Relevant bibliographies by topics / Low computational complexity algorithms

Academic literature on the topic 'Low computational complexity algorithms'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Low computational complexity algorithms"

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Zhang, Xinhe, Wenbo Lv, and Haoran Tan. "Low-Complexity GSM Detection Based on Maximum Ratio Combining." Future Internet 14, no. 5 (May 23, 2022): 159. http://dx.doi.org/10.3390/fi14050159.

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Generalized spatial modulation (GSM) technology is an extension of spatial modulation (SM) technology, and one of its main advantages is to further improve band efficiency. However, the multiple active antennas for transmission also brings the demodulation difficulties at the receiver. To solve the problem of high computational complexity of the optimal maximum likelihood (ML) detection, two sub-optimal detection algorithms are proposed through reducing the number of transmit antenna combinations (TACs) detected at the receiver. One is the maximum ratio combining detection algorithm based on repetitive sorting strategy, termed as (MRC-RS), which uses MRC repetitive sorting strategy to select the most likely TACs in detection. The other is the maximum ratio combining detection algorithm, which is based on the iterative idea of the orthogonal matching pursuit, termed the MRC-MP algorithm. The MRC-MP algorithm reduces the number of TACs through finite iterations to reduce the computational complexity. For M-QAM constellation, a hard-limited maximum likelihood (HLML) detection algorithm is introduced to calculate the modulation symbol. For the M-PSK constellation, a low-complexity maximum likelihood (LCML) algorithm is introduced to calculate the modulation symbol. The computational complexity of these two algorithms for calculating the modulation symbol are independent of modulation order. The simulation results show that for GSM systems with a large number of TACs, the proposed two algorithms not only achieve almost the same bit error rate (BER) performance as the ML algorithm, but also can greatly reduce the computational complexity.
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Kharlampovich, Olga, and Alina Vdovina. "Low complexity algorithms in knot theory." International Journal of Algebra and Computation 29, no. 02 (March 2019): 245–62. http://dx.doi.org/10.1142/s0218196718500698.

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Agol, Haas and Thurston showed that the problem of determining a bound on the genus of a knot in a 3-manifold, is NP-complete. This shows that (unless P[Formula: see text]NP) the genus problem has high computational complexity even for knots in a 3-manifold. We initiate the study of classes of knots where the genus problem and even the equivalence problem have very low computational complexity. We show that the genus problem for alternating knots with n crossings has linear time complexity and is in Logspace[Formula: see text]. Alternating knots with some additional combinatorial structure will be referred to as standard. As expected, almost all alternating knots of a given genus are standard. We show that the genus problem for these knots belongs to [Formula: see text] circuit complexity class. We also show, that the equivalence problem for such knots with [Formula: see text] crossings has time complexity [Formula: see text] and is in Logspace[Formula: see text] and [Formula: see text] complexity classes.
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Chen, Haihua, Jialiang Hu, Hui Tian, Shibao Li, Jianhang Liu, and Masakiyo Suzuki. "A Low-Complexity GA-WSF Algorithm for Narrow-Band DOA Estimation." International Journal of Antennas and Propagation 2018 (November 4, 2018): 1–6. http://dx.doi.org/10.1155/2018/7175653.

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This paper proposes a low-complexity estimation algorithm for weighted subspace fitting (WSF) based on the Genetic Algorithm (GA) in the problem of narrow-band direction-of-arrival (DOA) finding. Among various solving techniques for DOA, WSF is one of the highest estimation accuracy algorithms. However, its criteria is a multimodal nonlinear multivariate optimization problem. As a result, the computational complexity of WSF is very high, which prevents its application to real systems. The Genetic Algorithm (GA) is considered as an effective algorithm for finding the global solution of WSF. However, conventional GA usually needs a big population size to cover the whole searching space and a large number of generations for convergence, which means that the computational complexity is still high. To reduce the computational complexity of WSF, this paper proposes an improved Genetic algorithm. Firstly a hypothesis technique is used for a rough DOA estimation for WSF. Then, a dynamic initialization space is formed around this value with an empirical function. Within this space, a smaller population size and smaller amount of generations are required. Consequently, the computational complexity is reduced. Simulation results show the efficiency of the proposed algorithm in comparison to many existing algorithms.
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Xue, Xiaomei, Zhengquan Li, Yongqiang Man, Song Xing, Yang Liu, Baolong Li, and Qiong Wu. "Improved Massive MIMO RZF Precoding Algorithm Based on Truncated Kapteyn Series Expansion." Information 10, no. 4 (April 11, 2019): 136. http://dx.doi.org/10.3390/info10040136.

