Suppose that ƒ(x) = 2√x - 1. The formula in terms of x for each of the functions is: The graph was shifted to the right 1 unit, and stretched vertically by a factor of 2. Suppose we were given the ...

This repository houses a set of functions dedicated to the study of how well neural networks can learn a piecewise function dataset of varying complexity. You will find code dedicated to generating ...

Discover a groundbreaking method for optimizing nonlinear functions through piecewise linearization. Explore our paper for the best approximation techniques and real-world examples.

Many data are suitably modeled by functions consisting of straight-line segments. These functions may be called piecewise-linear. Smooth functions that are related to the hyperbola and that have ...

To represent this situation, the binary piecewise linear membership function is then employed. In order to solve the problem, we propose a new idea of how to formulate the binary piecewise linear ...

One of the most important properties of neural nets (NNs) for control purposes is the universal approximation property. Unfortunately,, this property is generally proven for continuous functions. In ...

For this aim, we try to obtain the best approximation of a nonlinear function as a piecewise linear function. Our method is based on an optimization problem. The optimal solution of this optimization ...