If pi (i = 1,...,N) is the probability of the i-th letter of a memoryless source, the length li of the corresponding binary Huffman codeword can be very different from the value − log ∑pi. For a typical letter, however, li ∑ ≈ − log pi. More pre-pj < 2 −c(m−2)+2 cisely, P − m = where c ≈ 2.27.

and the associated decoder, using a feedback decoding rule, is implemented as P pipelined identical elementary decoders. Consider a binary rate R=1/2 convolutional encoder with constraint length K and memory M=K-1. The input to the encoder at time k is a bit dk and the corresponding codeword

is corrupted by one or more bit errors, then as soon as the receiver by random chance correctly detects a self-synchronizing string, the receiver can continue properly parsing the bit sequence into codewords. Most commonly used binary prefix codes, including Huffman codes, are “complete”, in the sense

Optimal (minimum cost) binary prefix-free codes for infinite sources with geometrically distributed frequencies, e.g., P = {pi (1 − p)} ∞ i=0, 0 < p < 1, were first (implicitly) suggested by Golomb over thirty years ago in the context of run-length encodings. Ten years later Gallager and Van

Abstract:- Given a list W = [w1,…, wn] of n positive symbol weights, and a list L = [l1,…,ln] of n corresponding integer codeword lengths, it is required to find the new list L when a new value x is inserted in or when an existing value is deleted from the list of weights W. The presented algorithm

C be the corresponding Huffman code that has 26 codewords {c1, c2,..., c26} with average codeword length 4.15573. The respective lengths of the codewords are given by {`1, `2,..., `26}. According to P, a concatenation of 1000 symbols randomly generated from A is Huffman encoded into a bitstream x

We perform compressed pattern matching in Huffman encoded texts. A modified Knuth-Morris-Pratt (KMP) algorithm is used in order to overcome the problem of false matches, i.e., an occurrence of the encoded pattern in the encoded text that does not correspond to an occurrence of the pattern itself

, in which codes are restricted to the set of codes in which none of the n codewords is longer than a given length, lmax. Binary lengthlimited coding can be done in O(nlmax) time and O(n) space using the widely used Package-Merge algorithm. In this paper the Package-Merge approach is generalized in order

In this study, the focus was on the use of ternary tree over binary tree. Here, a new two pass Algorithm for encoding Huffman ternary tree codes was implemented. In this algorithm we tried to find out the codeword length of the symbol. Here I used the concept of Huffman encoding. Huffman encoding

In this study, the focus was on the use of ternary tree over binary tree. Here, a new one pass Algorithm for Decoding adaptive Huffman ternary tree codes was implemented. To reduce the memory size and fasten the process of searching for a symbol in a Huffman tree, we exploited the property