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Plain Old Telephone Service (POTS)
Published in Jerry D. Gibson, The Communications Handbook, 2018
Signalling has been integrated into a modern telecommunications network, depicted in Fig. 21.5, and when coupled with centralized data-bases, provides many of the features associated with today's intelligent network. The database, known as a service control point (SCP), contains the information needed to translate 800-numbers to the appropriate telephone location, among other items. The signalling information is sent over its own signalling links from one signalling processor to another, located at nodes called signal transfer points (STP). The signalling processors determine the actual switching of the customer circuits, performed by switching systems at service switching points. The bulk traffic carried over transmission media can be switched in times of service failures or to balance loads by digital crossconnect systems (DCS). The signalling links connect to the local network at a signalling point of interface (SPI), and the customer circuits connect at a point of presence. Today's signalling systems add much functionality to the network.
ATM Signaling and Traffic Control
Published in P. S. Neelakanta, ATM Telecommunications, 2018
Signaling is a means by which communication is established, released, monitored, controlled, and maintained between end-entities via the intervening networks in a telecommunication system. It is one of the two major functions of a telecommunication network. The primary function is the transportation of a message transmission across the network depicting an information transfer from a sending end to one or more destinations. An adjunct effort is essentially what is known as the signaling function. That is, in order to facilitate an information transfer, a communication path should be established between the sending and receiving ends; further, this path should be monitored while it is in use and it should be disconnected when the transfer of information is completed.
S
Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
signal-to-interference ratio (SIR) the ratio of the average power of the signal component to the average power of the interference component in a case where an information-bearing signal of interest has been corrupted by interfering signals. signal-to-noise plus interference ratio (SNIR) the ratio of total signal power to the sum of total noise power and total interference power at a receiver. The SNIR is a more complete indicator of received signal quality than either SIR or SNR, where the relative contribution of receiver noise and external sources of interference are either unknown or widely varying. It is a unitless quantity. See also signal-to-noise ratio, signal-tointerference ratio. signal-to-noise ratio (SNR) the ratio of the average power of the information signal component to the average power of the noise component in a signal consisting of the sum of an information signal component and a corrupting noise component. It is a unitless quantity. signaling procedures used to control (set up and clear down) calls and connections within a telecommunication network. signaling system 7 (SS7) a communications protocol used in common-channel signaling networks. signature a characteristic easily computed feature or function by which a particular object or signal may be at least tentatively identified. An example is the centroidal profile for an object having a well defined boundary. signature analysis (1) a test where the responses of a device over time are compared to a characteristic value called a signature, which is then compared to a known good one.
ANFIS Supervised PID Controlled SAPF for Harmonic Current Compensation at Nonlinear Loads
Published in IETE Journal of Research, 2022
Figure 5 represents a comparative model of the conventional control algorithm and ANFIS supervised control algorithm. The actual current is compared with a reference signal from the conventional filter (CF) and the error is recorded. This error is the actual activation signal to the PID controller for the generation of gate signaling. While, ANFIS compares the error signal Er and deviation in error signal ΔE with unit delay Z−1. This comparison is monitored through training data set of neural network and then more adequate excitation signal is fed to the PID controller. Now, this set of controller attribute controls the phase rectification of SAPF in a more effective manner. From the error deviation to SAPF phase compensation, the neural network plays smart computing in determination of more adequate fuzzy set rules. The harmonic current distortion is controlled in the nonlinear load system with functional response of correlated entities in ANFIS-PID APF compensation.
A resource-oriented decomposition approach for train timetabling problem with variant running time and minimum headway
Published in Transportation Letters, 2022
Zhengwen Liao, Jianrui Miao, Lingyun Meng, Haiying Li
In typical train timetabling models, a minimum headway constraint is applied to maintain the safety distance of two successive trains, as shown in Figure 3 where is the arrival minimum headway at station j, and is the departure minimum headway at station i. From a signaling aspect, the minimum headway is determined by two signal-related time components. One of them is the signal clearance time of the previous train (), and the other of them is the signal pre-occupied time of the following train (). In general, a minimum headway can be decomposed into two signal-related time components, which can be formulated as
Study of Full-body Virtual Embodiment Using noninvasive Brain Stimulation and Imaging
Published in International Journal of Human–Computer Interaction, 2021
To collect real-time physiological data from the brain, several imaging techniques are commonly employed by the researchers. Functional magnetic resonance imaging (fMRI) or positron emission tomography (PET) are among the widely used brain imaging techniques, but they depend on large equipment that effectively immobilizes the participant. A popular neuroimaging method is the EEG. EEG records electrophysiological signals, the neural oscillations, corresponding to summation of electrical discharges from large patches of neuronal cells with similar spatial orientation (Cohen, 2017). Typically, the EEG signal is recorded simultaneously from multiple electrodes placed on the scalp (EEG channels) against a non-encephalic reference electrode. Location of the EEG sensors is typically determined by the 10–20 international system for electrode positioning (Homan et al., 1987). Temporal resolution of the EEG is in order of milliseconds, allowing to record changes in neural oscillations following time-locked events with great precision (Gevins et al., 1995). Downsides of the EEG result from the necessity of the signal to pass through various tissues, especially the skull. Resulting main drawbacks of EEG are a poor spatial resolution and high susceptibility to noise. Besides the environmental noise, bodily movements are contaminants of the signal, as electrical signaling in muscles tends to overpower the brain sources of the signal. Participants are typically disallowed to move during an EEG investigation, or only a limited movement is permitted.