Get Advances in Self-Organizing Maps and Learning Vector PDF

By Thomas Villmann, Frank-Michael Schleif, Marika Kaden, Mandy Lange (eds.)

The ebook collects the medical contributions provided on the tenth Workshop on Self-Organizing Maps (WSOM 2014) held on the college of technologies Mittweida, Mittweida (Germany, Saxony), on July 2–4, 2014. beginning with the 1st WSOM-workshop 1997 in Helsinki this workshop makes a speciality of most modern leads to the sector of supervised and unsupervised vector quantization like self-organizing maps for facts mining and knowledge classification.

This tenth WSOM introduced jointly greater than 50 researchers, specialists and practitioners within the attractive small city Mittweida in Saxony (Germany) within sight the mountains Erzgebirge to debate new advancements within the box of unsupervised self-organizing vector quantization platforms and studying vector quantization ways for category. The publication comprises the approved papers of the workshop after a cautious overview procedure in addition to summaries of the invited talks. between those publication chapters there are first-class examples of using self-organizing maps in agriculture, computing device technological know-how, information visualization, wellbeing and fitness platforms, economics, engineering, social sciences, textual content and photo research and time sequence research. different chapters current the newest theoretical paintings on self-organizing maps in addition to studying vector quantization tools, comparable to concerning these the way to classical statistical selection methods.

All the contribution show that vector quantization equipment hide a wide variety of program parts together with information visualization of high-dimensional advanced info, complex choice making and class or information clustering and knowledge compression.

Show description

Read or Download Advances in Self-Organizing Maps and Learning Vector Quantization: Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 PDF

Best international_1 books

New PDF release: Algorithmic Learning Theory: 11th International Conference,

This booklet constitutes the refereed court cases of the eleventh overseas convention on Algorithmic studying conception, ALT 2000, held in Sydney, Australia in December 2000. The 22 revised complete papers awarded including 3 invited papers have been conscientiously reviewed and chosen from 39 submissions. The papers are geared up in topical sections on statistical studying, inductive common sense programming, inductive inference, complexity, neural networks and different paradigms, help vector machines.

Download e-book for kindle: CONCUR’99 Concurrency Theory: 10th International Conference by Rance Cleaveland (auth.), Jos C. M. Baeten, Sjouke Mauw

This e-book constitutes the complaints of the tenth overseas convention on Concurrency conception, CONCUR'99, held in Eindhoven, The Netherlands in August 1999. The 32 revised complete papers awarded including 4 invited contributions have been chosen from a complete of ninety one submissions. The papers handle all parts of semantics, logics, and verification ideas for concurrent platforms, particularly technique algebras, Petri nets, event-structures, real-time platforms, hybrid structures, stochastic platforms, decidability, model-checking, verification, refinement, time period and graph rewriting, allotted programming, common sense constraint programming, typing structures, and so forth.

Download e-book for kindle: NASA in the World: Fifty Years of International by John Krige;Angelina Long Callahan;Ashok Maharaj

The nationwide Aeronautics and house management is sometimes considered in nationwide phrases - as an American initiative constructed particularly to compete with the Soviet Union. but, from its inception, NASA was once mandated not just to maintain US management in area, but additionally to pursue overseas collaboration.

Natalya Shakhovska's Advances in Intelligent Systems and Computing: Selected PDF

The publication experiences on new theories and functions within the box of clever platforms and computing. It covers computational and synthetic intelligence equipment, in addition to advances in laptop imaginative and prescient, present factor in massive info and cloud computing, computation linguistics, cyber-physical structures in addition to themes in clever details administration.

Extra resources for Advances in Self-Organizing Maps and Learning Vector Quantization: Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014

Sample text

High accumulated magnitude means high learning up to the moment, and therefore unit becomes practically static. 4. The value of β, the forgetting factor. Using the definition of learning factor of (9), when β is equal to one, unit weights become the running weighted mean of the value of the data samples belonging to its Voronoi region, and adjacent regions (weighted according to its neighbourhood). To the contrary, lower values of β means that recent patterns have higher importance in the running weighted mean.

Then the same process would apply and, step by step, all the prototypes would converge to the center of mass of the distribution. In the simulation, we observe that the prototypes correctly self-organize. As a second example, we now consider a continuous stream of inputs. The point of this simulation is to demonstrate the ability of the neural field to selforganize from a continuous stream of inputs without requiring an explicit reset signal. Indeed, we present to the network a small patch of 100 × 100 pixels on which a rotating bar is drawn.

Then, introducing adaptive prototypes for defining the input, we show experimentally that such a neural field can actually self-organize in a way similar to Kohonen’s self-organizing maps [7]. 1 Results Detecting Where the Input Is Locally Maximal When self-organizing maps were introduced by [7], the author identified several processes “1. Formation of an activity cluster in the array around the unit at which activation is maximum. 2. Adaptive change in the input weights of those units where activity was confined ”.

Download PDF sample

Rated 4.06 of 5 – based on 25 votes