標(biāo)題: Titlebook: Advances in Self-Organising Maps; Nigel Allinson,Hujun Yin,Jon Slack Conference proceedings 2001 Springer-Verlag London Limited 2001 Data [打印本頁(yè)] 作者: AMUSE 時(shí)間: 2025-3-21 17:37
書(shū)目名稱(chēng)Advances in Self-Organising Maps影響因子(影響力)
書(shū)目名稱(chēng)Advances in Self-Organising Maps影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Advances in Self-Organising Maps網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Advances in Self-Organising Maps網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Advances in Self-Organising Maps被引頻次
書(shū)目名稱(chēng)Advances in Self-Organising Maps被引頻次學(xué)科排名
書(shū)目名稱(chēng)Advances in Self-Organising Maps年度引用
書(shū)目名稱(chēng)Advances in Self-Organising Maps年度引用學(xué)科排名
書(shū)目名稱(chēng)Advances in Self-Organising Maps讀者反饋
書(shū)目名稱(chēng)Advances in Self-Organising Maps讀者反饋學(xué)科排名
作者: 古董 時(shí)間: 2025-3-21 22:02 作者: 樹(shù)木心 時(shí)間: 2025-3-22 01:19
https://doi.org/10.1007/978-1-4471-4048-1mize the differential entropies of the kernel outputs and, at the same time, to minimize the mutual information between these outputs. The learning scheme is based on . learning supplemented with a cooperative/competitive stage to achieve topographically-organized maps. As a potential application, we consider density estimation.作者: sphincter 時(shí)間: 2025-3-22 05:44 作者: Intellectual 時(shí)間: 2025-3-22 09:19
Iva Bojic,Tomislav Lipic,Vedran Podobnike, we suggest a new version of SOM, using the supervised learning approach. We compare the supervised version and the unsupervised version of SOM-SD on a benchmark problem involving visual patterns. As may be expected, the supervised version is able to solve the classification problem using very compact networks.作者: myalgia 時(shí)間: 2025-3-22 15:49
Lecture Notes in Computer Scienceto identify health inequality structure is critical. It is believed that health inequality analysis is a complex problem. Self- organisation mapping is therefore employed in this paper to analyse health inequalities based on a data set provided by the Centre for Disease Control and Prevention, USA (CDC).作者: Cocker 時(shí)間: 2025-3-22 17:53 作者: 聯(lián)邦 時(shí)間: 2025-3-23 00:56 作者: 帽子 時(shí)間: 2025-3-23 03:02 作者: 痛苦一生 時(shí)間: 2025-3-23 09:30 作者: panorama 時(shí)間: 2025-3-23 12:36
https://doi.org/10.1007/978-1-4471-4054-2processes of the SOMA network are divided into a learning mode and an association mode. In the learning mode, the similar perfect informations are represented by a few units on the competitive layer. In the association mode, when the information, whose parts are lost, is applied to the SOMA network,作者: arrogant 時(shí)間: 2025-3-23 17:39 作者: Cosmopolitan 時(shí)間: 2025-3-23 19:23 作者: analogous 時(shí)間: 2025-3-23 23:40
Erzhong Zhou,Jiajin Huang,Xinxin Xuplore the multidimensional properties of a data set of recent speculative attacks in search of potential associations between economic descriptors, and the size and duration of speculative attack’s real effects. We found that speculative attack’s real effects were associated with: the health of the 作者: 有組織 時(shí)間: 2025-3-24 03:56 作者: Pathogen 時(shí)間: 2025-3-24 08:36
https://doi.org/10.1007/978-3-319-21786-4rs. The topographic map approaches usually use the common vector space model for text document representation. We present here a new two stage representation which uses sentences as intermediate information units. In this way contextual information is preserved and influences the process of self-org作者: escalate 時(shí)間: 2025-3-24 12:27
Vu H. Nguyen,Hien T. Nguyen,Vaclav Snaselious possibilities regarding the norm and the direction of the adaptation vectors. The performance and convergence of each rule is evaluated by two criteria: topology preservation and quantization error.作者: Fatten 時(shí)間: 2025-3-24 15:18
Braulio Dumba,Golshan Golnari,Zhi-Li Zhangn-connected and of various intrinsic dimension. This technique is based onto the Induced Delaunay Triangulation of the data built by a Topology Representing Network. It opens the way to a new field of research and applications in data analysis, data modeling and forecasting.作者: thrombus 時(shí)間: 2025-3-24 22:42
https://doi.org/10.1007/978-1-4684-1977-1 between neurons. Even so, the structures of the data clusters may not be apparent and their shapes are often distorted. In this paper, a visualisation-induced SOM (ViSOM) is proposed as a new tool for data visualisation. The algorithm constrains the lateral contraction forces between a winning neur作者: addition 時(shí)間: 2025-3-25 02:34 作者: 斑駁 時(shí)間: 2025-3-25 05:46
Optical Properties of Polytypes of Germaniumtion measure-based model represents each cluster. The proposed algorithm is iterative. At the end of each iteration, a competition between the models is performed. Then the data is regrouped between the models. The “movement” of the data between the models and the retraining allows the minimization 作者: 誘拐 時(shí)間: 2025-3-25 07:59
