This paper considers spectral and autocovariance estimation for a zero-mean, band-limited, stationary process that has been sampled at time points jittered from a regular, equi-interval, sampling scheme. The case of interest is where the sampling scheme is near regular so that the jitter standard deviation is small compared to the sampling interval. Such situations occur with many time series c...

All known time of arrival (TOA) deinterleaving algorithms have great diiculty separating interleaved radar pulse trains when two or more of the trains are significantly jittered. Such scenarios tend to lead to overwhelming ambiguity and fragmentation diiculties when using traditional techniques. In this report we propose a modiied sequence search technique combined with a novel recursive neural...

We study the discrepancy of jittered sampling: a jittered sampling set P ⊂ [0, 1]d is generated for fixed m ∈ N by partitioning [0, 1]d into md axis aligned cubes of equal measure and placing a random point inside each of the N = md cubes. We prove that, for N sufficiently large, 1 10 d N 1 2 + 1 2d ≤ ED∗ N (P) ≤ √ d(logN) 1 2

This study investigates whether temporally jittered stimuli will produce performance-intensity, phonetically balanced (PI-PB) rollover in young adults with normal hearing. Although not yet explicitly stated in the literature, there is clinical and theoretical evidence to suggest that PI-PB rollover, such as that found in cases of acoustic neuroma, is caused by neural dyssynchrony in the auditor...

Image synthesis techniques requiringMonteCarlo integration frequentlyneed to generate uniformly distributed samples within the unit hypercube. The ideal sample generation method will maximize the variance reduction as the numberof samples increases. Strati cationvia jittering is one simple, tractable, R. L. Cook. Stochastic sampling in computer graphics. ACM Transactions on Graphics, 5(1):51–72...

3 ParamNN 2 3.1 Randomly Generated Seed Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3.2 Predicted Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.3 Best Predicted Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.4 Jittered Best Predicted Parameters . . . . . . . . . . . . . . ...