Tag: spectrum imaging
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Spectrum Imager 1.4
temDM Spectrum Imager is updated! Download the latest version at https://temdm.com/msa/ The recent development focused on 4D STEM treatment, namely on the pivot correction that improved a lot interpretability of PCA results. On top of that we have changed drastically the internal program structure, thus the package should be more stable. Some bugs are fixed.…
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Squeezing dimensions
I’ve always admired James Bond’s knack for wriggling out of impossible situations. I said to him: “It’s quite remarkable how smoothly you scale fences, leap from windows, and bulldoze through walls. I find myself wishing I could be a bit more like you…” James’ response, however, was less than encouraging. “You wish to experience claustrophobia?”…
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Accuracy of PCA
Once, I asked James Bond where his most difficult mission took place — was it in Turkey, Mexico, or Russia? “In Great Britain, when I was promoted to the central analytical office of MI-6,” he answered. “Were the headquarters suddenly attacked by an army of foreign spies?” “I would have wished for that. Instead, I…
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Spectrum Imager 1.2
temDM Spectrum Imager is updated! Download the latest version at http://temdm.com/msa The version 1.2 improves dramatically data visualization in the latent factor space. You can investigate closely the distribution of data with help of the 2D and 3D viewers. Data clustering is easy. On top of that, the pop-up help for all tool buttons and…
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ICA vs PCA
Once, I asked James Bond what was most important for a secret agent: shooting smartly or running quickly. “None of them,” answered Bond. “The most important thing is to be invisible. You should not be noticed by anybody who is searching for you.” “So, should you be dressed as a very average person?” “Not exactly,”…
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How much noise can we remove by PCA?
Y’all probably heard about Principal Component Analysis (PCA) and how it can be used to clean up noisy datasets. This can be done with our software, for instance. But have you ever wondered how it actually works? And more importantly, can it eliminate all the noise or just a fraction? Well, this post is here…