A Piecewise Linear Fitting Technique for Multivalued Two-dimensional Paths
نویسندگان
چکیده
منابع مشابه
Piecewise Linear Two-Dimensional Warping
A new efficient dynamic programming (DP) algorithm for 2D elastic matching is proposed. The present DP algorithm requires by far less complexity than previous DPbased elastic matching algorithms. This complexity reduction results from piecewise linearization of a 2D-2D mapping which specifies an elastic matching between two given images. Since this linearization can be guided by a priori knowle...
متن کاملConvex piecewise-linear fitting
We consider the problem of fitting a convex piecewise-linear function, with some specified form, to given multi-dimensional data. Except for a few special cases, this problem is hard to solve exactly, so we focus on heuristic methods that find locally optimal fits. The method we describe, which is a variation on the K-means algorithm for clustering, seems to work well in practice, at least on d...
متن کاملFitting piecewise linear continuous functions
We consider the problem of fitting a continuous piecewise linear function to a finite set of data points, modeled as a mathematical program with convex objective. We review some fitting problems that can be modeled as convex programs, and then introduce mixed-binary generalizations that allow variability in the regions defining the best-fit function’s domain. We also study the additional constr...
متن کاملSmoothing of Piecewise Linear Paths
The pointwise traversal of a given path is a popular task in the area of robotics, e.g. in mobile, industrial or surgical robotics. The easiest method to describe paths is by a sequence of linear segments, and for many tasks the precision of a path approximated by linear segments is sufficient. The movements to be accomplished by a mobile robot or the robot’s end-effector are described by a seq...
متن کاملPiecewise Linear Regularized Solution Paths
We consider the generic regularized optimization problem β̂(λ) = arg minβ L(y,Xβ) + λJ (β). Efron, Hastie, Johnstone and Tibshirani [Ann. Statist. 32 (2004) 407–499] have shown that for the LASSO—that is, if L is squared error loss and J (β)= ‖β‖1 is the 1 norm of β—the optimal coefficient path is piecewise linear, that is, ∂β̂(λ)/∂λ is piecewise constant. We derive a general characterization of ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Research and Technology
سال: 2013
ISSN: 1665-6423
DOI: 10.1016/s1665-6423(13)71571-2