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Multilayer Networks A single perceptron will not implement the XOR. The XOR is a Boolean function that is true if one or the other input are true, but not if both are true. What is required for the exclusive OR is a two-layer neural network such as that shown in Figure 6-8. Figure 6-9 is an example of an XOR (obtained by an unspeci ed process of design). In the ow graph, the comparator F( ) is ideal (either true or false) and switches at a threshold of zero; the logic levels are + 1, 1. An interested reader may demonstrate that these two layers can generate an XOR by tracing inputs through Figure 6-9. The NOT function results from the XOR if one of the inputs is held true (+ 1). An arbitrary Boolean function may result for any number of inputs by combining basic AND, OR, and NOT. Learning in a multilayer arti cial neural network is equivalent to designing weighting factors. Unfortunately, the number of weighting factors grows exponentially with the number of layers used. Computers apply an algorithm to force the actual output to approach the desired output. The output desired for given inputs must be available for training the network.
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19.3.2 Change management in organisations
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The License Agreement is presented in a window that has a scrollbar that allows you to scroll through the agreement from top to bottom. It informs you that you are giving consent to be bound by all of the information within the agreement. That is, it is a legal agreement between you and Nortel as to the intentions of the VPN Client software, and exactly how that software can be used.
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3 Click the Normal mode button to return to Normal view.
Part VII
where a is a positive real number and J p ( w )is the new cost function (it is dependent on a). In the text we studied the case a = 0 (see expression (8.7) for J(w)). above modified cost function The penalizes the energy (or squared norm) of the vector w , is therefore useful in situations where and we want to avoid solutions with potentially large norms. Show that the optimal solution is given by w a = [R, aI]-'Rd,. Compute the resulting minimum cost, J a ( w a ) ,and show that J"(wp)> 0 - RudRzllRdu= Jmin, where J m i n : is the minimum cost associated with J ( w ) (cf. (8.11)). Let b = w a - w o denote the difference between the new solution w p and the linear leastw mean squares solution wo of (8.4). Show that R,dSw = Jmin J"(w"). Justify the validity of the following steepest-descent method for determining we:
RealNetworks has led the way in cross-platform authoring and playback. Versions of RealPlayer are available for Windows, OS X, and the full range of available mobile devices. The previous version of the player is also available for Macintosh OS 9, Unix, Linux, and even OS/2. MSN TV even plays RealAudio 3.0. By contrast, QuickTime is limited to Windows and Macintosh, and Microsoft s streaming video solution is basically Windows-only. RealNetworks has also led the way in terms of users; for years it was the only option for largescale streaming media sites. Even now, when it faces the stiffest competition it has ever had, its market share is very high. RealPlayer is included with major browsers, as well as with Windows and Red Hat Linux.
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Part VI
Sampling Strategies and Spaces
Promoting Your Podcast
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Part II: Editing with Premiere
Formatting Numbers Using the Format Cells Dialog Box
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Select the Color Sampler tool from the Tools panel. Go to the Options bar at the top of the screen and change the setting from point sample to at least 5 by 5 Average, as shown in Figure 7.11. This tells the tool to sample a grid of pixels that is 5 by 5 and average them instead of sampling a single point. This assures that some renegade pixel isn t accidentally sampled alone. This setting also affects the Eyedropper tool, which is okay because it shouldn t be set to sample single pixels for the same reason. Return to the Spring_Flowers.tif practice le.
SELECTED GENERAL PROPERTIES
(3) Plan formation. We saw above that a group will not form a collective unless they believe they can actually achieve the desired goal. This, in turn, implies there is at least one action known to the group that will take them 'closer' to the goal. However, it is possible that there are many agents that know of actions the group can perform in order to take them closer to the goal. Moreover, some members of the collective may have objections to one or more of these actions. It is therefore necessary for the collective to come to some agreement about exactly which course of action they will follow. Such an agreement is reached via negotiation or argumentation, of exactly the kind discussed in 7.
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