惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Martin Fowler
Martin Fowler
D
DataBreaches.Net
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
The GitHub Blog
The GitHub Blog
Blog — PlanetScale
Blog — PlanetScale
Microsoft Security Blog
Microsoft Security Blog
A
About on SuperTechFans
Vercel News
Vercel News
L
LangChain Blog
B
Blog RSS Feed
Y
Y Combinator Blog
IT之家
IT之家
H
Hackread – Cybersecurity News, Data Breaches, AI and More
GbyAI
GbyAI
V
V2EX
博客园 - 三生石上(FineUI控件)
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
阮一峰的网络日志
阮一峰的网络日志
有赞技术团队
有赞技术团队
D
Docker
V
Visual Studio Blog
aimingoo的专栏
aimingoo的专栏
Last Week in AI
Last Week in AI
月光博客
月光博客

cs.IT updates on arXiv.org

Theoretical Limits of Language Model Alignment $f$-Divergence Regularized RLHF: Two Tales of Sampling and Unified Analyses A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation When Semantic Communication Meets Queueing: Cross-Layer Latency and Task Fidelity Optimization Convexity in Disguise: A Theoretical Framework for Nonconvex Low-Rank Matrix Estimation Conditional Diffusion Under Linear Constraints: Langevin Mixing and Information-Theoretic Guarantees Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval Expert Routing for Communication-Efficient MoE via Finite Expert Banks Contextual Memory-Enhanced Source Coding for Low-SNR Communications Realizable Bayes-Consistency for General Metric Losses Leveraging Code Automorphisms for Improved Syndrome-Based Neural Decoding A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy Optimization of CV-QKD Under Practical Constraints Benchmarking Wireless Representations: High-Dimensional vs. Compressed Embeddings for Efficiency and Robustness Real-Time Text Transmission via LLM-Based Entropy Coding over Fixed-Rate Channels SwiftChannel: Algorithm-Hardware Co-Design for Deep Learning-Based 5G Channel Estimation Evolving Token Communication with Parametric Memory Network Remote Action Generation: Remote Control with Minimal Communication The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation Linear-Readout Floors and Threshold Recovery in Computation in Superposition Soft Graph Diffusion Transformer for MIMO Detection Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design Exponential families from a single KL identity MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness Diffusion-OAMP for Joint Image Compression and Wireless Transmission Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Improving the Finite-Length Performance of Spatially Coup...
Pablo M. Olmos, David G. M. Mitchell, Dmitri Truhachev, Daniel J · 2014-02-28 · via cs.IT updates on arXiv.org

In this paper, we analyze the finite-length performance of codes on graphs constructed by connecting spatially coupled low-density parity-check (SC-LDPC) code chains. Successive (peeling) decoding is considered for the binary erasure channel (BEC). The evolution of the undecoded portion of the bipartite graph remaining after each iteration is analyzed as a dynamical system. When connecting short SC-LDPC chains, we show that, in addition to superior iterative decoding thresholds, connected chain ensembles have better finite-length performance than single chain ensembles of the same rate and length. In addition, we present a novel encoding/transmission scheme to improve the performance of a system using long SC-LDPC chains, where, instead of transmitting codewords corresponding to a single SC-LDPC chain independently, we connect consecutive chains in a multi-layer format to form a connected chain ensemble. We refer to such a transmission scheme to as continuous chain (CC) transmission of SC-LDPC codes. We show that CC transmission can be implemented with no significant increase in encoding/decoding complexity or decoding delay with respect a system using a single SC-LDPC code chain for encoding.