Tag Archives: matrices

Robot Committing Suicide

I move my arm. [holonomy] I move my arm, hand and shoulder. [holonomy] I move my arm, hand, shoulders, but my fingers are still. I move my arm. [lie group] I move my arm across the table. [embedded in a … Continue reading

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How do I Create the Identity Matrix in R? Also a bit of group theory.

I googled for this once upon a time and nothing came up. Hopefully this saves someone ten minutes of digging about in the documentation. You make identity matrices with the keyword diag, and the number of dimensions in parentheses. > … Continue reading

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multiplicitiesoffreedom: Gotcha.

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@IgorCarron blogs recent applications of compressive sensing and matrix factorisation every week. (Compressive sensing solves underdetermined systems of equations, for example trying to fill in missing data, by L₁-norm minimisation.) This week: reverse-engineering biochemical pathways and complex systems analysis. (Source: … Continue reading

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Once you’re comfortable with 2-arrays and 2-matrices, you can move up a dimension or two, to 4-arrays or 4-tensors. You can move up to a 3-array / 3-tensor just by imagining a matrix which “extends back into the blackboard”. Like … Continue reading

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Linear Transformations will take you on a Trip Comparable to that of Magical Mushroom Sauce, And Perhaps cause More Lasting Damage Long after I was supposed to “get it”, I finally came to understand matrices by looking at the above … Continue reading

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Positive Semi-Definite

Mathematical matrices are blocks of numbers. So they don’t necessarily have definite characteristics the way plain vanilla, singleton numbers do. They’re freer. For example 131 ∈ positive and −9 ∈ negative. But is positive, negative, or zero? Well, it has … Continue reading

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How to multiply matrices

This is for my homies in math class. Mathematical matrices are blocks of numbers, arrayed in 2-D. (Higher-dimensional arrays are called tensors.) Left “times” right equals target. Each entry in the target is the result of a series of +’s … Continue reading

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Determinant

A matrix ℳ represents a sequence of + and × operations. At the end you’ve linearly transformed a space (sheared it, expanded it, rotated it — but kept the origin where it is.) Did the amount of stuff in the picture change when you … Continue reading

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What is an eigenvector?

The eigenvectors of a matrix summarise what it does. Think about a large, not-sparse matrix. A lot of computations are implied in that block of numbers. Some of those computations might overlap each other—2 steps forward, 1 step back, 3 steps … Continue reading

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