degeneracy problem for this method and learn how to solve it via resampling.
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
Is this an accredited online course?
Accreditation for 'Particle Filters (and Navigation)' is determined by the provider, University of Colorado System. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
Can this course be used for continuing education credits?
Many of the courses listed on our platform are suitable for professional continuing education. However, acceptance for credit varies by state and licensing board. Please confirm with your board and {course.provider} that this specific course qualifies.
How do I enroll in this online school program?
To enroll, click the 'ENROLL NOW' button on this page. You will be taken to the official page for 'Particle Filters (and Navigation)' on the University of Colorado System online class platform, where you can complete your registration.
