On the approximation of curves by line segments using dynamic programming
Communications of the ACM
Dynamic Programming
Least squares fitting of planes to surfaces using dynamic programming
Communications of the ACM
Relation-based aggregation: finding objects in large spatial datasets
Intelligent Data Analysis
Piecewise linear approximations of fewest line segments
AFIPS '72 (Spring) Proceedings of the May 16-18, 1972, spring joint computer conference
Waveform Segmentation Through Functional Approximation
IEEE Transactions on Computers
SIAM Journal on Scientific Computing
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In a recent paper, Bellman showed how dynamic programming could be used to determine the solution to a problem previously considered by Stone. The problem comprises the determination, given N, of the N points of subdivision of a given interval (&agr;, &bgr; and the corresponding line segments, that give the best least squares fit to a function g(x) in the interval. Bellman confined himself primarily to the analytical derivation, suggesting briefly, however, how the solution of the equation derived for each particular point of subdivision ui could be reduced to a discrete search. In this paper, the computational procedure is considered more fully, and the similarities to some of Stone's equations are indicated. It is further shown that an equation for u2 involving no minimization may be found. In addition, it is shown how Bellman's method may be applied to the curve-fitting problem when the additional constraints are added that the ends of the line segments must be on the curve.