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In order to reduce the computational complexity of the inverse matrix in the regularized zero-forcing (RZF) precoding algorithm, this paper expands and approximates the inverse matrix based on the truncated Kapteyn series expansion and the corresponding low-complexity RZF precoding algorithm is obtained. In addition, the expansion coefficients of the truncated Kapteyn series in our proposed algorithm are optimized, leading to further improvement of the convergence speed of the precoding algorithm under the premise of the same computational complexity as the traditional RZF precoding. Moreover, the computational complexity and the downlink channel performance in terms of the average achievable rate of the proposed RZF precoding algorithm and other RZF precoding algorithms with typical truncated series expansion approaches are analyzed, and further evaluated by numerical simulations in a large-scale single-cell multiple-input-multiple-output (MIMO) system. Simulation results show that the proposed improved RZF precoding algorithm based on the truncated Kapteyn series expansion performs better than other compared algorithms while keeping low computational complexity.
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Manis, George, Md Aktaruzzaman, and Roberto Sassi. "Low Computational Cost for Sample Entropy." Entropy 20, no. 1 (January 13, 2018): 61. http://dx.doi.org/10.3390/e20010061.

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Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regularity/complexity of a time series. On the other hand, it is a computationally expensive method which may require a large amount of time when used in long series or with a large number of signals. The computationally intensive part is the similarity check between points in m dimensional space. In this paper, we propose new algorithms or extend already proposed ones, aiming to compute Sample Entropy quickly. All algorithms return exactly the same value for Sample Entropy, and no approximation techniques are used. We compare and evaluate them using cardiac inter-beat (RR) time series. We investigate three algorithms. The first one is an extension of the k d -trees algorithm, customized for Sample Entropy. The second one is an extension of an algorithm initially proposed for Approximate Entropy, again customized for Sample Entropy, but also improved to present even faster results. The last one is a completely new algorithm, presenting the fastest execution times for specific values of m, r, time series length, and signal characteristics. These algorithms are compared with the straightforward implementation, directly resulting from the definition of Sample Entropy, in order to give a clear image of the speedups achieved. All algorithms assume the classical approach to the metric, in which the maximum norm is used. The key idea of the two last suggested algorithms is to avoid unnecessary comparisons by detecting them early. We use the term unnecessary to refer to those comparisons for which we know a priori that they will fail at the similarity check. The number of avoided comparisons is proved to be very large, resulting in an analogous large reduction of execution time, making them the fastest algorithms available today for the computation of Sample Entropy.
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Zhang, Xinhe, Yuehua Zhang, Chang Liu, and Hanzhong Jia. "Low-Complexity Detection Algorithms for Spatial Modulation MIMO Systems." Journal of Electrical and Computer Engineering 2018 (November 15, 2018): 1–7. http://dx.doi.org/10.1155/2018/4034625.

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In this paper, the authors propose three low-complexity detection schemes for spatial modulation (SM) systems based on the modified beam search (MBS) detection. The MBS detector, which splits the search tree into some subtrees, can reduce the computational complexity by decreasing the nodes retained in each layer. However, the MBS detector does not take into account the effect of subtree search order on computational complexity, and it does not consider the effect of layers search order on the bit-error-rate (BER) performance. The ost-MBS detector starts the search from the subtree where the optimal solution is most likely to be located, which can reduce total searches of nodes in the subsequent subtrees. Thus, it can decrease the computational complexity. When the number of the retained nodes is fixed, which nodes are retained is very important. That is, the different search orders of layers have a direct influence on BER. Based on this, we propose the oy-MBS detector. The ost-oy-MBS detector combines the detection order of ost-MBS and oy-MBS together. The algorithm analysis and experimental results show that the proposed detectors outstrip MBS with respect to the BER performance and the computational complexity.
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Rampa, Vittorio. "Design and Implementation of a Low Complexity Multiuser Detector for Hybrid CDMA Systems." Journal of Communications Software and Systems 1, no. 1 (April 6, 2017): 42. http://dx.doi.org/10.24138/jcomss.v1i1.316.

