Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 - 10
of
6,175
INVARIANCE OF THE WHITE NOISE FOR KDV
, 2009
"... We prove the invariance of the mean 0 white noise for the periodic KdV. First, we show that the Besov-type space b b s p,∞, sp < −1, contains the support of the white noise. Then, we prove local well-posedness in b s p, ∞ for p = 2+, s = − 1 + such that 2 sp < −1. In establishing the local we ..."
Abstract
-
Cited by 21 (11 self)
- Add to MetaCart
We prove the invariance of the mean 0 white noise for the periodic KdV. First, we show that the Besov-type space b b s p,∞, sp < −1, contains the support of the white noise. Then, we prove local well-posedness in b s p, ∞ for p = 2+, s = − 1 + such that 2 sp < −1. In establishing the local
Biases in white noise analysis . . .
- PRESENTED AT: THE ANNUAL COMPUTATIONAL NEUROSCIENCE MEETING (CNS*02), CHICAGO, ILLINOIS
, 2002
"... White noise analysis methods for characterizing neurons typically ignore the dynamics of neural spike generation, assuming that spikes arise from an inhomogeneous Poisson process. We show that when spikes arise from a leaky integrate-and fire mechanism, a classical white-noise estimate of a neuro ..."
Abstract
- Add to MetaCart
White noise analysis methods for characterizing neurons typically ignore the dynamics of neural spike generation, assuming that spikes arise from an inhomogeneous Poisson process. We show that when spikes arise from a leaky integrate-and fire mechanism, a classical white-noise estimate of a
On the Autocorrelation of Complex Envelope of White Noise
"... Published in Viswanathan, R. (2006). On the autocorrelation of complex envelope of white noise. ..."
Abstract
- Add to MetaCart
Published in Viswanathan, R. (2006). On the autocorrelation of complex envelope of white noise.
White Noise Calculus
"... It has been often said that white noise calculus is founded on an infinite dimensional analogue of Schwartz type distribution theory on a finite dimensional space. In fact, the Gelfand triple $(E)\subset(L^{2})=L^{2}(E^{*}, \mu)\subset(E)^{*}$ ..."
Abstract
-
Cited by 1 (1 self)
- Add to MetaCart
It has been often said that white noise calculus is founded on an infinite dimensional analogue of Schwartz type distribution theory on a finite dimensional space. In fact, the Gelfand triple $(E)\subset(L^{2})=L^{2}(E^{*}, \mu)\subset(E)^{*}$
Amplification induced by white noise
, 2008
"... We investigate the amplification of the field induced by white noise. In the present study, we study a stochastic equation which has two parameters, the energy ω ( k) of a free particle and the coupling strength D between the field and white noise, where the quantity k represents the momentum of a f ..."
Abstract
- Add to MetaCart
We investigate the amplification of the field induced by white noise. In the present study, we study a stochastic equation which has two parameters, the energy ω ( k) of a free particle and the coupling strength D between the field and white noise, where the quantity k represents the momentum of a
Unit Roots in White Noise?!
"... Abstract We show that the empirical distribution of the roots of the vector auto-regression of order n fitted to T observations of a general stationary or non-stationary process, converges to the uniform distribution over the unit circle on the complex plane, when both T and n tend to infinity so t ..."
Abstract
- Add to MetaCart
that (ln T ) /n → 0 and n 3 /T → 0. In particular, even if the process is a white noise, the roots of the estimated vector auto-regression will converge by absolute value to unity. Researchers are often inclined to interpret the presence of an estimated root with a near-unit absolute value as evidence
A NOTE ON CONVOLUTION OPERATORS IN WHITE NOISE CALCULUS
, 2011
"... A note on convolution operators in white noise calculus ..."
WICK DERIVATIONS ON WHITE NOISE FUNCTIONALS
"... The white noise analysis, initiated by Hida [3] in 1975, has been developed to an infinite dimensional distribution theory on Gaussian space.E; / as an infinite dimensional analogue of Schwartz distribution theory on Euclidean space with Lebesgue measure. The mathematical framework of white noise ..."
Abstract
- Add to MetaCart
The white noise analysis, initiated by Hida [3] in 1975, has been developed to an infinite dimensional distribution theory on Gaussian space.E; / as an infinite dimensional analogue of Schwartz distribution theory on Euclidean space with Lebesgue measure. The mathematical framework of white noise
Results 1 - 10
of
6,175
