Results 271 to 280 of about 3,602,130 (312)

Signal processing models for point processes

ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A signal-processing model for the generation of point processes is derived. In the context of this model, the interval between successive events is treated as a time series. The input-output relationship of a system generating inter-event intervals is shown to be derivable from the intensity of the desired point process.
Don H. Johnson, Darel A. Linebarger
openaire   +1 more source

Networks, Point Processes, and Networks of Point Processes

2020
I consider two classes of statistical models: networks and point processes. These random structures are oftenused in situations where traditional statistical assumptions do not hold (e.g. the data are not independent or identically distributed), meaning extra care must be taken to develop and extend statistical theory and tools to these settings.
openaire   +1 more source

Interrupted Point Processes

Biometrical Journal, 1979
AbstractA simple random thinning procedure for point processes is considered. The model is used for the description of a pattern generated by positions of tree seedlings.
openaire   +2 more sources

Process-Family-Points

2006
Software system families are characterized through a structured reuse of components and a high degree of automation based on a common infrastructure. It is possible to increase the efficiency of software system families by an explicit consideration of process flows in application domains which are driven by processes.
Sebastian Kiebusch, Bogdan Franczyk, Andreas Speck   +2 more
openaire   +1 more source

The Entropy of a Point Process

Journal of the Society for Industrial and Applied Mathematics, 1965
In this paper the entropy of a point process is defined. This entropy can be expressed as a sum of two terms: (a) the numerical entropy, associated with the number of events in a fixed interval, and (b) the locational entropy, associated with the locations of those events in the interval.
openaire   +1 more source

A Point Process Approach to Filtered Processes

Methodology And Computing In Applied Probability, 2004
Let us start with a definition of a filtered process. Let \(\lambda\) be a nonnegative \(\sigma\)-finite measure on the real axis \(\mathbb R\) and \(\mu\) be a probability measure on \(\mathbb R_+\). Let \(\mathbb P\) be a Poisson point process on \(\mathbb R\times\mathbb R\) of intensity measure \(\lambda \otimes \mu\), and \(h: \mathbb R^2\times ...
openaire   +2 more sources

Extremal Splittings of Point Processes

Mathematics of Operations Research, 1985
The sequence with nth term defined by [(n + 1)p] − [np] is an extremal zero-one valued sequence of asymptotic mean p in the following sense (for example): if a fraction p of customers from a point process with iid interarrival times is sent to an exponential server queue according to a prespecified splitting sequence, then the long-term average queue ...
openaire   +2 more sources

Basics of Stochastic Processes, Point and Marked Point Processes

2015
The study of the dynamic performance of engineered systems subject to uncertainty requires the use of tools from stochastic processes. Although stochastic processes have been used extensively in many disciplines (e.g., see [1, 2, 3, 4]), this chapter will focus on the the mathematical background that supports the models presented later in the book. The
Mauricio Sánchez-Silva, Georgia-Ann Klutke   +1 more
openaire   +1 more source

Change-points for point processes

2018
This chapter studies estimation and testing methods for the intensities of parametric or functional Poisson models, for parametric or nonparametric hazard function under right-censoring and for point processes, with change-points at unknown time thresholds.
openaire   +2 more sources