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In hybrid CDMA systems, multiuser detection (MUD) algorithms are adopted at the base station to reduce both multiple access and inter-symbol interference by exploitingspace-time (ST) signal processing techniques. Linear ST-MUD algorithms solve a linear problem where the system matrix has a block-Toeplitz shape. While exact inversion techniques impose an intolerable computational load, reduced complexity algorithms may be efficiently employed even if they show suboptimal behavior introducing performance degradation and nearfar effects. The block-Fourier MUD algorithm is generally considered the most effective one. However, the block-Bareiss MUD algorithm, that has been recently reintroduced, shows also good performance and low computational complexity comparingfavorably with the block-Fourier one. In this paper, both MUD algorithms will be compared, along with other well known ones, in terms of complexity, performance figures, hardware feasibility and implementation issues. Finally a short hardware description of the block-Bareiss and block-Fourier algorithms will be presented along with the FPGA (Field Programmable Gate Array) implementation of the block-Fourier using standard VHDL (VHSIC Hardware Description Language) design.
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Wang, Yuhuan, Jianguo Li, Neng Ye, and Xiangyuan Bu. "Novel Low Complexity BP Decoding Algorithms for Polar Codes: Simplifying on Non-Linear Operations." Electronics 11, no. 1 (December 28, 2021): 93. http://dx.doi.org/10.3390/electronics11010093.

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The parallel nature of the belief propagation (BP) decoding algorithm for polar codes opens up a real possibility of high throughput and low decoding latency during hardware implementation. To address the problem that the BP decoding algorithm introduces high-complexity non-linear operations in the iterative messages update process, this paper proposes to simplify these operations and develops two novel low complexity BP decoding algorithms, namely, exponential BP (Exp-BP) decoding algorithm and quantization function BP (QF-BP) decoding algorithm. The proposed algorithms simplify the compound hyperbolic tangent function by using probability distribution fitting techniques. Specifically, the Exp-BP algorithm simplifies two types of non-linear operations into single non-linear operation using the piece-wise exponential model function, which can approximate the hyperbolic tangent function in the updating formula. The QF-BP algorithm eliminates non-linear operations using the non-uniform quantization in the updating formula, which is effective in reducing computational complexity. According to the simulation results, the proposed algorithms can reduce the computational complexity up to 50% in each iteration with a loss of less than 0.1 dB compared with the BP decoding algorithm, which can facilitate the hardware implementation.
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Otunniyi, Temidayo O., and Hermanus C. Myburgh. "Low-Complexity Filter for Software-Defined Radio by Modulated Interpolated Coefficient Decimated Filter in a Hybrid Farrow." Sensors 22, no. 3 (February 3, 2022): 1164. http://dx.doi.org/10.3390/s22031164.

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Realising a low-complexity Farrow channelisation algorithm for multi-standard receivers in software-defined radio is a challenging task. A Farrow filter operates best at low frequencies while its performance degrades towards the Nyquist region. This makes wideband channelisation in software-defined radio a challenging task with high computational complexity. In this paper, a hybrid Farrow algorithm that combines a modulated Farrow filter with a frequency response interpolated coefficient decimated masking filter is proposed for the design of a novel filter with low computational complexity. A design example shows that the HFarrow filter bank achieved multiplier reduction of 50%, 70% and 64%, respectively, in comparison with non-uniform modulated discrete Fourier transform (NU MDFT FB), coefficient decimated filter bank (CD FB) and interpolated coefficient decimated (ICDM) filter algorithms. The HFarrow filter bank is able to provide the same number of sub-band channels as other algorithms such as non-uniform modulated discrete Fourier transform (NU MDFT FB), coefficient decimated filter bank (CD FB) and interpolated coefficient decimated (ICDM) filter algorithms, but with less computational complexity.
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Chen, Haihua, Haoran Li, Mingyang Yang, Changbo Xiang, and Masakiyo Suzuki. "General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation." International Journal of Antennas and Propagation 2019 (December 11, 2019): 1–9. http://dx.doi.org/10.1155/2019/3858794.

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Heuristic algorithms are considered to be effective approaches for super-resolution DOA estimations such as Deterministic Maximum Likelihood (DML), Stochastic Maximum Likelihood (SML), and Weighted Subspace Fitting (WSF) which are involved in nonlinear multi-dimensional optimization. Traditional heuristic algorithms usually need a large number of particles and iteration times. As a result, the computational complexity is still a bit high, which prevents the application of these super-resolution techniques in real systems. To reduce the computational complexity of heuristic algorithms for these super-resolution techniques of DOA, this paper proposes three general improvements of heuristic algorithms, i.e., the optimization of the initialization space, the optimization of evolutionary strategies, and the usage of parallel computing techniques. Simulation results show that the computational complexity can be greatly reduced while these improvements are used.
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Dissertations / Theses on the topic "Low computational complexity algorithms"

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Troiani, Chiara. "Vision-Aided Inertial Navigation : low computational complexity algorithms with applications to Micro Aerial Vehicles." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM021/document.

