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one of the sequences is xed and the other is random. The techniques of weak typicality allow us only to calculate the average set size of the conditionally typical set. Using the ideas of strong typicality, on the other hand, provides us with stronger bounds that work for all typical x n sequences. We outline the proof that Pr{(x n , Y n ) A (n) } 2 nI (X;Y ) for all typical x n . This approach was introduced by Berger [53] and is fully developed in the book by Csisz r and K rner [149]. a o Let (Xi , Yi ) be drawn i.i.d. p(x, y). Let the marginals of X and Y be p(x) and p(y), respectively. (a) Let A (n) be the strongly typical set for X. Show that |A (n) |=2nH (X) .

entry_link() Returns the URL for a given entry ID and archive type. entry_comment_count() Returns the number of comments for a given entry ID. entry_ping_count() Returns the number of pings for a given entry ID. fetch_category() Returns an individual category record for the given

Flash movie authoring by letting you share library assets with other Flash documents, either while authoring, or when a movie is played with the Flash Player. Shared runtime libraries help you create smaller files and easily make updates to multiple documents simultaneously by letting your document show library symbols and shared objects that are stored on an intranet or the Internet. Shared author-time libraries improve your work pace by letting you track, update, and swap symbols in any Flash document available on your computer or network. See Using shared library assets on page 165.

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1 is compared with a constant-length code for the same case, constituted from four codewords of two bits, 00, 01, 10, 11, it is seen that the code in Table 11 adds redundancy Assuming equally likely messages, the average number of transmitted bits per symbol is equal to 275 However, if for instance symbol s2 were characterized by a probability of being transmitted of 076, and all other symbols in this code were characterized by a probability of being transmitted equal to 008, then this source would transmit an average number of bits per symbol of 224 bits As seen in this simple example, a level of compression is possible when the information source is not uniform, that is, when a source generates messages that are not equally likely.

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This causes the sheet to be protected, but your macros can still make changes to the sheet. It s important to understand that this setting is not saved with the workbook. When the workbook is re-opened, you ll need to re-execute the statement in order to reapply the UserInterfaceOnly protection.

The source information measure, the channel capacity measure and coding are all related by one of the Shannon theorems, the channel coding theorem, which is stated as follows: If the information rate of a given source does not exceed the capacity of a given channel, then there exists a coding technique that makes possible transmission through this unreliable channel with an arbitrarily low error rate This important theorem predicts the possibility of error-free transmission through a noisy or unreliable channel This is obtained by using coding The above theorem is due to Claude Shannon [1, 2], and states the restrictions on the transmission of information through a noisy channel, stating also that the solution for overcoming those restrictions is the application of a rather sophisticated coding technique What is not formally stated is how to implement this coding technique.

Psychologists strive to benefit those with whom they work and take care to do no harm. In their professional actions, psychologists seek to safeguard the welfare and rights of those with whom they interact professionally and other affected persons, and the welfare of animal subjects of research. When conflicts occur among psychologists obligations or concerns, they attempt to resolve these conflicts in a responsible fashion that avoids or minimizes harm. Because psychologists scientific and professional judgments and actions may affect the lives of others, they are

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