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Congratulations, you have reached the end of this introduction course to linear common filter.

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So let's recap everything that we've covered.

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So we have covered how to probabilistically express the uncertainty using probability distribution.

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So we've looked at using the Gaussian distribution to estimate the uncertainty inside the state and

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measurements.

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We have had a look how to convert differential equations into the states based representation for linear

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and nonlinear representations.

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We know how then to simulate these states based dynamic systems, whether they're linear or nonlinear.

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We've also looked at version of estimation called least squares estimation to solve static estimation

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problems.

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And we've also then extended that into the linear come and fill it up and looked at how to solve optimal

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estimation problems, which was the bulk of this course.

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We know how to drive the different system matrices for the common filter and we know how to do this

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in general so we can apply this to any filter, any problem that we want to apply to Linear Algebra

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two.

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We also know how to optimally tuned linear midfielder to get the best performance.

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And finally, we have covered how to implement the linear common filter in Python.

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But the equations are essentially same.

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So we can carry this over to any different programming languages or the math is exactly the same.

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All the concepts are exactly the same.

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So in conclusion, this should be everything you need to know to get you started with the linear algebra

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for sense of fusion and state estimation, you should be able to handle any problems or situation that

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arise using the fundamental knowledge in this course.

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We have also included the reference documents and cheat sheets, which are a handy reference for when

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you go through and implement your own computer or any problems you run into.

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So you are now definitely on your way to becoming a subject matter expert on all things common filtering.

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So in conclusion, I'd like to personally thank you for purchasing this course and taking the time to

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finish the course.

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I hope you enjoyed the course and it's been very useful for you.

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Please consider my other courses for any of your future learning adventures.