Computational Solid State Physicsdom in the input vector are represented in the code. In particular, this may be applied to the problem of encoding data that predominantly lies on a manifold whose dimensionality is much less than the full dimensionality of the data space. In effect, the approach learns a subspace that approximates 作者: ASTER 時(shí)間: 2025-3-25 14:57
A Review of Solution Techniques,uctural information contained in geometrical structures is extracted using the pairwise geometric histograms. These histograms are quantised using a self-organising maps (SOM), as the SOMs offer a number of advantages over the standard equidistance histogram quantisation Using this trained SOM, a gl作者: gonioscopy 時(shí)間: 2025-3-25 19:08 作者: AUGER 時(shí)間: 2025-3-25 21:21
General Equations for Planetary Flight,e expression of a set of yeast genes in several experimental treatments. The structures are visualized in an intuitive manner with colors: The similarity of hue correspond to the similarity of the multivariate data. The clusters can be interpreted by visualizing changes of the data variables (expres作者: STANT 時(shí)間: 2025-3-26 03:23 作者: INTER 時(shí)間: 2025-3-26 05:07
Towards an information-theoretic approach to kernel-based topographic map formation,mize the differential entropies of the kernel outputs and, at the same time, to minimize the mutual information between these outputs. The learning scheme is based on . learning supplemented with a cooperative/competitive stage to achieve topographically-organized maps. As a potential application, we consider density estimation.作者: AWL 時(shí)間: 2025-3-26 08:43 作者: Collected 時(shí)間: 2025-3-26 15:54 作者: Blemish 時(shí)間: 2025-3-26 20:48
Analysing Health Inequalities Using SOM,to identify health inequality structure is critical. It is believed that health inequality analysis is a complex problem. Self- organisation mapping is therefore employed in this paper to analyse health inequalities based on a data set provided by the Centre for Disease Control and Prevention, USA (CDC).作者: 表臉 時(shí)間: 2025-3-26 21:53
Recursive learning rules for SOMs,ious possibilities regarding the norm and the direction of the adaptation vectors. The performance and convergence of each rule is evaluated by two criteria: topology preservation and quantization error.作者: Fracture 時(shí)間: 2025-3-27 03:54 作者: 飛行員 時(shí)間: 2025-3-27 07:34
http://image.papertrans.cn/a/image/149645.jpg作者: hurricane 時(shí)間: 2025-3-27 10:01
Canh V. Pham,Huan X. Hoang,Manh M. VuThis paper presents a concept of global distributed information network comprising millions of personal agents acting on the Internet on behalf of their owners.作者: nocturia 時(shí)間: 2025-3-27 17:06 作者: 豪華 時(shí)間: 2025-3-27 19:55 作者: BRAWL 時(shí)間: 2025-3-28 00:59
ty of Lincolnshire and Humberside, 13 - 15 June, 2001. The University is the newest of England‘s universities but it is situated in the heart of one of our oldest cities - founded by the Romans and overlooked by the towering mass of its medieval cathedral. Primarily Lincoln has always been a centre for the ri978-1-85233-511-3978-1-4471-0715-6作者: 提升 時(shí)間: 2025-3-28 05:54
Towards an information-theoretic approach to kernel-based topographic map formation,mize the differential entropies of the kernel outputs and, at the same time, to minimize the mutual information between these outputs. The learning scheme is based on . learning supplemented with a cooperative/competitive stage to achieve topographically-organized maps. As a potential application, w作者: 錢(qián)財(cái) 時(shí)間: 2025-3-28 08:21
A Statistical Tool to Assess the Reliability of Self-Organizing Maps,sitive than other neural paradigms to problems related to convergence, local minima, etc. This paper introduces objective statistical measures that can be used to assess the stability of the results of SOM, both on the distortion and on the topology preservation points of views.作者: LINE 時(shí)間: 2025-3-28 11:44
A SOM Association Network,processes of the SOMA network are divided into a learning mode and an association mode. In the learning mode, the similar perfect informations are represented by a few units on the competitive layer. In the association mode, when the information, whose parts are lost, is applied to the SOMA network,作者: LATE 時(shí)間: 2025-3-28 15:06
A Supervised Self-Organizing Map for Structured Data,e, we suggest a new version of SOM, using the supervised learning approach. We compare the supervised version and the unsupervised version of SOM-SD on a benchmark problem involving visual patterns. As may be expected, the supervised version is able to solve the classification problem using very com作者: 自制 時(shí)間: 2025-3-28 21:58 作者: 抱怨 時(shí)間: 2025-3-28 23:19
