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Decoding of convolutional codes poses a significant challenge for coding theory. Classical methods, based on e.g. Viterbi decoding, suffer from being computationally expensive and are restricted therefore to codes of small complexity. Based…

Information Theory · Computer Science 2009-09-04 Jose Ignacio Iglesias Curto , Uwe Helmke

In the pursuit of a reduced energy demand of VVC decoders, it was found that the coding tool configuration has a substantial influence on the bit rate efficiency and the decoding energy demand. The Advanced Design Space Exploration…

Image and Video Processing · Electrical Eng. & Systems 2024-10-02 Teresa Stürzenhofäcker , Matthias Kränzler , Christian Herglotz , André Kaup

The aim of this paper is to prove coding theorems for the wiretap channel coding problem and secret key agreement problem based on the the notion of a hash property for an ensemble of functions. These theorems imply that codes using sparse…

Information Theory · Computer Science 2012-05-22 Jun Muramatsu , Shigeki Miyake

Subsystem codes protect quantum information by encoding it in a tensor factor of a subspace of the physical state space. Subsystem codes generalize all major quantum error protection schemes, and therefore are especially versatile. This…

Quantum Physics · Physics 2008-11-11 Salah A. Aly , Andreas Klappenecker

We provide a novel framework to study subspace codes for non-coherent communications in wireless networks. To this end, an analog operator channel is defined with inputs and outputs being subspaces of $\mathbb{C}^n$. Then a certain distance…

Information Theory · Computer Science 2022-01-31 Mahdi Soleymani , Hessam Mahdavifar

Qubits with predominantly erasure errors present distinctive advantages for quantum error correction(QEC) and fault tolerant quantum computing. Logical qubits based on dual-rail encoding that exploit erasure detection have been recently…

We present a two-step decoder for the parity code and evaluate its performance in code-capacity and faulty-measurement settings. For noiseless measurements, we find that the decoding problem can be reduced to a series of repetition codes…

We analyze Linear Programming (LP) decoding of graphical binary codes operating over soft-output, symmetric and log-concave channels. We show that the error-surface, separating domain of the correct decoding from domain of the erroneous…

Information Theory · Computer Science 2016-11-15 Michael Chertkov , Mikhail Stepanov

Neural speech codecs aim to compress input signals into minimal bits while maintaining content quality in a low-latency manner. However, existing neural codecs often trade model complexity for reconstruction performance. These codecs…

Sound · Computer Science 2024-10-04 Yuzhe Gu , Enmao Diao

The overhead of quantum error correction (QEC) poses a major bottleneck for realizing fault-tolerant computation. To reduce this overhead, we exploit the idea of erasure qubits, relying on an efficient conversion of the dominant noise into…

Quantum Physics · Physics 2025-09-30 Shouzhen Gu , Alex Retzker , Aleksander Kubica

We design short blocklength codes for the Gaussian wiretap channel under information-theoretic security guarantees. Our approach consists in decoupling the reliability and secrecy constraints in our code design. Specifically, we handle the…

Information Theory · Computer Science 2023-01-24 Vidhi Rana , Remi A. Chou

Recently, the notions of self-orthogonal subspace codes and LCD subspace codes were introduced, and LCD subspace codes obtained from mutually unbiased weighing matrices were studied. In this paper, we provide a method of constructing…

Combinatorics · Mathematics 2024-07-09 Dean Crnković , Keita Ishizuka , Hadi Kharaghani , Sho Suda , Andrea Švob

A spread code is a set of vector spaces of a fixed dimension over a finite field Fq with certain properties used for random network coding. It can be constructed in different ways which lead to different decoding algorithms. In this work we…

Information Theory · Computer Science 2014-06-20 Felice Manganiello , Anna-Lena Trautmann

Coded compressed sensing is an algorithmic framework tailored to sparse recovery in very large dimensional spaces. This framework is originally envisioned for the unsourced multiple access channel, a wireless paradigm attuned to…

Information Theory · Computer Science 2019-10-23 Vamsi K. Amalladinne , Jean-Francois Chamberland , Krishna R. Narayanan

We gather and examine in detail gate decomposition techniques for continuous-variable quantum computers and also introduce some new techniques which expand on these methods. Both exact and approximate decomposition methods are studied and…

Quantum Physics · Physics 2021-02-10 Timjan Kalajdzievski , Nicolás Quesada

This paper introduces a subspace method for the estimation of an array covariance matrix. It is shown that when the received signals are uncorrelated, the true array covariance matrices lie in a specific subspace whose dimension is…

Numerical Analysis · Computer Science 2014-11-04 Mostafa Rahmani , George Atia

A Viterbi-like decoding algorithm is proposed in this paper for generalized convolutional network error correction coding. Different from classical Viterbi algorithm, our decoding algorithm is based on minimum error weight rather than the…

Information Theory · Computer Science 2019-02-12 Hengjie Yang , Wangmei Guo

High-rate concatenated quantum codes offer a promising pathway toward fault-tolerant quantum computation, yet designing efficient decoders that fully exploit their error-correction capability remains a significant challenge. In this work,…

Quantum Physics · Physics 2026-01-15 Chao Zhang , Zipeng Wu , Jiahui Wu , Shilin Huang

We consider the locality of encoding and decoding operations in distributed storage systems (DSS), and propose a new class of codes, called locally encodable and decodable codes (LEDC), that provides a higher degree of operational locality…

Information Theory · Computer Science 2015-04-21 Son Hoang Dau , Han Mao Kiah , Wentu Song , Chau Yuen

We propose computationally efficient encoders and decoders for lossy compression using a Sparse Regression Code. The codebook is defined by a design matrix and codewords are structured linear combinations of columns of this matrix. The…

Information Theory · Computer Science 2014-05-20 Ramji Venkataramanan , Tuhin Sarkar , Sekhar Tatikonda