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In this paper we introduce a way to quantify the noise level associated to a given quantum transformation. The key mechanism lying at the heart of the proposal is "noise addition": in other words we compute the amount of extra noise we need…

Quantum Physics · Physics 2015-03-20 Antonella De Pasquale , Vittorio Giovannetti

This letter proposes superposing two Generalized Quadratic Noise Modulators (GQNM) by simply adding their outputs. It creates a 16-ary noise modulator that resembles QAM modulators in classical communication. It modulates the information…

Signal Processing · Electrical Eng. & Systems 2025-10-03 Hadi Zayyani , Mohammad Salman , Felipe A. P. de Figueiredo , Rausley A. A. de Souza

For the additive white Gaussian noise channel with average codeword power constraint, new coding methods are devised in which the codewords are sparse superpositions, that is, linear combinations of subsets of vectors from a given design,…

Information Theory · Computer Science 2010-06-21 Andrew R. Barron , Antony Joseph

A key competence for open-ended learning is the formation of increasingly abstract representations useful for driving complex behavior. Abstract representations ignore specific details and facilitate generalization. Here we consider the…

Machine Learning · Computer Science 2021-09-06 Charles Wilmot , Gianluca Baldassarre , Jochen Triesch

We consider the response of a memoryless nonlinear device that converts an input signal $\xi(t)$ into an output $\eta(t)$ that only depends on the value of the input at the same time, $t$. For input Gaussian noise with power spectrum…

Statistical Mechanics · Physics 2017-08-30 Avinash Chand Yadav , Ramakrishna Ramaswamy , Deepak Dhar

For a learning task, Gaussian process (GP) is interested in learning the statistical relationship between inputs and outputs, since it offers not only the prediction mean but also the associated variability. The vanilla GP however struggles…

Machine Learning · Statistics 2020-09-01 Haitao Liu , Yew-Soon Ong , Xiaomo Jiang , Xiaofang Wang

A general attenuator $\Phi_{\lambda, \sigma}$ is a bosonic quantum channel that acts by combining the input with a fixed environment state $\sigma$ in a beam splitter of transmissivity $\lambda$. If $\sigma$ is a thermal state the resulting…

Quantum Physics · Physics 2020-09-14 Ludovico Lami , Martin B. Plenio , Vittorio Giovannetti , Alexander S. Holevo

Lossy transmission over a relay channel in which the relay has access to correlated side information is considered. First, a joint source-channel decode-and-forward scheme is proposed for general discrete memoryless sources and channels.…

Information Theory · Computer Science 2016-11-17 Deniz Gunduz , Elza Erkip , Andrea J. Goldsmith , H. Vincent Poor

We consider the special case of index coding over the Gaussian broadcast channel where each receiver has prior knowledge of a subset of messages at the transmitter and demands all the messages from the source. We propose a concatenated…

Information Theory · Computer Science 2015-07-02 Lakshmi Natarajan , Yi Hong , Emanuele Viterbo

We establish the capacity of a class of communication channels introduced in [1]. The $n$-letter input from a finite alphabet is passed through a discrete memoryless channel $P_{Z|X}$ and then the output $n$-letter sequence is uniformly…

Information Theory · Computer Science 2023-10-30 Jennifer Tang , Yury Polyanskiy

We consider molecular communication, with information conveyed in the time of release of molecules. The main contribution of this paper is the development of a theoretical foundation for such a communication system. Specifically, we develop…

Information Theory · Computer Science 2016-11-17 K. V. Srinivas , Raviraj S. Adve , Andrew W. Eckford

Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise variance, channel reliability…

Information Theory · Computer Science 2007-07-13 Fredrik Brannstrom , Lars K. Rasmussen

In this paper, we consider single- and multi-user Gaussian channels with feedback under expected power constraints and with non-vanishing error probabilities. In the first of two contributions, we study asymptotic expansions for the…

Information Theory · Computer Science 2016-09-22 Lan V. Truong , Silas L. Fong , Vincent Y. F. Tan

We consider the problem of controlling an unstable scalar linear plant over a power-constrained additive white Gaussian noise (AWGN) channel, where the controller/receiver has access to an additional noisy measurement of the state of the…

Systems and Control · Electrical Eng. & Systems 2020-04-09 Omri Lev , Anatoly Khina

We reinterpret multiplicative noise in neural networks as auxiliary random variables that augment the approximate posterior in a variational setting for Bayesian neural networks. We show that through this interpretation it is both efficient…

Machine Learning · Statistics 2017-06-14 Christos Louizos , Max Welling

In this paper we introduce a novel performance analysis of the ${\eta}$-${\mu}$ generalized radio fading channels with integer value of the ${\mu}$ fading parameter, i.e. with even number of multipath clusters. This fading model includes…

Information Theory · Computer Science 2017-03-14 Ehab Salahat , Murad Qasaimeh

This study examines multilevel channel polarization for a certain class of erasure channels that the input alphabet size is an arbitrary composite number. We derive limiting proportions of partially noiseless channels for such a class. The…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Ken-ichi Iwata , Hiroshi Fujisaki

This paper considers the problem of the multiple-input multiple-output (MIMO) Gaussian broadcast channel with two receivers (receivers 1 and 2) and two messages: a common message intended for both receivers and a confidential message…

Information Theory · Computer Science 2016-11-17 Hung D. Ly , Tie Liu , Yingbin Liang

Neural networks readily learn a subset of the modular arithmetic tasks, while failing to generalize on the rest. This limitation remains unmoved by the choice of architecture and training strategies. On the other hand, an analytical…

Machine Learning · Computer Science 2024-06-06 Darshil Doshi , Tianyu He , Aritra Das , Andrey Gromov

In this work we show how an improved lower bound to the error exponent of the memoryless multiple-access (MAC) channel is attained via the use of linear codes, thus demonstrating that structure can be beneficial even in cases where there is…

Information Theory · Computer Science 2016-11-18 Eli Haim , Yuval Kochman , Uri Erez
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