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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.
Quincunx is the device used by Galton to illustrate his lectures, which is shown in the Figure. It had a glass face and a funnel at its top. The shot was passed through funnel an
There is high level of fluctuation in a zigzag pattern in the time series for RESI1 which indicates that there is possibly negative autocorrelation present. Column C11 show
Regression line drawn as y= c+ 1075x ,when x was2, and y was 239,given that y intercept was 11. Calculate the residual ?
3. a. A researcher in Hong Kong computes the correlation between the percentage of employee turnover and the local unemployment rate (also expressed as a percentage) over a 20-mont
A value related with the square matrix which represents sums and products of its elements. For instance, if the matrix is then the determinant of A (conventionally written as
Principal factor analysis is the method of factor analysis which is basically equivalent to a principal components analysis performed on reduced covariance matrix attained by repl
properties of chebyshevs lemma
Matching coefficient is a similarity coefficient for data consisting of the number of binary variables which is often used in cluster analysis. It can be given as follows he
how to find the PDF and CDF of a gamma random variable with given equation?
The rapid development or growth of the disease in a community or region. Statistical thinking has made very much significant contributions to the understanding of such type of phen
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