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Data-dependent jitter (DDJ) is a specific class of timing jitter. In particular, it is a form of deterministic jitter which is correlated with the sequence of bits in the data stream. It is also a form of ISI .
Jitter in serial bus architectures is measured by means of eye patterns. There are standards for jitter measurement in serial bus architectures. The standards cover jitter tolerance, jitter transfer function and jitter generation, with the required values for these attributes varying among different applications. Where applicable, compliant ...
A simple way to have the eye pattern display jitter in the signal is to estimate the symbol rate of the signal (perhaps by counting the average number of zero crossings in a known window of time) and acquiring many UIs in a single oscilloscope capture. The first zero crossing in the capture is located and declared to be the start of the first ...
Deterministic Networking (DetNet) is an effort by the IETF DetNet Working Group to study implementation of deterministic data paths for real-time applications with extremely low data loss rates, packet delay variation (jitter), and bounded latency, such as audio and video streaming, industrial automation, and vehicle control.
Time-Sensitive Networking (TSN) is a set of standards under development by the Time-Sensitive Networking task group of the IEEE 802.1 working group. [1] The TSN task group was formed in November 2012 by renaming the existing Audio Video Bridging Task Group [2] and continuing its work.
Instantaneous packet delay variation is the difference between successive packets—here RFC 3393 does specify the selection criteria—and this is usually what is loosely termed "jitter", although jitter is also sometimes the term used for the variance of the packet delay. As an example, say packets are transmitted every 20 ms.
Deterministic algorithms are by far the most studied and familiar kind of algorithm, as well as one of the most practical, since they can be run on real machines efficiently. Formally, a deterministic algorithm computes a mathematical function ; a function has a unique value for any input in its domain , and the algorithm is a process that ...
A scale-free network is a type of networks that is of particular interest of network science.It is characterized by its degree distribution following a power law. While the most widely known generative models for scale-free networks are stochastic, such as the Barabási–Albert model or the Fitness model can reproduce many properties of real-life networks by assuming preferential attachment ...