Sentence examples for inverse learning from inspiring English sources

On this account, the inverse learning technique based on ESNs can be utilized to replace the dynamics-based inverse model.

Based on inverse learning and data fusion theory, two simple and intuitive integration schemes are proposed to integrate linguistic and numerical information with various forms, such as direct and indirect.

We can term it as understanding organic evolution of fish swimming (a biological hypothesis) through bio-inspired machines (designed on principles of mathematics and physics) [15],[16], in an inverse learning map.

However, the plant inverse error, e p, is nonzero and thus the plant inverse learns (and motor performance changes) even though there was no performance error.

Methods range from conventional neural networks, where some classical work had been performed early by the group of Schulten (Martinetz et al. 1990) and Torras [mainly in the domain of inverse kinematics learning, Ruis de Angulo and Torras (2005a); Ruis de Angulo and Torras (2005b ], to the now dominating methods of reinforcement learning (RL).

Gradient and pseudo-inverse learning methods are inapplicable because the functions in the proposed model are nonlinear and cannot be differentiated as a result of the feedback loop.

The plant inverse is learned by approximating the plant "forward model" from x′ c y′ c to x s, y s and then inverting the resulting 2×2 matrix.

In this paper, a solution based on hyper radial basis functions networks (HRBF) for learning inverse kinematics in redundant robots is presented.

Two models that stress learning inverse kinematics transformations for the hand are those of Molina-Vilaplana et al.

Most related grasping models focus on learning inverse kinematics for the hand, selecting contact points on the object's surface, and developing feedback-based control of the hand.

This inverse-power-law learning behaviour appears to be universal and is observed for many classifiers and types of datasets and it could be a possible way also in our proof-of-concept study to predict the performance of the classifier when trained with additional samples (will the accuracy of the SMO improve significantly? Is the effort to collect additional samples worthwhile?).