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Huffman code is used to compress data file, where the data is represented as a sequence of characters. Huffman's greedy algorithm uses a table giving how often each character occurs; it then uses this table to build up an optimal way of representing each character as a binary string. We call the binary string the codeword for that character. A property of Huffman code is that it is a prefix code, i.e., in Huffman coding, no codeword is a prefix of some other codeword. The advantage of prefix code is that it makes decoding easier, as we do not need to use delimiter between two successive codewords. Given the frequency of each of the character, we can devise a greedy algorithm for finding the optimal Huffman codeword of each of the characters. For details of the greedy algorithm,
In this assignment, we will build a compression library that compress text les using Huffman coding scheme. This library will have two programs: compress, and decompress; compress accepts a text file and produces a compressed representation of that text file; decompress accepts a file that was compressed with the compress program, and recovers the original file.
the problem that demonstrates inference from two dependent samples uses hypothetical data from TB vaccinations and the number of new cases before and after vaccinations for cases o
A mixture of benzene, toluene, and xylene enters a two-stage distillation process where some of the componentsare recovered. The distillation process operates at steady-state condi
Latent class analysis is a technique of assessing whether the set of observations including q categorical variables, in specific, binary variables, consists of the number of diffe
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
re-reference all these indexes
Johnson-Neyman technique: The technique which can be used in the situations where analysis of the covariance is not valid because of the heterogeneity of slopes. With this method
Two-phase sampling is the sampling scheme including two distinct phases, in the first of which the information about the particular variables of interest is collected on all the m
This is the powerful visualization tool for studying how the response relies on an explanatory variable given the values of other explanatory variables. The plot comprises of a num
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Collective risk models : The models applied to insurance portfolios which do not create direct reference to the risk characteristics of individual members of the portfolio when des
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