13 papers · ranked by Valyu relevance
Marcin Zukowski
Huffman encoding has been an enduring technique for 70+ years, ubiquitous in compression algorithms since its invention. In this paper we propose a new approach to Huffman coding, based on a data structure from wavelet trees. The resulting pivot-coded Huffman (PivCo-Huffman) enables high-performance SIMD-friendly…
H. Yamamoto, Ken-ichi Iwata
This paper proposes a new lossless data compression coding scheme named an asymmetric encoding-decoding scheme (AEDS), which can be considered as a generalization of tANS (tabled variant of asymmetric numeral systems). In the AEDS, a data sequence s = s1s 2 · · · s n is encoded in backward order st, t = n, · · · , 2…
Muntahi Safwan Mahfi, Md. Manzurul Hasan, Gahangir Hossain
—In this paper, we introduce OBHS (Optimized Block Huffman Scheme), a novel lossless audio compression algorithm tailored for real-time streaming applications. OBHS leverages block-wise Huffman coding with canonical code representation and intelligent fallback mechanisms to achieve high compression ratios while…
Hongyang Liu, Wei Yan
For the discrete memoryless sources with a countably infinite alphabet, we prove that for any positive integer $k$, there exists a corresponding probability interval such that if the largest symbol probability $p_{1}$ falls in this interval, the optimal code length for the symbol equals $k$. Furthermore, for infinite…
Vinamra Singh
CABAC, the entropy coder of H.264/AVC and the basis for HEVC and VVC, decomposes multi-symbol values into bins via a binarization scheme before a binary arithmetic coder. H.264 uses Truncated Unary plus k-th order Exp-Golomb (UEG); alternatives include canonical Huffman and the entropy-conserving binarization (ECB)…
Alice Tor, Yuxin Wu, Stephen E Clarke, Lisa Yamada + 2 more
The complexity of neural data changes as the brain processes information during events. Universal lossless compression algorithms, which are broadly applicable and grounded in information theory, identify and exploit redundancies in data in order to compress it to essentially-optimal sizes regardless of underlying…
Ibrahim Nawaz, Parv Agarwal, Thomas Heinis
DNA storage is a developing field that uses DNA to archive digital data owing to its superior information density and stability. Although DNA storage has been performed on a significant scale, challenges arise from the synthesis and sequencing of data-encoded oligonucleotides. Synthesis of DNA introduces significant…
Kees Schouhamer Immink, Jos H. Weber, Tuan Thanh Nguyen, Kui Cai + 2 more
The design of low-complexity and efficient constrained codes has been a major research item for many years. This paper reports on a versatile method named concatenated constrained codes for designing efficient fixed-length constrained codes with small complexity. A concatenated constrained code comprises two (or more)…
Beatriz García García, Consuelo Martínez López, Ignacio F. Rúa, Patrick Solé
In this paper, we study the cyclicity of binary group codes, identifying them as ideals in a group algebra. We focus on the construction of $ω|ω¯$ codes, proving that they are self-dual group codes over the abelian group $C_{2}\timesC_{k}$. We demonstrate that for even integers $k>2$, if the polynomial $xk-1$ splits…
Gengsheng L. Zeng
The Ising model is able to memorize some patterns or solutions as stable states. An Ising network may automatically converge to a pre-stored solution for a random input. However, in many cases, the Ising model cannot perform this task. The gap is that for a set of desired patterns, one may not be able to construct an…
Huanqiu Zhang, Israel Nelken, Tatyana Sharpee
Deciphering the neural code requires identifying its fundamental symbols or code-words. Neural activity is usually interpreted either as a rate code – based on average spike counts – or as a temporal code, which distinguishes patterns with identical counts. Yet, the symbols of the code remain undefined. Here we show…
Ofer Hadar
Recent advances in image and video processing have been profoundly influenced by developments in information theory, source coding, and learning-based representations. Classical concepts such as entropy modeling, rate-distortion optimization, transform coding, and quantization are now being revisited in the context of…
Authors not listed
The Hidden Subgroup Problem (HSP) unifies several landmark quantum algorithms, yet systematic exploration of its variants and modern applications has slowed. This paper revives HSP-based algorithm design by examining new group structures with direct relevance to post-quantum cryptography, lattice problems, and…