«Static and dynamic noisy data»
۱۵۲ نتیجهPerceptual Discrimination In Static and Dynamic Noise: Probing the Limits of the Diffusion Model of Decision Making
Twelve experiments investigated factors that affect the time course of perceptual processing and its effects on subsequent decision making. Stimuli in letter discrimination and brightness discrimination tasks were degraded with static and dynamic noise. The onset and the time cou
Stochastic processes in a confining harmonic potential inthe presence of static and dynamic measurement noise
Abstract We consider the overdamped dynamics of different stochastic processes,
including Brownian motion and autoregressive processes, continuous time
random walks, fractional motion, scaled motion,
confined by an harmonic potential. discuss effect both s
Title : Reconstruction of sparsely - sampled dynamic MRI data using Iterative “ Error Energy ” [ 1 ] Reduction
Introduction A well-known reconstruction technique developed by Gerchberg, based on “error energy” reduction [1], is extended in this study to sparsely sampled dynamic cardiac magnetic resonance imaging (CMRI). A-priori knowledge of static and dynamic regions in the FOV is used t
Damage Detection in Beam-like Structures using Finite Volume Method
In this paper the damage location in beam like-structure is determined using static and dynamic data obtained using finite volume method. The change of static and dynamic displacement due to damage is used to establish an indicator for determining the damage location. In order to
From Static to Dynamic Web Usage Mining: Towards Scalable Profiling and Personalization with Evolutionary Computation
In addition to its ever-expanding size and lack of structure, the World Wide Web has not been responsive to user preferences and interests. Personalization deals with tailoring a user’s interaction with the Web information space based on information about him/her. Mass profiling
Selecting relevant information and delaying irrelevant data for objects recognition
This paper presents basic principles as well as results obtained with our opportunistic and asynchronous object recognition system. The fundamental idea is to transform a static image into several dataflows of images primitives (e.g line segments, circular arcs, regions). The ran
Uncertainty-based learning of acoustic models from noisy data
We consider the problem of acoustic modeling of noisy speech data, where the uncertainty over the data is given by a Gaussian distribution. While this uncertainty has been exploited at the decoding stage via uncertainty decoding, its usage at the training stage remains limited to
Merging Live and pre-Captured Data to support Full 3D Head Reconstruction for Telepresence
This paper proposes a 3D head reconstruction method for low cost 3D telepresence systems that uses only a single consumer level hybrid sensor (color+depth) located in front of the users. Our method fuses the real-time, noisy and incomplete output of a hybrid sensor with a set of
“the Evolution of C2: Where Have We Been? Where Are We Going?” Probabilistic Ontologies and Pragmatics for Complex Systems Integration
Information systems are increasingly pervasive in our lives, and are becoming increasingly sophisticated as technology evolves. This has resulted in an evergrowing complexity that makes interoperability a major issue. We argue that addressing the interoperability problem requires
Regularization Methods for Prediction in Dynamic Graphs and e-Marketing Applications
Predicting connections among objects, based either on a noisy observation or on a sequence of observations, is a problem of interest for numerous applications such as recommender systems for e-commerce and social networks, and also in system biology, for inferring interaction pat