Kalman Filter and Sensor Fusion.
In the Spring of 2012 and again in the Spring of 2019 I posted a series of posts about the Kalman Filter, which […]
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More Work on RVFL Networks
Back in November last year I posted about Random Vector Functional Link (RVFL) networks here and here. Since then, along with my […]
Read moreWeight 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 moreAnother Method of Creating Synthetic Data
Over the years I have posted about several different methodologies for creating synthetic data and I have recently come across yet another […]
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 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 moreHidden Markov Modelling of Synthetic Periodic Time Series Data
I am currently working on a method of predicting/projecting cyclic price action, based upon John Ehlers’ sinewave indicator code, and to test […]
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