We study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log ...
The present codes estimate the network statistics of the Hopf whole-brain model (Deco et al. 2017). This model corresponds to a network of nonlinear oscillators described by a normal form of a ...
We discuss structure-preserving model order reduction for port-Hamiltonian systems based on a nonlinear approximation ansatz which is linear with respect to a part of the state variables of the ...
We humans seem to be born with a number line in our head. But a May 30 study in Science suggests it may look less like an evenly segmented ruler and more like a logarithmic slide rule on which the ...
Abstract: In this article, the disjunctive and conjunctive lattice piecewise affine (PWA) approximations of explicit linear model predictive control (MPC) are proposed. Training data consisting of ...
ABSTRACT: Nonlinear approximation is widely used in signal processing. Real-life signals can be modeled as functions of bounded variation. Thus the variable knot of approximating function could be ...
We describe an algorithm, based on the simplex method of linear programming, for solving the discrete l 1 approximation problem with any type of linear constraints. The numerical results reported here ...
Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...
Abstract: Floating-point division involves the computation of the ratio (1 + Mx)/(1 + My), where Mx and My represents the mantissas of the input values. In this paper, we propose a new method for ...
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