18 papers · ranked by Valyu relevance
Niklas Gassner, Julia Lieb, Abhinaba Mazumder, Michael Schaller
In this paper, we present a framework for generic decoding of convolutional codes, which allows us to do cryptanalysis of code-based systems that use convolutional codes as public keys. We then apply this framework to information set decoding, study success probabilities and give tools to choose variables. Finally, we…
Martin Bossert, Rebekka Schulz, Sebastian Bitzer
—The binary primitive BCH codes are cyclic and are constructed by choosing a subset of the cyclotomic cosets. Which subset is chosen determines the dimension, the minimum distance and the weight distribution of the BCH code. We construct possible BCH codes and determine their coderate, true minimum distance and the…
Sarah Anhala Cepeda-Humerez, Jakob Ruess, Gašper Tkačik, Alexandre V. Morozov
'Alexandre V. Morozov'] Across diverse biological systems-ranging from neural networks to intracellular signaling and genetic regulatory networks-the information about changes in the environment is frequently encoded in the full temporal dynamics of the network nodes. A pressing data-analysis challenge has thus been to…
Jia Lu, Ryan Tsoi, Nan Luo, Yuanchi Ha + 8 more
Dynamical systems often generate distinct outputs according to different initial conditions, and one can infer the corresponding input configuration given an output. This property captures the essence of information encoding and decoding. Here, we demonstrate the use of self-organized patterns, combined with machine…
Marcelo Firer, Luciano Panek, Jerry Anderson Pinheiro
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 coding and decoding scheme for discrete channels and that exchanges the usual…
Ilya Dumer
Successive cancellation (SC) decoding was considered in [1] for general Reed-Muller codes RM(r, m) of order r and dimension m. It was also proposed in [1] to set to zeros those information bits that are the least protected in SC decoding. Simulation results of [1] show that the resulting subcodes with frozen bits…
David Kracht, Steffen Schober
Background Barcode multiplexing is a key strategy for sharing the rising capacity of next-generation sequencing devices: Synthetic DNA tags, called barcodes, are attached to natural DNA fragments within the library preparation procedure. Different libraries, can individually be labeled with barcodes for a joint…
Jan Lewandowsky, Gerhard Bauch, Maximilian Stark, Jerry D. Gibson
Digital communication receivers extract information about the transmitted data from the received signal in subsequent processing steps, such as synchronization, demodulation and channel decoding. Technically, the receiver-side signal processing for conducting these tasks is complex and hence causes bottleneck…
Julia Lieb, Joachim Rosenthal
In this paper, we employ the linear systems representation of a convolutional code to develop a decoding algorithm for convolutional codes over the erasure channel. We study the decoding problem using the state space description and this provides in a natural way additional information. With respect to previously known…
Edgar Beck, Carsten Bockelmann, Armin Dekorsy, Changchuan Yin
Motivated by the recent success of Machine Learning (ML) tools in wireless communications, the idea of semantic communication by Weaver from 1949 has gained attention. It breaks with Shannon’s classic design paradigm by aiming to transmit the meaning of a message, i.e., semantics, rather than its exact version and…
Authors not listed
Quantum state tomography has been widely used to reconstruct the quantum state of a system from a set of informationally-complete measurements. Obtaining enough information about, e.g., the wavefunction of a molecule allows its complete characterization. On the other hand, deep learning models for molecular property…
Gabriel Matías Lorenz, Nicola M. Engel, Marco Celotto, Loren Kocillari + 3 more
Information theory has deeply influenced the conceptualization of brain information processing and is a mainstream framework for analyzing how neural networks in the brain process information to generate behavior. Information theory tools have been initially conceived and used to study how information about sensory…
Dor Tsur, Haim Permuter, Kichun Lee
Despite the widespread use of information measures in analyzing probabilistic systems, effective visualization tools for understanding complex dependencies in sequential data are scarce. In this work, we introduce the information matrix (InfoMat), a novel and intuitive matrix representation of information transfer in…
Roberto Maffulli, Miguel A. Casal, Marco Celotto, Stefano Zucca + 3 more
Information theory provides a popular and principled framework for the analysis of neural data. It allows to uncover in an assumption-free way how neurons encode and transmit information, capturing both linear and non-linear coding mechanisms and including the information carried by interactions of any order. To…
Julie E. Elie, Frédéric E. Theunissen
Although information theoretic approaches have been used extensively in the analysis of the neural code, they have yet to be used to describe how information is accumulated in time while sensory systems are categorizing dynamic sensory stimuli such as speech sounds or visual objects. Here, we present a novel method to…
Michail Gkagkos, Charalambos D. Charalambous, Eduard Jorswieck
The main focus of this paper is the derivation of the structural properties of the test channels of Wyner’s operational information rate distortion function (RDF), $R¯(Δ_{X})$, for arbitrary abstract sources and, subsequently, the derivation of additional properties for a tuple of multivariate correlated, jointly…
Xinhao Fan, Shreesh P Mysore
A cornerstone of our understanding of both biological and artificial neural networks is that they store information in the strengths of connections among the constituent neurons. However, in contrast to the well-established theory for quantifying information encoded by the firing patterns of neural networks, little is…
Victor H. R. Nogueira, Rishabh Sharma, Rafael V. C. Guido, Michael J. Keiser
As efforts to improve the robustness of molecular representations advance, so does the need for methods to test and validate them. We use a Variational Auto-Encoder (VAE), an unsupervised deep learning model, to generate anomalous samples of a well-known molecular string format called SELF-referencIng Embedded Strings…