We consider a recent method for generating an input signal with a desired auto correlation while satisfying both input and output constraints for the system it is to be applied to. This is an important problem in system identification, since the properties of the identified model depend on the used excitation signal while on real processes, due to actuator saturation and safety considerations, ...

This paper presents an approach for designing multi-input shapers using an s-plane pole placement technique. Slightly more information about the system model is taken into account than has been traditionally done with input shaping designs. The input shaping sequences for all system inputs are solved for simultaneously , and the resulting designs lead to shorter impulse sequences than solving f...

Weighted games for several levels of approval in input and output were introduced in [9]. An extension of the desirability relation for simple games, called the influence relation, was introduced for games with several levels of approval in input in [24] (see also [18]). However, there are weighted games not being complete for the influence relation, something different to what occurs for simpl...

BULLSEYE is a flexible, computer input device that operates by generating and analyzing the image of known ‘‘props’’ at 60 Hz to determine position, orientation, and usercontrolled internal state variables. The compact device, containing both the camera and processing engine, has been built and fielded. This paper provides an overview of the concept and hardware, then examines the problems and ...

A polymorphic analysis is an analysis whose input and output contain parameters which serve as placeholders for information that is unknown before analysis but provided after analysis. In this paper, we present a polymorphic groundness analysis that infers parameterised groundness descriptions of the variables of interest at a program point. The polymorphic groundness analysis is designed by re...

The method of input shaping has been shown to yield good performance in the control of exible structures while being insensitive to modeling errors. However, previous studies do not take into account the distributions of the parameter variations. We develop a new input shaping method that allows the ranges of system parameter values to be weighted according to the expected modeling errors. Comp...

In this paper, a model of analogy-based learning is presented, whose main novelty is the crucial ability to produce analogies in multi-dimensional input and output spaces. Evaluations are performed on various word pronunciation tasks, revealing the effectiveness of such joint learning strategies.

In a range of contexts, one comes across processes resembling inference, but where input propositions are not in general included among outputs, and the operation is not in any way reversible. Examples arise in contexts of conditional obligations, goals, ideals, preferences, actions, and beliefs. Our purpose is to develop a general theory of propositional input/output operations. Particular att...