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Convolutional sparse coding (CSC) is an important building block of many computer vision applications ranging from image and video compression to deep learning. We present two contributions to the state of the art in CSC. First, we…

Computer Vision and Pattern Recognition · Computer Science 2018-04-10 Lama Affara , Bernard Ghanem , Peter Wonka

Concatenation is a method of building long codes out of shorter ones, it attempts to meet the problem of decoding complexity by breaking the required computation into manageable segments. Concatenated Continuous Phase Frequency Shift Keying…

Information Theory · Computer Science 2011-05-24 Labib Francis Gergis

A superimposed code is a collection of binary vectors (codewords) with the property that no vector is contained in the Boolean sum of any $k$ others, enabling unique identification of codewords within any group of $k$. Superimposed codes…

Data Structures and Algorithms · Computer Science 2025-08-05 Gianluca De Marco , Dariusz R. Kowalski

The goal of combining beamforming and space-time coding in this work is to obtain full-diversity order and to provide additional received power (array gain) compared to conventional space-time codes. In our system, we consider a…

Information Theory · Computer Science 2008-04-23 Siavash Ekbatani , Hamid Jafarkhani

This paper investigates the design of self-connected spatially coupled low-density parity-check (SC-LDPC) codes. First, a termination method is proposed to reduce rate loss. Particularly, a single-side open SC-LDPC ensemble is introduced,…

Information Theory · Computer Science 2023-07-03 Yihuan Liao , Min Qiu , Jinhong Yuan

The concept of generalized concatenated quantum codes (GCQC) provides a systematic way for constructing good quantum codes from short component codes. We introduce a stabilizer formalism for GCQCs, which is achieved by defining quantum…

Quantum Physics · Physics 2013-10-14 Yun-Jiang Wang , Bei Zeng , Markus Grassl , Barry C. Sanders

Low-density parity-check (LDPC) convolutional codes (or spatially-coupled codes) have been shown to approach capacity on the binary erasure channel (BEC) and binary-input memoryless symmetric channels. The mechanism behind this spectacular…

Information Theory · Computer Science 2015-03-20 Arvind Yedla , Yung-Yih Jian , Phong S. Nguyen , Henry D. Pfister

In this paper, we study the application of spatially coupled LDPC codes with sub-block locality for space division multiplexing. We focus on the information exchange between the sub-blocks and compare decoding strategies with respect to the…

Information Theory · Computer Science 2023-10-25 Haizheng Li , Laurent Schmalen

Raptor codes are known as precoded rateless codes that achieve the capacity of BEC. However the maximum degree of Raptor codes needs to be unbounded to achieve the capacity. In this paper, we prove that spatially-coupled precoded rateless…

Information Theory · Computer Science 2014-01-29 Kosuke Sakata , Kenta Kasai , Kohichi Sakaniwa

Convolutional low-density parity-check (LDPC) codes (or spatially-coupled codes) have now been shown to achieve capacity on binary-input memoryless symmetric channels. The principle behind this surprising result is the threshold-saturation…

Information Theory · Computer Science 2013-01-25 Arvind Yedla , Yung-Yih Jian , Phong S. Nguyen , Henry D. Pfister

Sparse Regression Codes (SPARCs) are capacity-achieving codes introduced for communication over the Additive White Gaussian Noise (AWGN) channels and were later extended to general memoryless channels. In particular it was shown via…

Information Theory · Computer Science 2024-09-10 Yuhao Liu , Yizhou Xu , Tianqi Hou

We present a method for post-processing point clouds' geometric information by applying a previously proposed fractional super-resolution technique to clouds compressed and decoded with MPEG's G-PCC codec. In some sense, this is a…

Image and Video Processing · Electrical Eng. & Systems 2022-08-11 Renan U. B. Ferreira , Tomas M. Borges , Diogo C. Garcia , Ricardo L. de Queiroz

Generalized Concatenated codes are a code construction consisting of a number of outer codes whose code symbols are protected by an inner code. As outer codes, we assume the most frequently used Reed-Solomon codes; as inner code, we assume…

Information Theory · Computer Science 2010-04-29 Christian Senger , Vladimir Sidorenko , Martin Bossert , Victor Zyablov

Recently, a parallel decoding framework of $G_N$-coset codes was proposed. High throughput is achieved by decoding the independent component polar codes in parallel. Various algorithms can be employed to decode these component codes,…

Information Theory · Computer Science 2020-04-22 Xianbin Wang , Jiajie Tong , Huazi Zhang , Shengchen Dai , Rong Li , Jun Wang

In this paper, we introduce a novel class of pre-transformed polar codes, termed as deep polar codes. We first present a deep polar encoder that harnesses a series of multi-layered polar transformations with varying sizes. Our approach to…

Information Theory · Computer Science 2023-08-08 Geon Choi , Namyoon Lee

We recently proved threshold saturation for spatially coupled sparse superposition codes on the additive white Gaussian noise channel. Here we generalize our analysis to a much broader setting. We show for any memoryless channel that…

Information Theory · Computer Science 2016-03-16 Jean Barbier , Mohamad Dia , Nicolas Macris

The Gyrokinetic Toroidal Code at Princeton (GTC-P) is a highly scalable and portable particle-in-cell (PIC) code. It solves the 5D Vlasov-Poisson equation featuring efficient utilization of modern parallel computer architectures at the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-10-20 Bei Wang , Stephane Ethier , William Tang , Khaled Ibrahim , Kamesh Madduri , Samuel Williams , Leonid Oliker

In this paper, we propose a class of codes, referred to as random staircase generator matrix codes (SGMCs), which have staircase-like generator matrices. In the infinite-length region, we prove that the random SGMC is capacity-achieving…

Information Theory · Computer Science 2024-09-05 Qianfan Wang , Yiwen Wang , Yixin Wang , Jifan Liang , Xiao Ma

Convolutional sparse coding (CSC) has been popularly used for the learning of shift-invariant dictionaries in image and signal processing. However, existing methods have limited scalability. In this paper, instead of convolving with a…

Computer Vision and Pattern Recognition · Computer Science 2018-06-08 Yaqing Wang , Quanming Yao , James T. Kwok , Lionel M. Ni

This paper presents generalized channel coding theorems for a time-slotted distributed communication system where a transmitter-receiver pair is communicating in parallel with other transmitters. Assume that the channel code of each…

Information Theory · Computer Science 2016-11-15 Jie Luo