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L'estimation précise du mouvement 3D d'une caméra relativement à une scène rigideest essentielle pour tous les systèmes de navigation visuels. Aujourd'hui différentstypes de capteurs sont adoptés pour se localiser et naviguer dans des environnementsinconnus : GPS, capteurs de distance, caméras, capteurs magnétiques, centralesinertielles (IMU, Inertial Measurement Unit). Afin d'avoir une estimation robuste, lesmesures de plusieurs capteurs sont fusionnées. Même si le progrès technologiquepermet d'avoir des capteurs de plus en plus précis, et si la communauté de robotiquemobile développe algorithmes de navigation de plus en plus performantes, il y aencore des défis ouverts. De plus, l'intérêt croissant des la communauté de robotiquepour les micro robots et essaim de robots pousse vers l'emploi de capteurs à bas poids,bas coût et vers l'étude d'algorithmes à faible complexité. Dans ce contexte, capteursinertiels et caméras monoculaires, grâce à leurs caractéristiques complémentaires,faible poids, bas coût et utilisation généralisée, représentent une combinaison decapteur intéressante.Cette thèse présente une contribution dans le cadre de la navigation inertielle assistéepar vision et aborde les problèmes de fusion de données et estimation de la pose, envisant des algorithmes à faible complexité appliqués à des micro-véhicules aériens.Pour ce qui concerne l'association de données, une nouvelle méthode pour estimer lemouvement relatif entre deux vues de caméra consécutifs est proposée.Celle-ci ne nécessite l'observation que d'un seul point caractéristique de la scène et laconnaissance des vitesses angulaires fournies par la centrale inertielle, sousl'hypothèse que le mouvement de la caméra appartient localement à un planperpendiculaire à la direction de la gravité. Deux algorithmes très efficaces pouréliminer les fausses associations de données (outliers) sont proposés sur la base decette hypothèse de mouvement.Afin de généraliser l'approche pour des mouvements à six degrés de liberté, deuxpoints caracteristiques et les données gyroscopiques correspondantes sont nécessaires.Dans ce cas, deux algorithmes sont proposés pour éliminer les outliers.Nous montrons que dans le cas d'une caméra monoculaire montée sur un quadrotor,les informations de mouvement fournies par l'IMU peuvent être utilisées pouréliminer de mauvaises estimations.Pour ce qui concerne le problème d'estimation de la pose, cette thèse fournit unesolution analytique pour exprimer la pose du système à partir de l'observation de troispoints caractéristiques naturels dans une seule image, une fois que le roulis et letangage sont obtenus par les données inertielles sous l'hypothèse de terrain plan.Afin d'aborder le problème d'estimation de la pose dans des environnements sombresou manquant de points caractéristiques, un système équipé d'une caméra monoculaire,d'une centrale inertielle et d'un pointeur laser est considéré. Grace à une analysed'observabilité il est démontré que les grandeurs physiques qui peuvent êtredéterminées par l'exploitation des mesures fourni par ce systeme de capteurs pendantun court intervalle de temps sont : la distance entre le système et la surface plane ;la composante de la vitesse du système qui est orthogonale à la surface ; l'orientationrelative du système par rapport à la surface et l'orientation de la surface par rapport àla gravité. Une méthode récursive simple a été proposée pour l'estimation de toutesces quantités observables.Toutes les contributions de cette thèse sont validées par des expérimentations à l'aidedes données réelles et simulées. Grace à leur faible complexité de calcul, lesalgorithmes proposés sont très appropriés pour la mise en oeuvre en temps réel surdes systèmes ayant des ressources de calcul limitées. La suite de capteur considéréeest monté sur un quadrotor, mais les contributions de cette thèse peuvent êtreappliquées à n'importe quel appareil mobile
Accurate egomotion estimation is of utmost importance for any navigation system.Nowadays di_erent sensors are adopted to localize and navigate in unknownenvironments such as GPS, range sensors, cameras, magnetic field sensors, inertialsensors (IMU). In order to have a robust egomotion estimation, the information ofmultiple sensors is fused. Although the improvements of technology in providingmore accurate sensors, and the efforts of the mobile robotics community in thedevelopment of more performant navigation algorithms, there are still openchallenges. Furthermore, the growing interest of the robotics community in microrobots and swarm of robots pushes towards the employment of low weight, low costsensors and low computational complexity algorithms. In this context inertial sensorsand monocular cameras, thanks to their complementary characteristics, low weight,low cost and widespread use, represent an interesting sensor suite.This dissertation represents a contribution in the framework of vision-aided inertialnavigation and tackles the problems of data association and pose estimation aimingfor low computational complexity algorithms applied to MAVs.For what concerns the data association, a novel method to estimate the relative motionbetween two consecutive camera views is proposed. It only requires the observationof a single feature in the scene and the knowledge of the angular rates from an IMU,under the assumption that the local camera motion lies in a plane perpendicular to thegravity vector. Two very efficient algorithms to remove the outliers of the featurematchingprocess are provided under the abovementioned motion assumption. Inorder to generalize the approach to a 6DoF motion, two feature correspondences andgyroscopic data from IMU measurements are necessary. In this case, two algorithmsare provided to remove wrong data associations in the feature-matching process. Inthe case of a monocular camera mounted on a quadrotor vehicle, motion priors fromIMU are used to discard wrong estimations.For what concerns the pose estimation problem, this thesis provides a closed formsolution which gives the system pose from three natural features observed in a singlecamera image, once the roll and the pitch angles are obtained by the inertialmeasurements under the planar ground assumption.In order to tackle the pose estimation problem in dark or featureless environments, asystem equipped with a monocular camera, inertial sensors and a laser pointer isconsidered. The system moves in the surrounding of a planar surface and the laserpointer produces a laser spot on the abovementioned surface. The laser spot isobserved by the monocular camera and represents the only point feature considered.Through an observability analysis it is demonstrated that the physical quantities whichcan be determined by exploiting the measurements provided by the aforementionedsensor suite during a short time interval are: the distance of the system from the planarsurface; the component of the system speed that is orthogonal to the planar surface;the relative orientation of the system with respect to the planar surface; the orientationof the planar surface with respect to the gravity. A simple recursive method toperform the estimation of all the aforementioned observable quantities is provided.All the contributions of this thesis are validated through experimental results usingboth simulated and real data. Thanks to their low computational complexity, theproposed algorithms are very suitable for real time implementation on systems withlimited on-board computation resources. The considered sensor suite is mounted on aquadrotor vehicle but the contributions of this dissertations can be applied to anymobile device
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Goussevskaia, Olga. "Computational complexity and scheduling algorithms for wireless networks." Konstanz Hartung-Gorre, 2009. http://d-nb.info/997891122/04.

