Small-world neural network
WebAug 1, 2024 · This paper presents two novel small-world neural networks, the Watts-Strogatz small-world based on a BP neural network (WSBP) and a Newman-Watts small-world neural network based on a BP neural network (NWBP), related to previous research of complex networks. WebA Cellular Neural Network (CNN) is a neural network model linked only to neighborhoods and which is suitable for image processing, such as noise reduction and edge detection. A …
Small-world neural network
Did you know?
WebSep 6, 2024 · The bionic small-world neural network structure has inspired various application scenarios. However, in previous studies, the long-range wirings in the small-world network have been found to cause network instability. In this study, we investigate the influence of neural network training on the small-world topology. WebAbstract. We study a model of associative memory based on a neural network with small-world structure. The efficacy of the network to retrieve one of the stored patterns exhibits a phase transition at a finite value of the disorder. The more ordered networks are unable to recover the patterns, and are always attracted to mixture states.
WebOct 24, 2024 · The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be …
WebFeb 23, 2016 · The models are utilized to simulate a subset of units recorded from a large biological neural network using multiple electrodes. Two metrics for quantifying the small-world-ness both suggest that ... WebApr 13, 2024 · Efficient processing and transfer of information in neurons have been linked to noise-induced resonance phenomena such as coherence resonance (CR), and adaptive rules in neural networks have been mostly linked to two prevalent mechanisms: spike-timing-dependent plasticity (STDP) and homeostatic structural plasticity (HSP). Thus this …
WebFeb 28, 2005 · A small-world network is defined by two properties. First, the average clustering coefficient C is larger than for a corresponding random network with the same …
Small-world networks tend to contain cliques, and near-cliques, meaning sub-networks which have connections between almost any two nodes within them. This follows from the defining property of a high clustering coefficient. Secondly, most pairs of nodes will be connected by at least one short path. This … See more A small-world network is a 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. Due to this, most neighboring … See more Small-world properties are found in many real-world phenomena, including websites with navigation menus, food webs, electric power grids, metabolite processing networks, networks of brain neurons, voter networks, telephone call graphs, and airport networks. … See more It is hypothesized by some researchers, such as Barabási, that the prevalence of small world networks in biological systems may reflect … See more Applications to sociology The advantages to small world networking for social movement groups are their resistance to change due to the filtering apparatus of using … See more In another example, the famous theory of "six degrees of separation" between people tacitly presumes that the domain of discourse is the set of people alive at any one time. The number of degrees of separation between Albert Einstein and Alexander the Great is … See more The main mechanism to construct small-world networks is the Watts–Strogatz mechanism. Small-world networks can also be introduced with time-delay, which will not only produce fractals but also chaos under the right conditions, … See more • Barabási–Albert model – algorithm for generating random networks • Climate as complex networks – Conceptual model to generate insight into climate science • Dual-phase evolution – Process that drives self-organization within complex adaptive systems See more dart silver scotlandWebApr 9, 2024 · Our small-world models, called SWNets, provide several intriguing benefits: they facilitate data (gradient) flow within the network, enable feature-map reuse by adding … bistro md weight loss reviewsWebWe study a model of associative memory based on a neural network with small-world structure. The efficacy of the network to retrieve one of the stored patterns exhibits a phase transition at a finite value of the disorder. The more ordered networks are unable to recover the patterns, and are always attracted to non-symmetric mixture states. bistro meals fresh marketWebJun 15, 2014 · A small-world neural network has stronger generalization ability with high transfer efficiency than that of the regular neural networks. This paper presents two novel small-world neural networks, the Watts-Strogatz small-world based on a BP neural network (WSBP) and a Newman-Watts small-world neural network based on a BP neural network … darts in fortitude valleyWebAiming to solve the problem of the relatively large architecture for the small-world neural network and improve its generalization ability, we propose a pruning feedforward small-world neural network based on a dynamic regularization method with the smoothing l 1/2 norm (PFSWNN-DSRL1/2) and apply it to nonlinear system modeling. dart shp sbc engine blockWebNov 11, 2024 · The goal of deep anomaly detection is to identify abnormal data by utilizing a deep neural network trained by a normal training dataset. In general, industrial visual anomaly detection problems distinguish normal and abnormal data through small morphological differences, such as cracks and stains. Nevertheless, most existing … dart singlewhereWebJul 14, 2024 · In this study, we proposed a spiking neural network with small-world topology (SWSNN), where Izhikevich neuron models and synaptic plasticity models with excitatory and inhibitory synapses are introduced to represent nodes and … bistro meals dog food