Results 101 to 110 of about 74,220 (257)
Construction of LDPC codes for higher burst-error detecting
Tongxin xuebao, 2007 The coding of LDPC codes is focused on several aspects: high error-correction,low coding complexity and so on.All the construction methods do not give much consideration on hamming-distance and its distribution because of computation complexity.A ...
YAO Chun-guang1 +3 more
doaj +2 more sources
Assessment of minimum distances of non-primitive Hamming codes
Весці Нацыянальнай акадэміі навук Беларусі: Серыя фізіка-тэхнічных навук, 2016 It is proved that under certain conditions, non-primitive Hamming codes are quadratic residue codes, and can be at arbitrarily large minimum distance. Therefore, unlike primitive Hamming codes without decoding the primitive have unlimited possibilities.
V. A. Lipnitsky, A. O. Aliaksiuk
doaj
Advanced Intelligent Discovery, EarlyView.Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren +10 more
wiley +1 more source
Distance-two labellings of Hamming graphs
Discrete Applied Mathematics, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chang, G. J., Lu, C., Zhou, S.
openaire +2 more sources
Harnessing Phase Dynamics Across Diverse Frequencies with Multifrequency Oscillatory Neural Networks
Advanced Intelligent Discovery, EarlyView.Oscillatory Neural Networks (ONNs) are an emerging computing paradigm that encodes information in the phases of coupled oscillators. Traditionally, ONNs have been investigated using homogeneous frequency oscillators. However, physical hardware implementations are inherently subject to frequency mismatches, device variability, and nonuniformities.
Nil Dinç +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Constructing DNA Codes with Larger Distance from Quaternary Words
Jambura Journal of MathematicsIn this work, we propose a novel method to construct DNA codes from quaternary words. The method uses permutation groups that act in the set {1, 2, …, 4n}, representing the coordinate and coordinate value of quaternary words.
Benediktus Panji Pradipta +1 more
doaj +1 more source
Undetected error probability and throughput analysis of a concatenated coding scheme [PDF]
The performance of a proposed concatenated coding scheme for error control on a NASA telecommand system is analyzed. In this scheme, the inner code is a distance-4 Hamming code used for both error correction and error detection.
Costello, D. J.
core +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Advanced Intelligent Systems, EarlyView.Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source