Exploring Financial Crises Data with Self-Organizing Maps (SOM),plore the multidimensional properties of a data set of recent speculative attacks in search of potential associations between economic descriptors, and the size and duration of speculative attack’s real effects. We found that speculative attack’s real effects were associated with: the health of the 作者: dilute 時(shí)間: 2025-3-29 05:03
Analysing Health Inequalities Using SOM,to identify health inequality structure is critical. It is believed that health inequality analysis is a complex problem. Self- organisation mapping is therefore employed in this paper to analyse health inequalities based on a data set provided by the Centre for Disease Control and Prevention, USA (作者: Ascendancy 時(shí)間: 2025-3-29 09:27
Integrating Contextual Information into Text Document Clustering with Self-Organizing Maps,rs. The topographic map approaches usually use the common vector space model for text document representation. We present here a new two stage representation which uses sentences as intermediate information units. In this way contextual information is preserved and influences the process of self-org作者: NAUT 時(shí)間: 2025-3-29 14:02
Recursive learning rules for SOMs,ious possibilities regarding the norm and the direction of the adaptation vectors. The performance and convergence of each rule is evaluated by two criteria: topology preservation and quantization error.作者: 發(fā)怨言 時(shí)間: 2025-3-29 18:08 作者: 小官 時(shí)間: 2025-3-29 20:58 作者: Adjourn 時(shí)間: 2025-3-30 01:52
An approach to automated interpretation of SOM,h higher level object consists of a varying number of lower level objects. Both low and high level data is available and needs to be utilized. The information from lower levels is transferred to higher level using data histograms of lower level clusters. The clusters are formed and interpreted autom作者: 防止 時(shí)間: 2025-3-30 05:30 作者: 制造 時(shí)間: 2025-3-30 12:07 作者: encyclopedia 時(shí)間: 2025-3-30 15:32
Shapesom,uctural information contained in geometrical structures is extracted using the pairwise geometric histograms. These histograms are quantised using a self-organising maps (SOM), as the SOMs offer a number of advantages over the standard equidistance histogram quantisation Using this trained SOM, a gl作者: avarice 時(shí)間: 2025-3-30 19:52
A New Interpolation Algorithm Employing a Self-Organizing Map,thod employing the transient characteristics of the SOM is proposed in this paper. In order to realize a smooth interpolation, a modified updating equation based on compensation vector is used in the proposed method. Furthermore, we define the criterion of smoothness, and the reasonable number of le作者: Deduct 時(shí)間: 2025-3-31 00:43 作者: overshadow 時(shí)間: 2025-3-31 03:30 作者: LINE 時(shí)間: 2025-3-31 08:18
Human Gait Analysis using SOM*, salient features characterising each cluster as well as differentiating it from others. It is shown and experimentally verified that salient features do exist within the internal structure of the kinematic data from which diagnostic signatures are elicited. Existence of such features could be used by clinicians in the orthopaedic field.作者: urethritis 時(shí)間: 2025-3-31 12:08 作者: 營(yíng)養(yǎng) 時(shí)間: 2025-3-31 17:10 作者: disparage 時(shí)間: 2025-3-31 19:40
Exploring Financial Crises Data with Self-Organizing Maps (SOM),banking system; the law origin; the level of economic development; the terms of trade; and the financial development. Interestingly, we did not find evidence of the beneficial roles played by the IMF and the high interest rate policies in solving financial crises..作者: 截?cái)?nbsp; 時(shí)間: 2025-3-31 22:09 作者: 帽子 時(shí)間: 2025-4-1 04:24
Visualisation Induced SOM (ViSOM),on and its neighbouring ones and hence regularises the inter-neuron distances. The mapping preserves directly the interneuron distances on the map along with the topology. It produces a graded mesh in the data space and can accommodate both training data and new arrivals. The ViSOM represents a class of discrete principal curves and surfaces.作者: 幾何學(xué)家 時(shí)間: 2025-4-1 09:16
An approach to automated interpretation of SOM,atically so as to summarize the information given by the SOM, and to produce meaningful indicators that are useful also to problem domain experts. The results show that the approach works well at least in the case study of pulp and paper mills technology data.作者: DEVIL 時(shí)間: 2025-4-1 12:13 作者: squander 時(shí)間: 2025-4-1 14:36 作者: HEED 時(shí)間: 2025-4-1 19:45
SOM-Based Exploratory Analysis of Gene Expression Data,sion in different treatments) at the cluster borders. The relationship between the organization of the SOM and the functional classes of the proteins encoded by the genes may additionally reveal interesting relationships between the functional classes, and substructures within them
