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53rd Annual ACM SIGACT Symposium on Theory of Computing (STOC)

作者： Jeronimo, Fernando Granha Srivastava, Shashank Tulsiani, Madhur Univ Chicago Chicago IL 60637 USA TTIC Chicago IL USA

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.

关键词： decoding algorithm Regularity decomposition Near-linear time GV bound

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Tawa Pukllay Proof: New Method for Solving Arithmetic Operations with The Inca Yupana Using Pattern Recognition and Parallelism

Tawa Pukllay Proof: New Method for Solving Arithmetic Operat...

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International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML)

作者： Prem, Dhavit Guzman-Jimenez, Rosario Sotomayor, Fernando Saldivar, Alvaro Univ Lima ULIMA Syst Engn Lima Peru Univ Nacl Mayor San Marcos UNMSM Assoc Yupanki Lima Lima Peru Univ Lima ULIMA Fac Engn Lima Peru Univ Nacl Ingn UNI Postgrad Sch Lima Peru Univ Lima ULIMA Business Management Sci & Pedag Res Assoc Yupanki Lima Lima Peru

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.

关键词： inca mathematics tawa pukllay yupana pattern recognition parallel computation decoding algorithm

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A Reinforcement Learning-based Sequence Generation algorithm for Password Guessing

A Reinforcement Learning-based Sequence Generation Algorithm...

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IEEE Global Communications Conference (GLOBECOM)

作者： Chen, Zheng Zhang, Xuliang Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu Peoples R China

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.

关键词： Password Guessing decoding algorithm Reinforcement Learning

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A constellation design based on direct insertion and decoding algorithm for noncoherent unitary space-time codes

A constellation design based on direct insertion and decodin...

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International Conference on Cyberspace Technology (CCT 2014)

作者： Dongsheng Han Wei Yang Yinghai Xie School of Electrical and Electronic Engineering North China Electric Power University Baoding 071003 China School of Electronic and Information Engineering Beijing Jiaotong University 100044 China

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.

关键词： Multiple-input multiple output system constellation decoding algorithm unitary space-time constellations zero vector decoding algorithm Zero vector CONSTELLATIONS constellation design Unitary Unitary space-time modulation

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A New Iterative LT decoding algorithm for Binary and Nonbinary Galois Fields

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2013年第4期15卷 411-421页

作者： Mao, Yuexin Huang, Jie Wang, Bing Huang, Jianzhong Zhou, Wei Zhou, Shengli Univ Connecticut Dept Comp Sci & Engn Storrs CT 06269 USA Marvell Semicond Santa Clara CA 95054 USA LSI Corp San Jose CA 95131 USA Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

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.

关键词： Binary erasure channel (BEC) decoding algorithm digital fountain codes Luby transform (LT) codes nonbinary

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Securing Digital Data: A New Edge Detection and XOR Coding Approach for Imperceptible Image Steganography

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2023年第11期14卷 1214-1220页

作者： Al-Dmour, Hayat Mutah Univ Fac Informat Technol Mutah Karak Jordan

The rapid progress of digital devices and technology, coupled with the emergence of the internet has amplified the risks and perils associated with malicious attacks. Consequently, it becomes crucial to protect valuable information transmitted through the internet. Steganography is a tried-and-true technique for hiding information beneath digital content, such as pictures, texts, audio, and video. Various methodologies of image steganography have been developed recently. In image recognition, edge detection secures an image into well-defined areas. This paper introduces a novel image steganography algorithm with edge detection and XOR coding techniques. The proposed approach aims to conceal a confidential message within the spatial domain of the original image. In contrast to uniform regions, the Human Visual System (HVS) is less responsive to variations in the sharp areas;an edge detection algorithm is applied to identify edge pixels. Furthermore, to enhance the efficiency and reduce the embedding impact, XOR operation has been utilized to embed the secret message in the Least Significant Bit (LSB). According to the results of the experiments, the proposed method embeds confidential data without causing noticeable modifications to the stego image. The proposed method system produced imperceptible stego images with minimal embedding distortions compared to existing methods. Based on the results, the proposed approach outperforms the conventional methods regarding image distortion techniques. The PSNR values achieved by the proposed method are higher than the acceptable level.

