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Departing from traditional communication theory where decoding algorithms are assumed to perform without error, a system where noise perturbs both computational devices and communication channels is considered here. This paper studies…

Information Theory · Computer Science 2010-05-31 Lav R. Varshney

For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by…

Information Theory · Computer Science 2010-06-22 Andrew R Barron , Antony Joseph

The pivotal storage density win achieved by solid-state devices over magnetic devices recently is a result of multiple innovations in physics, architecture, and signal processing. Constrained coding is used in Flash devices to increase…

Information Theory · Computer Science 2023-11-15 Ahmed Hareedy , Simeng Zheng , Paul Siegel , Robert Calderbank

The inclusion of a macroscopic adaptive threshold is studied for the retrieval dynamics of both layered feedforward and fully connected neural network models with synaptic noise. These two types of architectures require a different method…

Disordered Systems and Neural Networks · Physics 2007-08-03 D. Bolle , R. Heylen

A prescription to calculate the minimum number of bits needed for binary strip detector readout is presented. This permits a systematic analysis of the readout efficiency relative to this theoretical minimum number of bits. Different level…

Instrumentation and Detectors · Physics 2015-06-17 Maurice Garcia-Sciveres , Xinkang Wang

Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm that can be used to perform maximum likelihood decoding. It attempts to find the errors introduced by the channel by generating a sequence of possible error…

Information Theory · Computer Science 2022-07-26 Carlo Condo

This work investigates a new erase scheme in NAND flash memory to improve the lifetime and performance of modern solid-state drives (SSDs). In NAND flash memory, an erase operation applies a high voltage (e.g., > 20 V) to flash cells for a…

Hardware Architecture · Computer Science 2024-04-17 Sungjun Cho , Beomjun Kim , Hyunuk Cho , Gyeongseob Seo , Onur Mutlu , Myungsuk Kim , Jisung Park

With the rapid advancements of deep learning in recent years, hardware accelerators are continuously deployed in more and more safety-critical applications such as autonomous driving and robotics. While the accelerators are usually…

Hardware Architecture · Computer Science 2023-08-31 Zuodong Zhang , Renjie Wei , Meng Li , Yibo Lin , Runsheng Wang , Ru Huang

Superchannels leverage the flexibility of elastic optical networks and pave the way to higher capacity channels in space division multiplexing (SDM) networks. A superchannel consists of subchannels to which continuous spectral grid slots…

Neural Machine Translation (NMT) currently exhibits biases such as producing translations that are too short and overgenerating frequent words, and shows poor robustness to copy noise in training data or domain shift. Recent work has tied…

Computation and Language · Computer Science 2021-05-19 Mathias Müller , Rico Sennrich

As DNA data storage moves closer to practical deployment, minimizing sequencing coverage depth is essential to reduce both operational costs and retrieval latency. This paper addresses the recently studied Random Access Problem, which…

Information Theory · Computer Science 2026-01-13 Chen Wang , Eitan Yaakobi

Quantum error correction requires decoders that are both accurate and efficient. To this end, union-find decoding has emerged as a promising candidate for error correction on the surface code. In this work, we benchmark a weighted variant…

Quantum Physics · Physics 2020-07-22 Shilin Huang , Michael Newman , Kenneth R. Brown

Guessing random additive noise decoding (GRAND) is a maximum likelihood (ML) decoding method that identifies the noise effects corrupting code-words of arbitrary code-books. In a joint detection and decoding framework, this work…

Information Theory · Computer Science 2023-04-18 Hadi Sarieddeen , Muriel Médard , Ken. R. Duffy

Label-noise learning (LNL) aims to increase the model's generalization given training data with noisy labels. To facilitate practical LNL algorithms, researchers have proposed different label noise types, ranging from class-conditional to…

Machine Learning · Computer Science 2024-02-13 Jingfeng Zhang , Bo Song , Haohan Wang , Bo Han , Tongliang Liu , Lei Liu , Masashi Sugiyama

The current flash memory technology focuses on the cost minimization of its static storage capacity. However, the resulting approach supports a relatively small number of program-erase cycles. This technology is effective for consumer…

Information Theory · Computer Science 2015-01-05 Eyal En Gad , Eitan Yaakobi , Anxiao , Jiang , Jehoshua Bruck

We investigate error propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit error rate (BER)…

Information Theory · Computer Science 2020-04-30 Min Zhu , David G. M. Mitchell , Michael Lentmaier , Daniel J. Costello, , Baoming Bai

In this paper, we propose a simple, fast decoding algorithm that fosters diversity in neural generation. The algorithm modifies the standard beam search algorithm by adding an inter-sibling ranking penalty, favoring choosing hypotheses from…

Computation and Language · Computer Science 2016-12-23 Jiwei Li , Will Monroe , Dan Jurafsky

Compared to planar (i.e., two-dimensional) NAND flash memory, 3D NAND flash memory uses a new flash cell design, and vertically stacks dozens of silicon layers in a single chip. This allows 3D NAND flash memory to increase storage density…

Hardware Architecture · Computer Science 2018-11-13 Yixin Luo , Saugata Ghose , Yu Cai , Erich F. Haratsch , Onur Mutlu

We show that a simple modification of the surface code can exhibit an enormous gain in the error correction threshold for a noise model in which Pauli Z errors occur more frequently than X or Y errors. Such biased noise, where dephasing…

Quantum Physics · Physics 2018-02-07 David K. Tuckett , Stephen D. Bartlett , Steven T. Flammia

The highest current estimates for the amount of noise a quantum computer can tolerate are based on fault-tolerance schemes relying heavily on postselecting on no detected errors. However, there has been no proof that these schemes give even…

Quantum Physics · Physics 2012-06-22 Ben W. Reichardt