Lipin Bill Cheng, Ren Jye Yeh · SpringerPlus · 2013
This paper proposes trial algorithms for some basic components in cryptography and lossless bit compression. The symmetric encryption is accomplished by mixing up randomizations and scrambling with hashing of the key playing an essential role. The digital signature is adapted from the Hill cipher with the verification key matrices incorporating un-invertible parts to hide the signature matrix. The hash is a straight running summation (addition chain) of data bytes plus some randomization. One simplified version can be burst error correcting code. The lossless bit compressor is the Shannon-Fano coding that is less optimal than the later Huffman and Arithmetic coding, but can be conveniently implemented without the use of a tree structure and improvable with bytes concatenation.
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Manuela Weigold, Johanna Barzen, Frank Leymann et al. · IET Quantum Communication · 2021
Abstract As quantum computers are based on the laws of quantum mechanics, they are capable of solving certain problems faster than their classical counterparts. However, quantum algorithms with a theoretical speed‐up often assume that data can be loaded efficiently. In general, the runtime complexity of the loading routine depends on (i) the data encoding that defines how the data is represented by the state of the quantum computer and (ii) the data itself. In some cases, loading the data requires at least exponential time that destroys a potential speed‐up. And especially for the first generation of devices that are currently available, the resources (qubits and operations) needed to encode the data are limited. In this work, we, therefore, present six patterns that describe how data is handled by quantum computers.
Cited by 90Open access
Havlíček, Jiří · Brno University of Technology Digital Library (Brno University of Technology) · 2013
Tato bakálářská práce se zabývá tzv. lehkou kryptografií určenou pro méně výkonný hardware. V první části práce jsou vysvětleny základní pojmy a princip kryptografie, rozdíl mezi symetrickým a asymetrickým šifrováním s popisem nejrozšířenějších zástupců obou těchto odvětví kryptografie. V práci jsou dále popsány a parametrově porovnány nově vyvinuté algoritmy se zaměřením na lehkou kryptografii. Pozornost je konkrétně věnována proudovým a blokovým šifrám a hashovacím funkcím. Následně se práce zabývá popisem hardwaru s omezeným výpočetním výkonem. Jedná se o zařízení omezené z hlediska napájení a velikosti samotných čipů. Popis je zaměřen na smart karty, RFID čipy a mikrokontroléry. Praktická část je zaměřena na testování proudových šifer navržených pro softwarové implementace a na testování speciálních proudových šifer navržených pro lehkou kryptografii. Výsledky těchto testů poskytují ucelený pohled na výkonnostní rozdíly jednotlivých šifer určených pro rozdílné implementace.
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Michael Matessa · Acta Astronautica · 2025
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Leszek Gąsieniec, Marek Karpiński, Wojciech Plandowski et al. · Lecture notes in computer science · 1996
Cited by 94
В. С. Выхованец, Jianming Du, Sergey Sakulin · Automation and Remote Control · 2020
This paper presents an overview of the phonetic encoding algorithms designed to determine the similarity of words in sound (pronunciation). Phonetic encoding algorithms are divided into the algorithms for comparing words and the algorithms for determining the distance between words. Word comparison algorithms, such as SoundEx, NYSIIS, Daitch–Mokotoff, Metaphone, and Polyphone, as well as algorithms for determining the distance between words, such as Levenshtein, Jaro, and N-grams, are described. For each algorithm, the advantages and shortcomings are discussed, and an analog for the Russian language is given. For eliminating the common shortcomings of phonetic encoding algorithms, the idea suggested in this paper is to use not the letter sequences of words, but the sequences of their elementary sounds. In this case, word recognition, record linkage, and word indexing by sounds are expected to improve.
Cited by 11
Harish Vangala, Yi Hong, Emanuele Viterbo · IEEE Communications Letters · 2015
Arıkan has laid the foundations of systematic polar codes and has also indicated that the computational complexity order of the systematic polar encoder (SPE) can be the same of a nonsystematic polar encoder (NSPE) i.e., θ(N log N). In this letter, we propose three efficient encoders along with their full pseudocode implementations, all with θ(N log N) complexity. These encoders work for any arbitrary choice of frozen bit indices, and they allow a tradeoff between the number of XOR computations and the number of bits of memory required by the encoder. We show that our best encoder requires exactly the same number of XORs as that of NSPE.
