Maximum run-length limited codes are constraint codes used in communication and data storage systems. Insertion/deletion correcting codes correct insertion or deletion errors caused in transmitted sequences and are us...
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Maximum run-length limited codes are constraint codes used in communication and data storage systems. Insertion/deletion correcting codes correct insertion or deletion errors caused in transmitted sequences and are used for combating synchronization errors. This paper investigates the maximum run-length limited single insertion/deletion correcting (RLL-SIDC) codes. More precisely, we construct efficiently encodable and decodable RLL-SIDC codes. Moreover, we present its encoding and decoding algorithms and show the redundancy of the code.
Recent developments have shown the existence of quantum low-density parity check (qLDPC) codes with constant rate and linear distance. A natural question concerns the efficient decodability of these codes. In this pap...
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ISBN:
(纸本)9781450399135
Recent developments have shown the existence of quantum low-density parity check (qLDPC) codes with constant rate and linear distance. A natural question concerns the efficient decodability of these codes. In this paper, we present a linear time decoder for the recent quantum Tanner codes construction of asymptotically good qLDPC codes, which can correct all errors of weight up to a constant fraction of the blocklength. Our decoder is an iterative algorithm which searches for corrections within constant-sized regions. At each step, the corrections are found by reducing a locally defined and efficiently computable cost function which serves as a proxy for the weight of the remaining error.
The Gilbert-Varshamov bound non-constructively establishes the existence of binary codes of distance 1/2 - epsilon/2 and rate Omega(epsilon(2)). In a breakthrough result, Ta-Shma [STOC 2017] constructed the first expl...
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ISBN:
(纸本)9781450380539
The Gilbert-Varshamov bound non-constructively establishes the existence of binary codes of distance 1/2 - epsilon/2 and rate Omega(epsilon(2)). In a breakthrough result, Ta-Shma [STOC 2017] constructed the first explicit family of nearly optimal binary codes with distance 1/2 - epsilon/2 and rate Omega(epsilon(2+alpha)), where alpha -> 0 as epsilon -> 0. Moreover, the codes in Ta-Shma's construction are e-balanced, where the distance between distinct codewords is not only bounded from below by 1/2 - epsilon/2, but also from above by 1/2 + epsilon/2. Polynomial time decoding algorithms for (a slight modification of) Ta-Shma's codes appeared in [FOCS 2020], and were based on the Sum-of-Squares (SoS) semidefinite programming hierarchy. The running times for these algorithms were of the form N(O alpha(1) )for unique decoding, and N-O epsilon,N-alpha(1) for the setting of "gentle list decoding", with large exponents of N even when a is a fixed constant. We derive new algorithms for both these tasks, running in time (O) over tilde (epsilon)(N). Our algorithms also apply to the general setting of decoding direct-sum codes. Our algorithms follow from new structural and algorithmic results for collections of k-tuples (ordered hypergraphs) possessing a "structured expansion" property, which we call splittability. This property was previously identified and used in the analysis of SoS-based decoding and constraint satisfaction algorithms, and is also known to be satisfied by Ta-Shma's code construction. We obtain a new weak regularity decomposition for (possibly sparse) splittable collections W subset of [n](k), similar to the regularity decomposition for dense structures by Frieze and Kannan [FOCS 1996]. These decompositions are also computable in near-linear time (O) over tilde(vertical bar W vertical bar), and form a key component of our algorithmic results.
The freeze of the 5th generation new radio (5G NR) Release 16 indicates that 5G development has stepped into a new stage. The application of a dedicated low-density parity-check (LDPC) code for channel coding is an im...
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The freeze of the 5th generation new radio (5G NR) Release 16 indicates that 5G development has stepped into a new stage. The application of a dedicated low-density parity-check (LDPC) code for channel coding is an important technical advance that distinguishes 5G NR from the 4th generation (4G) long-term evolution (LTE) and LIE-advanced. Although LDPC codes have been used in many different systems, the newly developed LDPC code in 5G NR integrates many cutting-edge technologies to provide better performance and attractive features. Thus, it can be a good reference for channel coding in other evolving systems headed by digital terrestrial television broadcasting (DTTB). In emerging applications, the DTTB system needs to carry information with higher density, while meeting the high requirements for real-time, coverage, and bit error rate of broadcasting. To provide a reference for DTTB channel coding that improves its performance and supports new services, a review of 5G NR LDPC code implementation is carried out from three aspects: code analysis and design, decoding algorithm, and decoder architecture. We thoroughly evaluate each solution and highlight some candidates for existing implementations or directions for further development of the DTTB system.
Yupana is an Inca device used for arithmetic operations. This article describes a new arithmetical system: Tawa Pukllay (TP), where arithmetic operations do not require mental calculations: no carries, no borrows, no ...
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ISBN:
(数字)9781665473644
ISBN:
(纸本)9781665473644
Yupana is an Inca device used for arithmetic operations. This article describes a new arithmetical system: Tawa Pukllay (TP), where arithmetic operations do not require mental calculations: no carries, no borrows, no memorization of multiplication tables, nor trial and error procedures for divisions. Instead, user recognizes patterns and makes predefined movements to perform the four basic arithmetic operations very quickly;moreover, the result of the operation can be reached by multiple paths and in parallel, allowing each user to create his own strategies. This paper proves with mathematical rigor that TP produces correct numerical results.
