Abstract.We study estimation of theWigner time-frequency spectrum of Gaussian stochastic processes. Assuming the covariance belongs to the Feichtinger algebra, we construct an estimation kernel that gives a mean square error arbitrarily close to the infimum over kernels in the Feichtinger algebra.2000 AMS Mathematics Subject Classification: Primary: 60G15, 42B35, 60G35, 62M15, 94A12. Abstract.We study estimation of theWigner time-frequency spectrum of Gaussian stochastic processes. Assuming the covariance belongs to the Feichtinger algebra, we construct an estimation kernel that gives a mean square error arbitrarily close to the infimum over kernels in the Feichtinger algebra.2000 AMS Mathematics Subject Classification: Primary: 60G15,...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
This paper treats estimation of the Wigner-Ville spectrum (WVS) of Gaussian continuous-time stochast...
Journal PaperCurrent theories of a time-varying spectrum of a nonstationary process all involve, eit...
This paper investigates the multiple windows of the mean squared error optimal time-frequency kernel...
This paper presents a new regularized kernel-based approach for the estimation of the second order m...
This work brings together two powerful concepts in Gaussian processes: the variational approach to s...
This work brings together two powerful concepts in Gaussian processes: the variational approach to s...
The study of a time-frequency image is often the method of choice to address key issues in cognitive...
This work brings together two powerful concepts in Gaussian processes: the variational approach to s...
In this correspondence, the form of the one-dimensional probability distribution function for the Wi...
This is the final version of the article. It first appeared at http://jmlr.org/proceedings/papers/v3...
We study the instantaneous frequency IF of continuoustime, complex-valued, zero-mean, proper, mean-...
Gaussian processes are a powerful and flexible class of nonparametric models that use covariance fun...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
This paper treats estimation of the Wigner-Ville spectrum (WVS) of Gaussian continuous-time stochast...
Journal PaperCurrent theories of a time-varying spectrum of a nonstationary process all involve, eit...
This paper investigates the multiple windows of the mean squared error optimal time-frequency kernel...
This paper presents a new regularized kernel-based approach for the estimation of the second order m...
This work brings together two powerful concepts in Gaussian processes: the variational approach to s...
This work brings together two powerful concepts in Gaussian processes: the variational approach to s...
The study of a time-frequency image is often the method of choice to address key issues in cognitive...
This work brings together two powerful concepts in Gaussian processes: the variational approach to s...
In this correspondence, the form of the one-dimensional probability distribution function for the Wi...
This is the final version of the article. It first appeared at http://jmlr.org/proceedings/papers/v3...
We study the instantaneous frequency IF of continuoustime, complex-valued, zero-mean, proper, mean-...
Gaussian processes are a powerful and flexible class of nonparametric models that use covariance fun...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...
International audienceThis work brings together two powerful concepts in Gaussian processes: the var...