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Let $P = {p(i)}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a source code that is optimal in the sense of minimizing expected codeword length. For some applications, however, a source code should instead minimize one of a family of nonlinear objective functions, $beta$-exponential means, those of the form $log_a sum_i p(i) a^{n(i)}$, where $n(i)$ is the length of the $i$th codeword and $a$ is a positive constant. Applications of such minimizations include a problem of maximizing the chance of message receipt in single-shot communications ($a<1$) and a problem of minimizing the chance of buffer overflow in a queueing system ($a>1$). This paper introduces methods for finding codes optimal for such exponential means. One method applies to geometric distributions, while another applies to distributions with lighter tails. The latter algorithm is applied to Poisson distributions. Both are extended to minimizing maximum pointwise redundancy.
A quasi-Gray code of dimension $n$ and length $ell$ over an alphabet $Sigma$ is a sequence of distinct words $w_1,w_2,dots,w_ell$ from $Sigma^n$ such that any two consecutive words differ in at most $c$ coordinates, for some fixed constant $c>0$. In
Huffman coding finds an optimal prefix code for a given probability mass function. Consider situations in which one wishes to find an optimal code with the restriction that all codewords have lengths that lie in a user-specified set of lengths (or, e
Locally recoverable (LRC) codes have recently been a focus point of research in coding theory due to their theoretical appeal and applications in distributed storage systems. In an LRC code, any erased symbol of a codeword can be recovered by accessi
An $(n, M)$ vector code $mathcal{C} subseteq mathbb{F}^n$ is a collection of $M$ codewords where $n$ elements (from the field $mathbb{F}$) in each of the codewords are referred to as code blocks. Assuming that $mathbb{F} cong mathbb{B}^{ell}$, the co
A Maximum Distance Separable code over an alphabet $F$ is defined via an encoding function $C:F^k rightarrow F^n$ that allows to retrieve a message $m in F^k$ from the codeword $C(m)$ even after erasing any $n-k$ of its symbols. The minimum possible