21 papers · ranked by Valyu relevance
Mark Braverman, Zhou He
The network coding problem asks whether data throughput in a network can be increased using coding (compared to treating bits as commodities in a flow). While it is well-known that a network coding advantage exists in directed graphs, the situation in undirected graphs is much less understood – in particular, despite…
Qin Zhou, Fang-Wei Fu
This paper investigates the minimum field size required for network maximum distance separable (MDS) codes, a critical parameter affecting computational complexity at network nodes. Focusing on generalized combination networks and Zosin Khuller networks, we develop a systematic framework for both scalar and vector…
Vipindev Adat Vasudevan, Homa Esfahanizadeh, Benjamin D. Kim, Laura Landon + 2 more
—Modern 5G communication systems implement a combination of error correction and feedback-based erasure correction (HARQ/ARQ) as reliability mechanisms, which can introduce substantial delay and resource inefficiency. We propose forward erasure correction using network coding as a more delayefficient alternative. We…
Sirui Liu, Li Que, Zongpeng Li, Baochun Li
Network coding allows intermediate nodes to encode received messages before transmission. The multiple-unicast conjecture asserts that coding has no throughput advantage over fractional routing for independent unicast sessions in any undirected network. Despite more than two decades of sustained study, this central…
Yongpeng Wu, Peihong Yuan
Channel coding has long stood at the core of reliable communications, shaping the evolution of modern information and communication systems. From classical algebraic codes to capacity-approaching schemes such as Turbo codes, low-density parity-check (LDPC) codes, and polar codes, decades of research have continuously…
Jirui Liu, Longsheng Jiang, Xueting Li, Jiamin Wu + 1 more
Efficient coding is essential for sensory systems to extract meaningful information from the environment. Here, we investigate how stimulus-driven thermodynamic shifts and geometric reorganization enable efficient population coding. Using wide-field calcium imaging, we simultaneously recorded neuronal activity across…
Kai Huang, Xinyu Xie, Chunpeng Chen, Wenjie Guan + 2 more
In this paper, we aim to explore the stochastic performance limit of large-field-size Random Linear Streaming Codes (RLSCs) in multi-hop relay networks. In our model, a source transmits a sequence of streaming messages to a destination through multiple relays subject to a delay constraint. Most previous research…
Zhipeng Li, Wenjie Ma
—This paper investigates streaming codes for threenode relay networks under burst packet erasures with a delay constraint T. In any sliding window of T + 1 consecutive packets, the source-to-relay and relay-to-destination channels may introduce burst erasures of lengths at most b 1 and b2, respectively. Let u = max{b1…
Arthur Prat-Carrabin, Maximilian V. Harl, Samuel J. Gershman
As the statistics of sensory environments often change, neural sensory systems must adapt to maintain useful representations. Efficient coding prescribes that neuronal tuning curves should be optimized to the prior, but whether they can adapt rapidly is unclear. Empirically, tuning curves after repeated stimulus…
Fatih Dinc, Marta Blanco-Pozo, David Klindt, Francisco Acosta + 8 more
Many neural recordings have revealed low-dimensional sets of behaviorally relevant variables encoded within large-scale neural activity patterns. However, dimensionality reduction analyses alone cannot yield causal explanations for how networks stably implement computations that are resilient to the substantial…
Nigel Crook, Alexander D. Rast, Eleni Elia, Mario Antoine Aoun
Introduction In this work, we introduce a novel approach to one of the historically fundamental questions in neural networks: how to encode information? More particularly, we look at temporal coding in spiking networks, where the timing of a spike as opposed to the frequency, determines the information content. In…
Bharat Singhal, István Z Kiss, Jr-Shin Li, Derek Abbott
Decoding the connectivity patterns of complex networks from time series measurements is crucial for understanding and controlling their dynamics. Although network inference algorithms have advanced significantly in identifying both pairwise and higher-order interactions, they often rely on the availability of…
Yuhang Wang, Weihua Chen, Linjing Song, Zhiping Xu + 6 more
With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high-efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two-stage framework with high computational complexity and frequently struggle to…
Lihong Cao
The human brain encodes a virtually infinite repertoire of semantic concepts using a finite number of neurons, a feat that defies the capacity limits of classical attractor networks. While “Concept Cells” in the medial temporal lobe (MTL) exhibit extreme sparsity, the information-theoretic principles governing their…
Henrique Reis Aguiar, Matthias H. Hennig
Predictive coding is a powerful normative framework for understanding cortical computation, but it is still an open question how biologically plausible networks with local plasticity support predictive inference and representation learning. In this work we show that a recurrent excitatory-inhibitory circuit with purely…
Yifei Huang, Siying Luo, Bowen Zheng, Chi Wan Sung
In the traditional $(K,L,M_{T},M_{U},N)$ partially connected linear network, a central server stores a library of N files and connects to $(K+L-1)$ transmitters, each equipped with a cache of size $M_{T}$. Each user is connected to L neighboring transmitters and is equipped with a local cache of size $M_{U}$. Motivated…
Yuwei Ma, Yingke Lei, Changming Liu, Wei Wang + 6 more
Facing heterogeneous signals increasing in dynamic spectrum, cognitive radio urgently needs blind channel coding identification. This technology addresses the core challenge of unknown coding schemes in non-cooperative communications. Existing methods are typically restricted to specific coding types and suffer from…
Kees Schouhamer Immink, Jos H. Weber, Tuan Thanh Nguyen, Kui Cai + 2 more
The design of low-complexity and efficient constrained codes has been a major research item for many years. This paper reports on a versatile method named concatenated constrained codes for designing efficient fixed-length constrained codes with small complexity. A concatenated constrained code comprises two (or more)…
Authors not listed
A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
Authors not listed
We present a chemical framework in which adaptive organization is achieved by tuning a gated quantum resonator (adaptive genomic resonator) {driven quantum oscillator} across a driven, dissipative reaction manifold (fitness landscape) {Hamiltonian potential surface}. In this view, catalytic elements set gain and phase…
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This work establishes theoretical foundations for hierarchical quantum-classical algorithm design, where complex problems are decomposed across multiple spatial, temporal, or organizational scales with quantum and classical computation assigned to appropriate levels. We develop a mathematical framework that…