Cited by 71
Perin, Lucas Pandolfo · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2021
Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2021.
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Katarina Z. Doctor, Tong Mao, H. N. Mhaskar · Applied Numerical Mathematics · 2023
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Manuela Weigold, Johanna Barzen, Frank Leymann et al. · 2021
As quantum computers are based on the laws of quantum mechanics, they are capable of solving certain problems faster than their classical counterparts. However, often algorithms which a theoretical speed-up assume that data can be loaded efficiently. In general, the runtime complexity of the loading routine depends on (i) the data encoding that defines how the data is represented and (ii) the data itself. In some cases, loading the data requires at least exponential time which destroys a potential speed-up. And especially for the first generation of devices that are currently available, the resources (qubits and operations) needed to encode the data are limited. Therefore, understanding the consequences of a particular data encoding is crucial. To capture knowledge about different encodings, we present two data encoding patterns that extend our previous collection of encoding patterns [1].
Cited by 63
Norbert Jankowski, Marek Orliński · 2019
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Hutton, Chase, Melrod, Adam · ArXiv.org · 2025
Many parallel algorithms which solve basic problems in computer science use auxiliary space linear in the input to facilitate conflict-free computation. There has been significant work on improving these parallel algorithms to be in-place, that is to use as little auxiliary memory as possible. In this paper, we provide novel in-place algorithms to solve the fundamental problems of merging two sorted sequences, and randomly shuffling a sequence. Both algorithms are work-efficient and have polylogarithmic span. Our algorithms employ encoding techniques which exploit the underlying structure of the input to gain access to more bits, which enables the use of auxiliary data as well as non-in-place methods. The encoding techniques we develop are general. We expect them to be useful in developing in-place algorithms for other problems beyond those already mentioned. To demonstrate this, we outline an additional application to integer sorting. In addition to our theoretical contributions, we implement our merging algorithm, and measure its memory usage and runtime.
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Vikas Nandal, Deepak Nandal · 2013
This paper is to study the evolution of genetic algorithms, their encoding schemes and their current applications. The discussion includes the theoretical concepts of genetic algorithms, evolution history, encoding and GAs current applications. Theoretical topics under review include basic concepts of GA, genetic operators, encoding techniques and applications. Examples of genetic algorithms application that are included in this review are optimization, economic models, pattern recognition, robotics, artificial life, expert system, electronic circuit design and biological applications.
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Sophie Rochet, Mohamed Slimane, Gilles Venturini · 2002
Epistasis is a well known tool introduced by Davidor (1991) to understand and predict the performance of a genetic algorithm using binary encoding. The meaning of variance of epistasis is analyzed using Walsh basis; it is established that this variance can be viewed as a measure of the quality of a linear approximation. Variance of epistasis is therefore easier to estimate using the well known context of polynomial approximation regarding Euclidian distance. This approach also leads to the extension of variance of epistasis to real encoding without considering the notion of schema. Following this new definition, numerical analysis tools can also be applied to compute efficiently this generalized variance of epistasis.
Cited by 12
Alexandru-Gheorghe Reuț · Communications in computer and information science · 2025
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de Gelder, Luuk (author) · Research Repository (Delft University of Technology) · 2021
Conversion from digital information to spike trains is needed for Spiking Neural Networks. Moreover, it is one of the most important steps for Spiking Neural Networks. This conversion could lead to much information loss depending on which encoding algorithm is used. Another major problem that can occur in a specific use-case is the limited bandwidth for the spikes that get generated through the encoding algorithm. In this thesis, we propose population Step Forward Encoding algorithm. This algorithm takes the signal encoding accuracy of Step Forward encoding algorithm and makes it into a population, generating multiple spike trains. This allows a higher threshold to encode a large part of the signal, increasing the efficiency. We show that population Step Forward Encoding algorithm doesn't just work good for the signal encoding accuracy, but also for the classification accuracy. Moreover, population Step Forward Encoding algorithm does not only have a high efficiency with a low spike count, it can also achieve higher efficiency with higher spike count. Thus, population Step Forward can make most use of a limited bandwidth of spikes.
