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Network Dynamics
Network dynamics is a research field for the study of Network theory, networks whose status changes in time. The dynamics may refer to the structure of connections of the units of a network, to the collective internal state of the network, or both. The networked systems could be from the fields of biology, chemistry, physics, sociology, economics, computer science, etc. Networked systems are typically characterized as complex systems consisting of many units coupled by specific, potentially changing, interaction topologies. For a dynamical systems' approach to discrete network dynamics, see sequential dynamical system. See also References Networks {{combin-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Network Theory
Network theory is the study of graphs as a representation of either symmetric relations or asymmetric relations between discrete objects. In computer science and network science, network theory is a part of graph theory: a network can be defined as a graph in which nodes and/or edges have attributes (e.g. names). Network theory has applications in many disciplines including statistical physics, particle physics, computer science, electrical engineering, biology, archaeology, economics, finance, operations research, climatology, ecology, public health, sociology, and neuroscience. Applications of network theory include logistical networks, the World Wide Web, Internet, gene regulatory networks, metabolic networks, social networks, epistemological networks, etc.; see List of network theory topics for more examples. Euler's solution of the Seven Bridges of Königsberg problem is considered to be the first true proof in the theory of networks. Network optimization Network pr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Network Analysis
Dynamic network analysis (DNA) is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA), social simulation and multi-agent systems (MAS) within network science and network theory. Dynamic networks are a function of time (modeled as a subset of the real numbers) to a set of graphs; for each time point there is a graph. This is akin to the definition of dynamical systems, in which the function is from time to an ambient space, where instead of ambient space time is translated to relationships between pairs of vertices. Overview There are two aspects of this field. The first is the statistical analysis of DNA data. The second is the utilization of simulation to address issues of network dynamics. DNA networks vary from traditional social networks in that they are larger, dynamic, multi-mode, multi-plex networks, and may contain varying levels of uncertainty. The main difference of DNA to SNA is that DNA takes interactions of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Baruch Barzel
Baruch Barzel (March 19, 1976) is an Israeli physicist and applied mathematician at Bar-Ilan University, a member of the Gonda Multidisciplinary Brain Research Center and of the Bar-Ilan Data Science Institute. His main research areas are statistical physics, complex systems, nonlinear dynamics and network science. In 2013 he introduced the concept of universality in the dynamics of complex networks, showing that complex systems from different domains condense into discrete forms, or universality classes, of dynamic behavior. In the following years, Barzel and colleagues developed a theoretical framework to predict the observed behavior of complex networked systems: their patterns of information flow; the timescales of their signal propagation; their resilience against failures and disruptions and their recoverability. During the COVID-19 PandemiBarzel's lab published the alternating quarantine strategy to mitigate the spread of SARS-CoV-2 alongside continuous socioeconomic act ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Small-world Network
A small-world network is a type of mathematical graph in which most nodes are not neighbors of one another, but the neighbors of any given node are likely to be neighbors of each other and most nodes can be reached from every other node by a small number of hops or steps. Specifically, a small-world network is defined to be a network where the typical distance ''L'' between two randomly chosen nodes (the number of steps required) grows proportionally to the logarithm of the number of nodes ''N'' in the network, that is: :L \propto \log N while the global clustering coefficient is not small. In the context of a social network, this results in the small world phenomenon of strangers being linked by a short chain of acquaintances. Many empirical graphs show the small-world effect, including social networks, wikis such as Wikipedia, gene networks, and even the underlying architecture of the Internet. It is the inspiration for many network-on-chip architectures in contempo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neurodynamics
Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons. At the level of neural ensembles, synchronized activity of large numbers of neurons can give rise to macroscopic oscillations, which can be observed in an electroencephalogram. Oscillatory activity in groups of neurons generally arises from feedback connections between the neurons that result in the synchronization of their firing patterns. The interaction between neurons can give rise to oscillations at a different frequency than the firing frequency of individual neurons. A well-known example of macro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Network Planning And Design