Human-generated passwords are naturally rich in structure, making them vulnerable to guessing attacks. Recently, people have employed strong deep neural networks to model and generate human-generated passwords, showin...
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ISBN:
(纸本)9781665435406
Human-generated passwords are naturally rich in structure, making them vulnerable to guessing attacks. Recently, people have employed strong deep neural networks to model and generate human-generated passwords, showing its great potential for efficient password guessing. However, the research on password guessing decoding algorithms, which is the other essential part of the sequence generation task, remains barely explored. In this paper, we provide an in-depth analysis of the two most widely used classes of sequence decoding algorithms, i.e., Beam Search and Sampling, and find out that a dynamically adjusted Temperature Sampling could be the most suitable one for massive password generation. However, it takes a lot of knowledge and practice even for a human expert to control the temperature parameters appropriately. Thus, we provide a Reinforcement learning-based Dynamic Temperature Sampling algorithm for massive password generation. We first train a Transformerbased password language model in an auto-regressive fashion. Next, we generate the passwords using Temperature Sampling in a batched manner. A neural Q-network is trained to adjust the temperature parameter automatically for each generation batch. A lower temperature value at the start batches allows the most common passwords to be generated rapidly. Then the temperature is gradually increased to generate more nonrepetitive long-tail passwords. Experimental results demonstrate that our proposed method far outperforms baseline methods in terms of both generation speed and hit rate.
A novel scheme of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the scheme, T 2 zero row vectors are added into conventional ...
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ISBN:
(纸本)9781510802704
A novel scheme of unitary space-time constellations generation based on zero vectors adding are proposed for the multiple-antenna communication system. In the scheme, T 2 zero row vectors are added into conventional unitary matrices directly, and the number of new unitary matrices obtained by different positions of the added zero vectors in T symbol duration is ⌊T/T 2 |⌋ times larger than that of conventional unitary matrices. According to the special construction, a corresponding decoding algorithm is proposed with low complexity in flat fading channel. Simulation results show that the proposed the constellation outperform the conventional constellations and the proposed decoding algorithm is efficient and simple.
Digital fountain codes are record-breaking codes for erasure channels. They have many potential applications in both wired and wireless communications. Most existing digital fountain codes operate over binary fields u...
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Digital fountain codes are record-breaking codes for erasure channels. They have many potential applications in both wired and wireless communications. Most existing digital fountain codes operate over binary fields using an iterative belief-propagation (BP) decoding algorithm. In this paper, we propose a new iterative decoding algorithm for both binary and nonbinary fields. The basic form of our proposed algorithm considers both degree-1 and degree-2 check nodes (instead of only degree-1 check nodes as in the original BP decoding scheme), and has linear complexity. Extensive simulation demonstrates that it outperforms the original BP decoding scheme, especially for a small number of source packets. The enhanced form of the proposed algorithm combines the basic form of the algorithm and a guess-based algorithm to further improve the decoding performance. Simulation results demonstrate that it can provide better decoding performance than the guess-based algorithm with fewer guesses, and can achieve decoding performance close to that of the maximum likelihood decoder at a much lower decoding complexity. Last, we show that our nonbinary scheme has the potential to outperform the binary scheme when choosing suitable degree distributions, and furthermore it is insensitive to the size of the Galois field.
Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for ...
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Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop VN stimulation (VNS) would be crucial to increase effectiveness of this approach. Therefore, the extrapolation of useful physiological information from VN electrical activity would represent an invaluable source for single-target applications. Here, we present an advanced decoding algorithm novel to VN studies and properly detecting different functional changes from VN signals. Approach. VN signals were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. We developed a decoding algorithm that combines discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees. Main results. The new decoding algorithm robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. Interestingly our findings suggest that electrodes positioning plays an important role on decoding performances. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles. Significance. This study represents an important step towards the comprehension of VN signaling, paving the way for the development of effective closed-loop VNS systems.
Monotonic Multihead Attention, which allows multiple heads to learn their own alignments per head, shows great performance on simultaneous machine translation and streaming speech recognition. However, it causes high ...
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ISBN:
(纸本)9781665437394
Monotonic Multihead Attention, which allows multiple heads to learn their own alignments per head, shows great performance on simultaneous machine translation and streaming speech recognition. However, it causes high latency waiting for the slowest head. Some recent advances such as Head-Synchronous Beam Search decoding and its learnable version Mutually-Constrained Monotonic Multihead Attention, try to address this issue by restricting the difference in times of chosen frames among multi-heads to a fixed waiting time threshold. In this paper, we hypothesis that the optimal threshold for high performance with low latency depends on the input sequence, and propose an adaptive algorithm that learns how long to wait depending on input tokens by introducing a threshold prediction module. We evaluate our approach on two benchmark datasets for online Automatic Speech Recognition task and demonstrate that our method reduces the latency together with even improving the recognition accuracy.
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