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Regenerating codes (RCs) can significantly reduce the repair-bandwidth of distributed storage networks. Initially, the analysis of RCs was based on the assumption that during the repair process, the newcomer does not distinguish (among all…

Information Theory · Computer Science 2016-11-15 Imad Ahmad , Chih-Chun Wang

We propose a very low-complexity and high-performance algorithm for soft-demapping of multi-dimensional modulation formats. We assess its performance over the linear channel for four 8D formats, generated using binary arithmetics. This…

Information Theory · Computer Science 2019-04-30 Djalal F. Bendimerad , Huijian Zhang , Ingmar Land , Hartmut Hafermann

Determinant codes are a class of exact-repair regenerating codes for distributed storage systems with parameters (n, k = d, d). These codes cover the entire trade-off between per-node storage and repair-bandwidth. In an earlier work of the…

Information Theory · Computer Science 2021-01-18 Mehran Elyasi , Soheil Mohajer

In this paper, probabilistic shaping is numerically and experimentally investigated for increasing the transmission reach of wavelength division multiplexed (WDM) optical communication system employing quadrature amplitude modulation (QAM).…

We develop a theory of percolation with plasticity systems (PWPs) rendering properties of interest for neuromorphic computing. Unlike the standard percolation between two large electrodes, they have multiple ($N\gg 1$) interfaces and…

Disordered Systems and Neural Networks · Physics 2020-05-05 V. G. Karpov , G. Serpen , Maria Patmiou

Permutation codes in the Ulam metric, which can correct multiple deletions, have been investigated extensively recently. In this work, we are interested in the maximum size of permutation codes in the Ulam metric and aim to design…

Information Theory · Computer Science 2024-12-11 Shuche Wang , The Nguyen , Yeow Meng Chee , Van Khu Vu

In many areas of engineering, nonlinear numerical analysis is playing an increasingly important role in supporting the design and monitoring of structures. Whilst increasing computer resources have made such formerly prohibitive analyses…

Numerical Analysis · Mathematics 2020-07-02 Thomas Simpson , Nikolaos Dervilis , Eleni Chatzi

It is shown that a class of optical physical unclonable functions (PUFs) can be learned to arbitrary precision with arbitrarily high probability, even in the presence of noise, given access to polynomially many challenge-response pairs and…

Machine Learning · Computer Science 2023-09-08 Apollo Albright , Boris Gelfand , Michael Dixon

Unsupervised machine learning methods can be of great help in many traditional engineering disciplines, where huge amount of labeled data is not readily available or is extremely difficult or costly to generate. Two specific examples…

Machine Learning · Computer Science 2020-07-21 Raj Kishore , Zohar Nussinov , Kisor Kumar Sahu

A malleable coding scheme considers not only compression efficiency but also the ease of alteration, thus encouraging some form of recycling of an old compressed version in the formation of a new one. Malleability cost is the difficulty of…

Information Theory · Computer Science 2008-07-01 Lav R. Varshney , Julius Kusuma , Vivek K Goyal

In this paper, we study a class of spatially coupled turbo codes, namely partially information- and partially parity-coupled turbo codes. This class of codes enjoy several advantages such as flexible code rate adjustment by varying the…

Information Theory · Computer Science 2020-12-25 Min Qiu , Xiaowei Wu , Alexandre Graell i Amat , Jinhong Yuan

We investigate the problem of delay-efficient and reliable data delivery in ultra-dense networks (UDNs) that constitute macro base stations (MBSs), small base stations (SBSs), and mobile users. Considering a two-hop data delivery system, we…

Information Theory · Computer Science 2020-08-27 Luyao Shang , Morteza Hashemi , Taejoon Kim , Erik Perrins

The number of neurons that can be simultaneously recorded doubles every seven years. This ever increasing number of recorded neurons opens up the possibility to address new questions and extract higher dimensional stimuli from the…

Neurons and Cognition · Quantitative Biology 2018-04-27 Anna Kutschireiter , Jean-Pascal Pfister

Physics-Informed Neural Networks (PINNs) are a useful framework for approximating partial differential equation solutions using deep learning methods. In this paper, we propose a principled redesign of the PINNsformer, a Transformer-based…

Machine Learning · Computer Science 2025-10-08 Rohan Arni , Carlos Blanco

In this work we explore possibilities for coding and decoding tailor-made for mean squared error evaluation of error in contexts such as image transmission. To do so, we introduce a loss function that expresses the overall performance of a…

Information Theory · Computer Science 2014-11-06 Marcelo Firer , Luciano Panek , Jerry Anderson Pinheiro

Machine learning has enabled differential cross section measurements that are not discretized. Going beyond the traditional histogram-based paradigm, these unbinned unfolding methods are rapidly being integrated into experimental workflows.…

High Energy Physics - Phenomenology · Physics 2025-05-28 Ryan Milton , Vinicius Mikuni , Trevin Lee , Miguel Arratia , Tanvi Wamorkar , Benjamin Nachman

Weak physical uncloneable function (WPUF) encryption key means that the manufacturer of the hardware can clone the key but anybody else is unable to so that. Strong physical uncloneable function (SPUF) encryption key means that even the…

Cryptography and Security · Computer Science 2013-12-18 Laszlo B. Kish , Chiman Kwan

We address the problem of multipermutation code design in the Ulam metric for novel storage applications. Multipermutation codes are suitable for flash memory where cell charges may share the same rank. Changes in the charges of cells…

Information Theory · Computer Science 2013-12-10 Farzad Farnoud , Olgica Milenkovic

Nowadays, pre-trained encoders are widely used in medical image segmentation due to their strong capability in extracting rich and generalized feature representations. However, existing methods often fail to fully leverage these features,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Xiaolin Gou , Chuanlin Liao , Jizhe Zhou , Fengshuo Ye , Yi Lin

Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in biometric recognition…

Machine Learning · Computer Science 2023-02-20 Mahdi Ghafourian , Julian Fierrez , Ruben Vera-Rodriguez , Aythami Morales , Ignacio Serna