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This paper presents a trajectory generator, which generates a smooth robot trajectory in real-time.
Two observers are developed for specific growth rate estimation, one producing a discontinuous estimation which is used afterwards for substrate estimation, and the other one – based on high-gain observers – that generates a smooth estimation with first-order dynamics and finite-time bounded convergence error.
Using a smooth kernel such as a Gaussian generates a smooth signal.
By combining the three operators we obtain an interpolation operator, which generates a smooth function, interpolating the given boundary data.
GPLVM, in contrast, generates a smooth mapping from the latent space to the data space; this implies that two points which are distant in the data space will be distant in the latent space, too.
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The TPS formulation [ 17, 18] used in our method generates a smoothing interpolation function as follows: We begin by defining f to be a function that maps R to R for a given set of N points in R, ν = { ν i: i = 1, 2,..., N}.
It is also the most computationally expensive, as a large number of particles are generally required to generate a smooth concentration distribution.
The 7-phase jerk-limited look-ahead planning is employed to generate a smooth feedrate profile.
Then we use patch-based bidirectional motion estimation to generate a smooth Motion Vector Felid MVFF).
Titanium samples were activated by either oxygen plasma or acid etching to generate a smooth or nanorough surface, respectively.
Occam's approach is an algorithm for generating a smooth minimum norm model to an appropriate fit of the data.
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CEO of Professional Science Editing for Scientists @ prosciediting.com