关键词： Steganography information hidings bits modification decoding algorithm edge detection canny edge detection human visual system

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Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals

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JOURNAL OF NEURAL ENGINEERING 2021年第4期18卷

作者： Vallone, Fabio Ottaviani, Matteo Maria Dedola, Francesca Cutrone, Annarita Romeni, Simone Panarese, Adele Macri Bernini, Fabio Cracchiolo, Marina Strauss, Ivo Gabisonia, Khatia Gorgodze, Nikoloz Mazzoni, Alberto Recchia, Fabio A. Micera, Silvestro Scuola Super Sant Anna BioRobot Inst Pisa Italy Scuola Super Sant Anna Dept Excellence Robot & Artificial Intelligence Pisa Italy Scuola Super Sant Anna Inst Life Sci Pisa Italy Ecole Polytech Fed Lausanne Ctr Neuroprosthet Bertarelli Fdn Chair Translat Neural Engn Lausanne Switzerland Ecole Polytech Fed Lausanne Inst Bioengn Lausanne Switzerland Fdn Toscana Gabriele Monasterio Pisa Italy Temple Univ Dept Physiol Cardiovasc Res Ctr Lewis Katz Sch Med Philadelphia PA 19122 USA

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.

关键词： bioelectronic medicine neuroprosthetics vagus nerve intraneural electrodes decoding algorithm hybrid modeling framework

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LEARNING HOW LONG TO WAIT : ADAPTIVELY-CONSTRAINED MONOTONIC MULTIHEAD ATTENTION FOR STREAMING ASR

LEARNING HOW LONG TO WAIT : ADAPTIVELY-CONSTRAINED MONOTONIC...

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IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

作者： Song, Jaeyun Shim, Hajin Yang, Eunho Korea Adv Inst Sci & Technol Daejeon South Korea AITRICS Seoul South Korea

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.

关键词： online speech recognition Transformer decoding algorithm Monotonic Multihead Attention Head-Synchronous Beam Search decoding

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Novel memory efficient LDPC decoders for beyond 5G

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PHYSICAL COMMUNICATION 2022年 51卷

作者： Li, Hongyuan Yu, Zhenghong Lu, Tongwei Zheng, Wanjun Feng, Haijie Ma, Ziqian Zhu, Fusheng Guangdong Polytech Sci & Technol Coll Robot Zhuhai 519090 Peoples R China Wuhan Inst Technol Hubei Key Lab Intelligent Robot Wuhan 430073 Peoples R China Guangdong New Generat Commun & Network Innovat In Guangzhou Peoples R China

Beyond-5G wireless networks are expected to gain a excellent trade-off among computational accuracy, latency, and efficient use of available resources. This poses a significant challenge to the channel decoder. In this paper, a novel memory efficient algorithm for decoding Low-Density Parity-Check (LDPC) codes is proposed with a view to reduce the implementation complexity and hardware resources. The algorithm, called Check Node Self-Update (CNSU) algorithm, is based on layered normalized min sum (LNMS) decoding algorithm while utilizing iteration parallel techniques to integrate both Variable Nodes (VNs) message and A-Posterior Probability(APP) message into the Check Nodes (CNs) message, which eliminates memories of both the VNs message and the APP message as well as updating module of APP message in CNs unit. Based on the proposed CNSU algorithm, design of partially parallel decoder architecture and serial simulations followed by implementation on the Stratix II EP2S180 FPGA are presented. The results show that the proposed algorithm and implementation bring a significant gain in efficient using of available resources, include reducing hardware memory resources and chip area while keeping the benefit of bit-error-rate (BER) performance and speeding up of convergence with LNMS, which are beneficial to apply in Beyond-5G wireless networks. (C) 2021 Published by Elsevier B.V.

关键词： Low density parity check (LDPC) decoding algorithm FPGA implementation Memory efficient Beyond 5G

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Review of brain-computer interface based on steady-state visual evoked potential

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Brain Science Advances 2022年第4期8卷 258-275页

作者： Siyu Liu Deyu Zhang Ziyu Liu Mengzhen Liu Zhiyuan Ming Tiantian Liu Dingjie Suo Shintaro Funahashi Tianyi Yan School of Life Science Beijing Institute of TechnologyBeijing 100081China School of Mechanical and Electrical Engineering Beijing Institute of TechnologyBeijing 100081China Advanced Research Institute of Multidisciplinary Science Beijing Institute of TechnologyBeijing 100981China Kyoto University Yoshida-honmachi 606-8501Kyoto-ShiJapan

The brain-computer interface(BCI)technology has received lots of attention in the field of scientific research because it can help disabled people improve their quality of ***-state visual evoked potential(SSVEP)is the most researched BCI experimental paradigm,which offers the advantages of high signal-to-noise ratio and short training-time requirement by *** a complete BCI system,the two most critical components are the experimental paradigm and decoding ***,a systematic combination of the SSVEP experimental paradigm and decoding algorithms is missing in existing *** the present study,the transient visual evoked potential,SSVEP,and various improved SSVEP paradigms are compared and analyzed,and the problems and development bottlenecks in the experimental paradigm are finally pointed ***,the canonical correlation analysis and various improved decoding algorithms are introduced,and the opportunities and challenges of the SSVEP decoding algorithm are discussed.

关键词： steady-state visual evoked potential brain–computer interface canonical correlation analysis decoding algorithm

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