Random Vector Functional Link Networks
In my last post I briefly mentioned Random Vector Functional Link networks and that this post would be about them, inspired by […]
Read moreCategory: Octave
Weight Agnostic Neural Net Training
I have recently come across the idea of weight agnostic neural net training and have implemented a crude version of this combined […]
Read moreIdeal Cyclic Tau Embedding as Times Series Features
Continuing on from my Ideal Tau for Time Series Embedding post, I have now written an Octave function based on these ideas […]
Read moreThe Ideal Tau for Time Series Embedding?
In my Preliminary Test Results of Time Series Embedding post I got a bit ahead of myself and mistakenly quoted the ideal […]
Read morePreliminary Test Results of Time Series Embedding
Following on from my post yesterday, this post presents some preliminary results from the test I was running while writing yesterday’s post. […]
Read moreTaken's Theorem and Time Series Embedding
I am now back from my summer break and am currently looking at using Taken’s theorem and am using an adapted version […]
Read moreProcess Noise Covariance Matrix Q for a Kalman Filter
Since my last post I have been working on the process noise covariance matrix Q, with a view to optimising both the […]
Read moreDetermining the Noise Covariance Matrix R for a Kalman Filter
An important part of getting a Kalman filter to work well is tuning the process noise covariance matrix Q and the measurement […]
Read moreTests of Constant and Variable Acceleration Model Kalman Filters
In my last post I said that this next post would report the results of tests on a Constant Acceleration model Kalman filter, and […]
Read moreTest of Constant Velocity Model Kalman Filter
Following on from my previous post, this post is a more detailed description of the testing methodology to test kinematic motion models […]
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