Mixed Gaussian processes: A filtering approach
نویسندگان
چکیده
منابع مشابه
Adaptive filtering for non-Gaussian processes
A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and realworld signals, shows that the proposed method has overall...
متن کاملGP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs
This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs. The main contribution is GP-SUM, a filtering algorithm tailored to dynamic systems and observation models expressed as Gaussian processes (GP), that does not rely on linearizations or unimodal Gaussian approximations of the belief. The algorithm can be seen as a combination of a sampling-ba...
متن کاملDynamical Pose Filtering for Mixtures of Gaussian Processes
In this paper we present a method for performing discriminative human pose estimation using a mixture of Gaussian Processes appearance model to map directly from the image features to the multi-model pose distribution. In order to obtain a pose estimate for a sequence of frames, we introduce a dynamic programming algorithm for inferring a smooth pose sequence from the multi-model distribution g...
متن کاملAnalytical Results for the Error in Filtering of Gaussian Processes
Bayesian filtering of stochastic stimuli has received a great deal of attention recently. It has been applied to describe the way in which biological systems dynamically represent and make decisions about the environment. There have been no exact results for the error in the biologically plausible setting of inference on point process, however. We present an exact analysis of the evolution of t...
متن کاملThe Rate of Entropy for Gaussian Processes
In this paper, we show that in order to obtain the Tsallis entropy rate for stochastic processes, we can use the limit of conditional entropy, as it was done for the case of Shannon and Renyi entropy rates. Using that we can obtain Tsallis entropy rate for stationary Gaussian processes. Finally, we derive the relation between Renyi, Shannon and Tsallis entropy rates for stationary Gaussian proc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Probability
سال: 2016
ISSN: 0091-1798
DOI: 10.1214/15-aop1041