By Toby Berger, Lee D. Davisson (auth.)
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Extra resources for Advances in Source Coding
Performance could be improved by introducing some coding delay in order to take future source outputs into consideration, too. LECTURE 7 Theory vs Practice and Some Open Problems In the final lccturc of this ovcrview of rate distortion theory, I shall bcgin by attcmpting to convcy somc fecling for the current status of the comparison of thcory and practicc in data compression. d. Gaussian sourcc and MSE criterion of Example 2 of Lecture 4 because this cxamplc has bccn treated the most thoroughly in the literature.
Cam bridge, Mass. , (1956) "On the Shannon Theory of Information Theory and Peredecü Reliable 38 References Transmission in the Case of Continuous Signals", Trans. IEEE, IT-2, 102-108. 47-160. Y. A. VAN DER HORST (1973) "BCH Source Codes", Submitted to IEEE Trans. on Information Theory. Y. Chapter 2. , (1969) "Tree Encoding of Memoryless Time-Discrete Sources with a Fidelity Criterion", Trans. IEEE, IT-15, 584-590. B. ANDERSON (1971) "Instrumentable Tree Encoding and Information Sources", Trans.
The code word corresponding to each such path is indicated in Figurc 5 directly to the right of the leaf at which the path terminates. Since thcrc arc 26 = 64 different words of length 6 that might be produced by ·the source, thcre usually will not be a code word that matches the source word exactly. _,y). For example, if.!. = 010110, then~ = 000110 is closest in the sense of the Hamming metric. When traversing the path- from the root to the leaf y = 000110, we branch first up, then down, and then up at the successive nodes cncountcrcd.
Advances in Source Coding by Toby Berger, Lee D. Davisson (auth.)