Network planning and design is an iterative process, encompassing topological design, network-synthesis, and network-realization, and is aimed at ensuring that a new telecommunications network or service meets the needs of the subscriber and operator.Penttinen A., ''Chapter 10 – Network Planning and Dimensioning, Lecture Notes: S-38.145 - Introduction to Teletraffic Theory'', Helsinki University of Technology, Fall 1999. The process can be tailored according to each new network or service.Farr R.E., ''Telecommunications Traffic, Tariffs and Costs – An Introduction For Managers'', Peter Peregrinus Ltd, 1988. A network planning methodology A traditional network planning methodology in the context of business decisions involves five layers of planning, namely: * need assessment and resource assessment * short-term network planning * IT resource * long-term and medium-term network planning * operations and maintenance. Each of these layers incorporates plans for different t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Network
In network science, a gradient network is a directed subnetwork of an undirected "substrate" computer network, network where each node (networking), node has an associated scalar potential and one out-link that points to the node with the smallest (or largest) potential in its neighborhood, defined as the union of itself and its Neighbourhood (graph theory), neighbors on the substrate network. Definition Transport takes place on a fixed network G = G(V,E) called the substrate graph. It has ''N'' nodes, V = \ and the set of edges E = \ . Given a node ''i'', we can define its set of neighbors in G by Si(1) = . Let us also consider a scalar field, ''h'' = defined on the set of nodes V, so that every node i has a scalar value ''h''''i'' associated to it. Gradient ∇''h''''i'' on a network: ∇h''i= (i, μ(i))'' i.e. the directed edge from ''i'' to ''μ(i)'', where ''μ''(''i'') ∈ Si(1) ∪ , and hμ has the maximum value in . ''Gradient network'' : ''∇G = ∇G (V, F) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gene Regulatory Network
A gene (or genetic) regulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell. GRN also play a central role in morphogenesis, the creation of body structures, which in turn is central to evolutionary developmental biology (evo-devo). The regulator can be DNA, RNA, protein or any combination of two or more of these three that form a complex, such as a specific sequence of DNA and a transcription factor to activate that sequence. The interaction can be direct or indirect (through transcribed RNA or translated protein). In general, each mRNA molecule goes on to make a specific protein (or set of proteins). In some cases this protein will be Protein#Structural proteins, structural, and will accumulate at the cell membrane or within the cell to give it particular structural properties. In other cases th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gaussian Network Model
The Gaussian network model (GNM) is a representation of a biological macromolecule as an elastic mass-and-spring network to study, understand, and characterize the mechanical aspects of its long-time large-scale dynamics. The model has a wide range of applications from small proteins such as enzymes composed of a single domain, to large macromolecular assemblies such as a ribosome or a viral capsid. Protein domain dynamics plays key roles in a multitude of molecular recognition and cell signalling processes. Protein domains, connected by intrinsically disordered flexible linker domains, induce long-range allostery via protein domain dynamics. The resultant dynamic modes cannot be generally predicted from static structures of either the entire protein or individual domains. The Gaussian network model is a minimalist, coarse-grained approach to study biological molecules. In the model, proteins are represented by nodes corresponding to α-carbons of the amino acid residues. Sim ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Single-frequency Networks
{{Unreferenced, date=January 2008 Dynamic Single Frequency Networks (DSFN) is a transmitter macrodiversity technique for OFDM based cellular networks. DSFN is based on the idea of single frequency networks (SFN), which is a group of radio transmitters that send the same signal simultaneously over the same frequency. The term originates from the broadcasting world, where a broadcast network is a group of transmitters that send the same TV or radio program. Digital wireless communication systems based on the OFDM modulation scheme are well-suited to SFN operation, since OFDM in combination with some forward error correction scheme can eliminate intersymbol interference and fading caused by multipath propagation without the use of complex equalization. The concept of DSFN implies the SFN grouping is changed dynamically over time, from timeslot to timeslot. The aim is to achieve efficient spectrum utilization for downlink unicast or multicast communication services in centrally contro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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