It has been recently proved that the redundancy r of any discrete memoryless source satisfies r 1 \Gamma H(p N ), where p N is the least likely source letter probability. This bound is achieved only by sources consisting of two letters. We prove a sharper bound if the number of source letters is greater than two. Also provided is a new upper bound on r, as function of the two least likely source letter probabilities which improve on previous results
We use the "conservation of entropy" [1] to derive a simple formula for the redundancy of...
The minimum expected number of bits needed to describe a random variable is its entropy, assuming kn...
We characterize the achievable pointwise redundancy rates for lossy data compression at a fixed dist...
In this paper, we provide a method to obtain tight lower bounds on the minimum redundancy achievable...
We study the redundancy of Huffman code (which, incidentally, is as old as the author of this paper)...
Abstract-If optimality is measured by average codeword length, Huffman's algorithm gives optima...
Huffman's algorithm gives optimal codes, as measured by average codeword length, and the redundancy ...
Copyright © 2014 Om Parkash, Priyanka Kakkar. This is an open access article distributed under the C...
Recent years have seen a resurgence of interest in redundancy of lossless coding. The redundancy (r...
AbstractAn n-ary Huffman sequence of length q is the list, in non-decreasing order, of the lengths o...
[[abstract]]One-to-one codes are nonsingular codes that assign a distinct codeword to each source sy...
One-to-one codes are “one shot ” codes that assign a distinct codeword to source symbols and are not...
Redundancy of universal codes for a class of sources determines by how much the actual code length e...
We consider the problem of bounding the average length of an optimal (Huffman) source code when only...
Lossless compression over a countable alphabet Lossless compression Mapping messages (sequences of s...
We use the "conservation of entropy" [1] to derive a simple formula for the redundancy of...
The minimum expected number of bits needed to describe a random variable is its entropy, assuming kn...
We characterize the achievable pointwise redundancy rates for lossy data compression at a fixed dist...
In this paper, we provide a method to obtain tight lower bounds on the minimum redundancy achievable...
We study the redundancy of Huffman code (which, incidentally, is as old as the author of this paper)...
Abstract-If optimality is measured by average codeword length, Huffman's algorithm gives optima...
Huffman's algorithm gives optimal codes, as measured by average codeword length, and the redundancy ...
Copyright © 2014 Om Parkash, Priyanka Kakkar. This is an open access article distributed under the C...
Recent years have seen a resurgence of interest in redundancy of lossless coding. The redundancy (r...
AbstractAn n-ary Huffman sequence of length q is the list, in non-decreasing order, of the lengths o...
[[abstract]]One-to-one codes are nonsingular codes that assign a distinct codeword to each source sy...
One-to-one codes are “one shot ” codes that assign a distinct codeword to source symbols and are not...
Redundancy of universal codes for a class of sources determines by how much the actual code length e...
We consider the problem of bounding the average length of an optimal (Huffman) source code when only...
Lossless compression over a countable alphabet Lossless compression Mapping messages (sequences of s...
We use the "conservation of entropy" [1] to derive a simple formula for the redundancy of...
The minimum expected number of bits needed to describe a random variable is its entropy, assuming kn...
We characterize the achievable pointwise redundancy rates for lossy data compression at a fixed dist...