Neural network black-box modeling is usually performed using nonlinear input-output models. The goal of this paper is to show that there are advantages in using nonlinear state-space models, which constitute a larger class of nonlinear dynamical models, and their corresponding state-space neural predictors. We recall the fundamentals of both input-output and state-space black-box modeling, and ...

MODELING OF SIGNAL BEHAVIOUR IN INTERCONNECTED INTEGRATED CIRCUITS BASED ON BLACK BOX APPROACH AND MODEL ORDER REDUCTION Grzegorz Lubkowski 1 , Radoslaw Piesiewicz 1 , Werner John 2 FhG IZM / University of Paderborn, Berlin/Paderborn – Germany Fraunhofer Institute for Reliability and Microintegration – Advanced Systems Engineering Technologiepark 34, 33100 Paderborn E-mail: grzegorz.lubkowski@p...

Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give data a more central role. This is achieved by introducing lifecycles and states for data objects, which is beneficial when modeling dataor knowl...

Cryptographic constructions of one primitive or protocol from another one usually come with a reductionist security proof, in the sense that the reduction turns any adversary breaking the derived scheme into a successful adversary against the underlying scheme. Very often the reduction is black-box in the sense that it only looks at the input/output behavior of the adversary and of the underlyi...

Despite its importance, the process of technostress remains significantly unstudied in MIS research. Here we review the relevant literature on technostress and synthesize the coping model of user adaptation (Beaudry and Pinsonneault, 2005) with transaction based models of technostress to align these theories with referent models of stress, appraisal and adaptation. We posit that technostress sh...

We develop a module-based framework for constraint modeling where it is possible to combine different constraint modeling languages and exploit their strengths in a flexible way. In the framework a constraint model consists of modules with clear input/output interfaces. When combining modules, apart from the interface, a module is a black box whose internals are invisible to the outside world. ...

Fast and reliable development of Web Applications (WA) calls for methods that address systematic design, and tools that cover all the aspects of the design process and complement the current implementation technologies. To ensure the reliability of WA it is important that they be validated and verified at early design phase. We focus on black-box, automated verification of the UML design of a W...

In this paper, Black Box approach is presented for behavioral modeling of a non linear power amplifier with memory effects. Large signal parameters of a Motorola LDMOS power amplifier driven by a WCDMA signal were extracted while taking into considerations the power amplifier’s bandwidth. The proposed model was validated based on the simulated data. Some validation results are presented both in...

The information overflow of today’s information society can be overcome by the usage of recommender systems. Due to the fact that most recommender systems act as black boxes, trust in a system decrease, especially when a recommendation failed. Recommender systems usually don’t offer any insight into the systems logic and cannot be questioned as it is normal for a recommendation process between ...