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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.
Window variables are the variables measured during the constrained interval of an observation period which is accepted as the proxies for the information over the whole period. Fo
Censored observations : An observation xi on some variable of interest is consired to be censored if it is known that xi Li (left-censored)or xi Ui (right-censored) where Li and Ui
The statistical methods for estimation and inference which are based on a function of sample observations, probability distribution of which does not rely upon a complete speci?cat
Machine learning is a term which literally means the ability of a machine to recognize patterns which have occurred repetitively and to improve its performance based on the past
difference between histogram and historigram
The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the
The generalization of the normal distribution used for the characterization of functions. It is known as a Gaussian process because it has Gaussian distributed finite dimensional m
The procedures used for determining how the quality of life is affected by the environment, in particular by factors such as air and solid wastes, water pollution, hazardous substa
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
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