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A method for efficiently constructing polar codes is presented and analyzed. Although polar codes are explicitly defined, straightforward construction is intractable since the resulting polar bit-channels have an output alphabet that grows…

Information Theory · Computer Science 2013-04-11 Ido Tal , Alexander Vardy

Polarization-adjusted convolutional (PAC) codes were recently proposed and arouse the interest of the channel coding community because they were shown to approach theoretical bounds for the (128,64) code size. In this letter, we propose…

Information Theory · Computer Science 2020-11-09 Thibaud Tonnellier , Warren J. Gross

Polar codes have attracted much recent attention as the first codes with low computational complexity that provably achieve optimal rate-regions for a large class of information-theoretic problems. One significant drawback, however, is that…

Information Theory · Computer Science 2010-01-15 Mayank Bakshi , Sidharth Jaggi , Michelle Effros

The construction of polar codes for channels other than BECs requires sorting of all bit channels and then selecting the best $K$ of them for a block length $N=2^n$. In this paper, two types of partial orders (PO) of polar codes are…

Information Theory · Computer Science 2017-04-25 Wei Wang , Liping Li

Reed Muller (RM) codes are known for their good minimum distance. One can use their structure to construct polar-like codes with good distance properties by choosing the information set as the rows of the polarization matrix with the…

Information Theory · Computer Science 2022-04-15 Samet Gelincik , Philippe Mary , Anne Savard , Jean-Yves Baudais

Multi-kernel polar codes have recently been proposed to construct polar codes of lengths different from powers of two. Decoder implementations for multi-kernel polar codes need to account for this feature, that becomes critical in memory…

Information Theory · Computer Science 2018-09-26 Valerio Bioglio , Carlo Condo , Ingmar Land

We consider the problem of using polar codes over slow fading wireless channels. For design, we focus on a parallel slow fading channel with 2 blocks, and polar codes with rate <= 1/2. Motivated by Arikan's systematic polar code…

Information Theory · Computer Science 2016-10-18 Saurabha R Tavildar

Polar codes are a family of capacity-achieving codes that have explicit and low-complexity construction, encoding, and decoding algorithms. Decoding of polar codes is based on the successive-cancellation decoder, which decodes in a bit-…

Information Theory · Computer Science 2018-03-06 Boaz Shuval , Ido Tal

A concatenated coding scheme over binary memoryless symmetric (BMS) channels using a polarization transformation followed by outer sub-codes is analyzed. Achievable error exponents and upper bounds on the error rate are derived. The first…

Information Theory · Computer Science 2017-10-24 Dina Goldin , David Burshtein

In the framework of computational complexity and in an effort to define a more natural reduction for problems of equivalence, we investigate the recently introduced kernel reduction, a reduction that operates on each element of a pair…

Computational Complexity · Computer Science 2016-04-29 Jeffrey Finkelstein , Benjamin Hescott

An algorithm is presented for approximating a single-user channel with a prime input alphabet size. The result is an upgraded version of the channel with a reduced output alphabet size. It is shown that this algorithm can be used to reduce…

Information Theory · Computer Science 2013-05-06 Arash Ghayoori , T. Aaron Gulliver

A method is proposed, called channel polarization, to construct code sequences that achieve the symmetric capacity $I(W)$ of any given binary-input discrete memoryless channel (B-DMC) $W$. The symmetric capacity is the highest rate…

Information Theory · Computer Science 2016-11-18 Erdal Arikan

Polar codes have received growing attention in the past decade and have been selected as the coding scheme for the control channel in the fifth generation (5G) wireless communication systems. However, the conventional polar codes have only…

Information Theory · Computer Science 2023-01-26 Hossein Rezaei , Nandana Rajatheva , Matti Latva-aho

Most blind deconvolution methods usually pre-define a large kernel size to guarantee the support domain. Blur kernel estimation error is likely to be introduced, yielding severe artifacts in deblurring results. In this paper, we first…

Computer Vision and Pattern Recognition · Computer Science 2019-02-25 Li Si-Yao , Dongwei Ren , Qian Yin

Kernel approximation methods create explicit, low-dimensional kernel feature maps to deal with the high computational and memory complexity of standard techniques. This work studies a supervised kernel learning methodology to optimize such…

Machine Learning · Computer Science 2020-02-17 Mert Al , Zejiang Hou , Sun-Yuan Kung

Kernel means are frequently used to represent probability distributions in machine learning problems. In particular, the well known kernel density estimator and the kernel mean embedding both have the form of a kernel mean. Unfortunately,…

Machine Learning · Statistics 2015-03-03 E. Cruz Cortés , C. Scott

The polarization process of polar codes over a ternary alphabet is studied. Recently it has been shown that the scaling of the blocklength of polar codes with prime alphabet size scales polynomially with respect to the inverse of the gap…

Information Theory · Computer Science 2015-02-11 Dina Goldin , David Burshtein

We introduce a new family of polar-like codes, called Partially Polarized Polar (PPP) codes. PPP codes are constructed from conventional polar codes by selectively pruning polarization kernels, thereby modifying the synthesized bit-channel…

Information Theory · Computer Science 2026-01-23 Arman Fazeli , Mohammad M. Mansour , Ziyuan Zhu , Louay Jalloul

In this paper we propose a new framework for analyzing the performance of preprocessing algorithms. Our framework builds on the notion of kernelization from parameterized complexity. However, as opposed to the original notion of…

Data Structures and Algorithms · Computer Science 2016-11-07 Daniel Lokshtanov , Fahad Panolan , M. S. Ramanujan , Saket Saurabh

A well-recognized limitation of kernel learning is the requirement to handle a kernel matrix, whose size is quadratic in the number of training examples. Many methods have been proposed to reduce this computational cost, mostly by using a…

Machine Learning · Computer Science 2014-11-06 Nicolò Cesa-Bianchi , Yishay Mansour , Ohad Shamir