Results 141 to 150 of about 4,215 (309)

Characterization of a Class of Error Correcting Frames for Robust Signal Transmission over Wireless Communication Channels

open access: yesEURASIP Journal on Advances in Signal Processing, 2005
Joint source-channel coding has been introduced recently as an element of QoS support for IP-based wired and wireless multimedia. Indeed, QoS provisioning in a global mobility context with highly varying channel characteristics is all the most ...
Rath Gagan, Guillemot Christine
doaj   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

open access: yesAdvanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong   +5 more
wiley   +1 more source

Performance Analysis of Coded $M$-ary Orthogonal Signaling Using Errors-and Erasures Decoding Over Frequency-Selective Fading Channels

open access: yes, 2001
The performance of $M$-ary orthogonal signaling schemes employing Reed–Solomon (RS) codes and redundant residue number system (RRNS) codes is investigated over frequency-selective Rayleigh fading channels.
Yang, L-L., Hanzo, L.
core  

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

open access: yesAdvanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal   +6 more
wiley   +1 more source

The n-shot classical capacity of the quantum erasure channel

open access: yesJournal of Physics Communications
We compute the n -shot classical capacity of the quantum erasure channel, providing upper bounds and almost-matching lower bounds for it, the latter achievable via large-minimum-distance classical linear codes for any n .
Matteo Rosati
doaj   +1 more source

A Lower Bound on the Success Probability of Binary Random Linear Network Codes Aided by Noise Decoding

open access: yesIEEE Open Journal of the Communications Society
The decoding of binary random linear codes for packet erasures relies on receivers collecting a sufficient number of error-free coded packets for the reconstruction of a transmitted message.
Ioannis Chatzigeorgiou
doaj   +1 more source

A Reed-Solomon Coded DS-CDMA System Using Noncoherent M-ary Orthogonal Modulation over Multipath Fading Channels

open access: yes, 2000
The performance of Reed–Solomon (RS) coded direct-sequence code division multiple-access (DS-CDMA) systems using noncoherent M-ary orthogonal modulation is investigated over multipath Rayleigh fading channels.
Yang, L-L., Hanzo, L., Yen, K.
core  

Erasure correcting codes for high-throughput optical ground-to-satellite links

open access: yes
Optical satellite links provide increased throughput at a more competitive SWaP compared to radio frequency links. Due to the nature of the light interaction with atmosphere and the limited pointing accuracy, the propagated optical signal suffers from ...
Poliak, Juraj   +7 more
core   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

open access: yesAdvanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison   +4 more
wiley   +1 more source

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