Learn More
Perceptual multistability, alternative perceptions of an unchanging stimulus, gives important clues to neural dynamics. The present study examined 56 perceptual dominance time series for a Necker cube stimulus, for ambiguous motion, and for binocular rivalry. We made histograms of the perceptual dominance times, based on from 307 to 2478 responses per time(More)
THERE IS RENEWED INTEREST in using hardware redundancy to mask faulty behavior in nanoelectronic components. In this article, we go back to the early ideas of von Neumann and review the key concepts behind N-tuple modular redundancy (NMR), hardware multiplex-ing, and interwoven redundant logic. We discuss several important concepts for redundant(More)
SUMMARY We present a multiplicative multifractal process to model tra$c which exhibits long-range dependence. Using tra$c trace data captured by Bellcore from operations across local and wide area networks, we examine the interarrival time series and the packet length sequences. We also model the frame size sequences of VBR video tra$c process. We prove a(More)
The Lempel-Ziv (LZ) complexity and its variants are popular metrics for characterizing biological signals. Proper interpretation of such analyses, however, has not been thoroughly addressed. In this letter, we study the the effect of finite data size. We derive analytic expressions for the LZ complexity for regular and random sequences, and employ them to(More)
— The precise nature of TCP dynamics over Internet connections has not been well understood, since the existing results are solely analytical or based on simulations. We employ the time-dependent exponent curves and logarithmic displacement curves to study TCP AIMD congestion window-size traces over Internet connections. We show that these dynamics have two(More)
Source traf®c streams as well as aggregated traf®c ¯ows often exhibit long-range-dependent (LRD) properties. In this paper, we study traf®c streams through their counting process representation. We ®rst study the condition for the measured LRD traf®c, as described by the interarrival time and packet size sequences, to be suf®ciently well approximated by a(More)
Due to the ubiquity of time series with long-range correlation in many areas of science and engineering, analysis and modeling of such data is an important problem. While the field seems to be mature, three major issues have not been satisfactorily resolved. (i) Many methods have been proposed to assess long-range correlation in time series. Under what(More)
—Time series measured in real world is often nonlinear, even chaotic. To effectively extract desired information from measured time series, it is important to preprocess data to reduce noise. In this Letter, we propose an adaptive denoising algorithm. Using chaotic Lorenz data and calculating root-mean-square-error, Lyapunov exponent, and correlation(More)