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Generalized sparse codes for non-Gaussian channels: Code design, algorithms, and applications [PDF]
Fundamental Research, 2022 In this paper, generalized sparse (GS) codes are proposed to support reliable and efficient transmission over non-Gaussian channels. Specifically, by expanding the single-parity check (SPC) code constraints with powerful algebraic codes, GS codes ...
Zhao Chen +3 more
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A Protocol Design Paradigm for Batched Sparse Codes [PDF]
Entropy, 2020 Internet of Things (IoT) connects billions of everyday objects to the Internet. The mobility of devices can be facilitated by means of employing multiple wireless links.
Hoover H. F. Yin +2 more
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Degeneracy and Its Impact on the Decoding of Sparse Quantum Codes
IEEE Access, 2021 The well-documented capacity-approaching performance of sparse codes in the realm of classical communications has inspired the search for their quantum counterparts.
Patricio Fuentes +3 more
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Sparse coding models can exhibit decreasing sparseness while learning sparse codes for natural images. [PDF]
PLoS Computational Biology, 2013 The sparse coding hypothesis has enjoyed much success in predicting response properties of simple cells in primary visual cortex (V1) based solely on the statistics of natural scenes. In typical sparse coding models, model neuron activities and receptive
Joel Zylberberg, Michael Robert DeWeese
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Learning dictionaries of sparse codes of 3D movements of body joints for real-time human activity understanding. [PDF]
PLoS ONE, 2014 Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been ...
Jin Qi, Zhiyong Yang
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Neuronal allocation and sparse coding of episodic memories in the human hippocampus [PDF]
Scientific ReportsNeurocomputational models hold that individual episodic memories are represented by a sparse, pattern-separated coding scheme in the hippocampus. Animal studies further suggest that the allocation of neurons to such codes is non-random and may be biased ...
Catherine W. Tallman +2 more
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Finite-rate sparse quantum codes aplenty [PDF]
Quantum, 2023 We introduce a methodology for generating random multi-qubit stabilizer codes based on solving a constraint satisfaction problem (CSP) on random bipartite graphs.
Maxime Tremblay +2 more
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Quantum Machine Intelligence, 2022 Abstract The ultimate goal of any sparse coding method is to accurately recover from a few noisy linear measurements, an unknown sparse vector. Unfortunately, this estimation problem is NP-hard in general, and it is therefore always approached with an approximation method, such as lasso or orthogonal matching pursuit, thus trading off accuracy ...
Yaniv Romano +7 more
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On the Logical Error Rate of Sparse Quantum Codes
IEEE Transactions on Quantum Engineering, 2022 The quantum paradigm presents a phenomenon known as degeneracy that can potentially improve the performance of quantum error correcting codes. However, the effects of this mechanism are sometimes ignored when evaluating the performance of sparse quantum ...
Patricio Fuentes +3 more
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Neural network detector with sparse codes for spin transfer torque magnetic random access memory
Cogent Engineering, 2023 This paper presents leveraging the neural network detector to improve the performance of a spin transfer torque magnetic random-access memory (STT-MRAM), where the sparse coding scheme is also applied to protect the user data for the asymmetric write ...
Chi Dinh Nguyen
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