Results 41 to 50 of about 737,076 (296)
Research of fast decoding for longer constraint length convolutional codes
To overcome the disadvantage of Viterbi decoding algorithm, in which its complexity exponentially increases with the increasing constraint length of convolutional codes, and the decoding delay was too large to fit the decoding of longer constraint length
HUANG Xiao-ling, YANG Hua-long
doaj +2 more sources
A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source
Unified quantum convolutional coding [PDF]
We outline a quantum convolutional coding technique for protecting a stream of classical bits and qubits. Our goal is to provide a framework for designing codes that approach the ``grandfather'' capacity of an entanglement-assisted quantum channel for sending classical and quantum information simultaneously.
Mark M. Wilde, Todd A. Brun
openaire +3 more sources
Near-capacity iterative decoding of binary self-concatenated codes using soft decision demapping and 3-D EXIT charts [PDF]
In this paper 3-D Extrinsic Information Transfer (EXIT) charts are used to design binary Self-Concatenated Convolutional Codes employing Iterative Decoding (SECCC-ID), exchanging extrinsic information with the soft-decision demapper to approach the ...
Butt, Muhammad Fasih +3 more
core +1 more source
In this paper, we characterize the achievable performance of a wavelet encoding-based videophone system, which further compresses and protects the wavelet-based video codec's bit-stream with the aid of Reversible Variable-Length (RVLC) codes.
Pham, A.Q. +7 more
core +2 more sources
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Summary: This paper describes a class of infinite convolution codes which are designed to minimize the time required to recover from an erasure burst on the binary erasure channel. It is shown that for any given rate, there exists a unique optimum erasure burst correcting code.
openaire +1 more source
Arikan's Polar codes attracted much attention as the first efficiently decodable and capacity achieving codes. Furthermore, Polar codes exhibit an exponentially decreasing block error probability with an asymptotic error exponent upper bounded by 1/2. Since their discovery, many attempts have been made to improve the error exponent and the finite block-
Andrew James Ferris +2 more
openaire +2 more sources
Artificial neural networks can solve various tasks in computer vision, such as image classification, object detection, and general recognition.
Ladislav Karrach, Elena Pivarčiová
doaj +1 more source
Rate-compatible LDPC convolutional codes over non-gaussian noise channel [PDF]
This paper is aimed to study the characteristics of the underwater acoustic channel with non-Gaussian noise channel. And Gaussian mixture model (GMM) is utilized to fit the background noise over the non-Gaussian noise channel.
Liu Qiang
doaj +1 more source

