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

S
SegmentFault 最新的问题
博客园 - 三生石上(FineUI控件)
爱范儿
爱范儿
博客园 - 聂微东
V
Visual Studio Blog
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
M
MIT News - Artificial intelligence
The GitHub Blog
The GitHub Blog
Recent Announcements
Recent Announcements
有赞技术团队
有赞技术团队
L
LangChain Blog
I
InfoQ
T
Tailwind CSS Blog
博客园 - 【当耐特】
V
V2EX
博客园_首页
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
GbyAI
GbyAI
Vercel News
Vercel News
雷峰网
雷峰网
量子位
A
About on SuperTechFans
Martin Fowler
Martin Fowler
H
Help Net Security

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
New Capacity Upper Bounds For Binary Deletion Channel
[Submitted on 7 Feb 2021 (v1), last revised 22 Jul 2026 (this ve · 2021-02-08 · via cs.IT updates on arXiv.org

View PDF HTML (experimental)

Abstract:This paper considers a binary channel with deletions. We derive two closed-form upper bounds on the capacity of the binary deletion channel (BDC). The first bound is obtained by computing the capacity of an auxiliary channel, the two-bit Fixed-length-Input BDC (FI-BDC), and showing that this auxiliary capacity upper-bounds the capacity of the BDC. The second bound is obtained by approximating the mutual information between sent and received bits directly, yielding a closed-form expression parameterized by a first-order Markov correlation parameter $\gamma$. Both bounds use a first-order Markov process for the channel input. We verify Theorem~1's optimization from first principles, directly from the two-bit auxiliary channel's transition matrix rather than from the mutual-information expression alone: the underlying objective is strictly concave with a unique interior maximizer, and the resulting closed-form bound is confirmed correct. The second proposed upper bound is evaluated against the Fertonani--Duman and Dalai bounds in Fig.~4.

Submission history

From: Hassan Tavakoli Dr [view email]
[v1] Sun, 7 Feb 2021 19:06:45 UTC (318 KB)
[v2] Wed, 22 Jul 2026 20:54:52 UTC (10 KB)