Legal Protection: WIPO (World Intellectual Property Organization) Presumably the major player in the field of international intellectual property protection and administrator of various multilateral treaties dealing with the legal and administrative aspects of intellectual property is the WIPO. Information on WIPO administered agreements in the field of industrial property (Paris Convention for the Protection of Industrial Property (1883), Madrid Agreement Concerning the International Registration of Marks (1891) etc.) can be found on: http://www.wipo.org/eng/general/index3.htm Information on treaties concerning copyright and neighboring rights (Berne Convention for the Protection of Literary and Artistic Works (1886) etc.) is published on: http://www.wipo.org/eng/general/index5.htm The most recent multilateral agreement on copyright is the 1996 WIPO Copyright Treaty. Among other things it provides that computer programs are protected as literary works and also introduces the protection of databases, which "... by reason of the selection or arrangement of their content constitute intellectual creations." Furthermore the 1996 WIPO Copyright Treaty contains provisions concerning technological measures, rights management information and establishes a new "right of communication to the public". It is available on: http://www.wipo.org/eng/diplconf/distrib/treaty01.htm

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Neural network A bottom-up artificial intelligence approach, a neural network is a network of many very simple processors ("units" or "neurons"), each possibly having a (small amount of) local memory. The units are connected by unidirectional communication channels ("connections"), which carry numeric data. The units operate only on their local data and on the inputs they receive via the connections. A neural network is a processing device, either an algorithm, or actual hardware, whose design was inspired by the design and functioning of animal brains and components thereof. Most neural networks have some sort of "training" rule whereby the weights of connections are adjusted on the basis of presented patterns. In other words, neural networks "learn" from examples and exhibit some structural capability for generalization.

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