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Andrii Tytarenko · Studies in computational intelligence · 2023
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Ahmed Swilem · International Journal of Mobile Computing and Multimedia Communications · 2009
Vector quantization (VQ) is a well-known compression method. In the encoding phase, given a block represented as a vector, searching the closest codeword in the codebook is a time-consuming task. In this article, two fast encoding algorithms for VQ are proposed. To reduce the search area and accelerate the search process, the first algorithm utilizes three significant features of a vector that are, the norm, andtwo projection angles to two projection axes. The second algorithm uses the first two features as in the first algorithm with the projection value of the vector to the second projection axe. The algorithms allow significant acceleration in the encoding process. Experimental results are presented on image block data. These results confirm the effectiveness of the proposed algorithms.
Cited by 2
Yarga, Sidi Yaya Arnaud, Rouat, Jean, Wood, Sean U. N. · arXiv (Cornell University) · 2022
Spiking Neural Networks (SNN) are known to be very effective for neuromorphic processor implementations, achieving orders of magnitude improvements in energy efficiency and computational latency over traditional deep learning approaches. Comparable algorithmic performance was recently made possible as well with the adaptation of supervised training algorithms to the context of SNN. However, information including audio, video, and other sensor-derived data are typically encoded as real-valued signals that are not well-suited to SNN, preventing the network from leveraging spike timing information. Efficient encoding from real-valued signals to spikes is therefore critical and significantly impacts the performance of the overall system. To efficiently encode signals into spikes, both the preservation of information relevant to the task at hand as well as the density of the encoded spikes must be considered. In this paper, we study four spike encoding methods in the context of a speaker independent digit classification system: Send on Delta, Time to First Spike, Leaky Integrate and Fire Neuron and Bens Spiker Algorithm. We first show that all encoding methods yield higher classification accuracy using significantly fewer spikes when encoding a bio-inspired cochleagram as opposed to a traditional short-time Fourier transform. We then show that two Send On Delta variants result in classification results comparable with a state of the art deep convolutional neural network baseline, while simultaneously reducing the encoded bit rate. Finally, we show that several encoding methods result in improved performance over the conventional deep learning baseline in certain cases, further demonstrating the power of spike encoding algorithms in the encoding of real-valued signals and that neuromorphic implementation has the potential to outperform state of the art techniques.
Cited by 0Open access
ISSA, Hazem, POSTAIRE, Jack-Gérard, RUICHEK, Yassine · OpenGrey (Institut de l'Information Scientifique et Technique) · 2004
Un des objectifs de la vision artificielle est de percevoir le relief d'un environnement à partir d'une ou plusieurs images. La vision binoculaire constitue l'une des méthodes les plus utilisées dans ce domaine. Il s'agit de retrouver la géométrie spatiale d'une scène à partir de deux images prises sous des angles différents. Une des principales difficultés de cette méthode est la mise en correspondance d'indices visuels extraits des images stéréoscopiques. Les techniques séquentielles ou multi-résolutions ayant montré leurs limites, nous présentons dans cette thèse une approche globale pour la mise en correspondance de primitives de type point de contour. Dans cette approche l'appariement stéréoscopique est considéré comme un problème d'optimisation dont la résolution est basée sur les concepts de calcul génétique. Grâce à un codage spécifique, une fonction d'évaluation des solutions (fonction fitness) est construite à partir des contraintes stéréoscopiques. Un algorithme génétique est ensuite mis en oeuvre pour explorer l'espaces des solutions, à partir d'une population initiale de solutions et par application des opérations de sélection, de croisement et de mutation. Afin de réduire la complexité du problème de mise en correspondance, nous proposons une stratégie hiérarchique de recherche des appariements. L'évaluation de nos algorithmes de mise en correspondance, appliqués sur de nombreuses images stéréoscopiques, montre l'intérêt de notre approche pour la reconstruction 3D d'une scène. L'implémentation des procédures développées sur des structures parallèles spécifiques pennettraient d'améliorer les temps d'exécutions et d'envisager une exploitation effective du procédé.
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