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Udupa, Pramod. "Algorithmes parallèles et architectures évolutives de faible complexité pour systèmes optiques OFDM cohérents temps réel." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S039/document.

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Dans cette thèse, des algorithmes à faible complexité et des architectures parallèles et efficaces sont explorés pour les systèmes CO-OFDM. Tout d'abord, des algorithmes de faible complexité pour la synchronisation et l'estimation du décalage en fréquence en présence d'un canal dispersif sont étudiés. Un nouvel algorithme de synchronisation temporelle à faible complexité qui peut résister à grande quantité de retard dispersif est proposé et comparé par rapport aux propositions antérieures. Ensuite, le problème de la réalisation d'une architecture parallèle à faible coût est étudié et une architecture parallèle générique et évolutive qui peut être utilisée pour réaliser tout type d'algorithme d'auto-corrélation est proposé. Cette architecture est ensuite étendue pour gérer plusieurs échantillons issus du convertisseur analogique/numérique (ADC) en parallèle et fournir une sortie qui suive la fréquence des ADC. L'évolutivité de l'architecture pour un nombre plus élevé de sorties en parallèle et les différents types d'algorithmes d'auto-corrélation sont explorés. Une approche d'adéquation algorithme-architecture est ensuite appliquée à l'ensemble de la chaîne de l'émetteur-récepteur CO-OFDM. Du côté de l'émetteur, un algorithme IFFT à radix-22 est choisi pour et une architecture parallèle Multipath Delay Commutator (MDC). Feed-forward (FF) est choisie car elle consomme moins de ressources par rapport aux architectures MDC-FF en radix-2/4. Au niveau du récepteur, un algorithme efficace pour l'estimation du Integer CFO est adopté et implémenté de façon optimisée sans l'utilisation de multiplicateurs complexes. Une réduction de la complexité matérielle est obtenue grâce à la conception d'architectures efficaces pour la synchronisation temporelle, la FFT et l'estimation du CFO. Une exploration du compromis entre la précision des calculs en virgule fixe et la complexité du matériel est réalisée pour la chaîne complète de l'émetteur- récepteur, de façon à trouver des points de fonctionnement qui n'affectent pas le taux d'erreur binaire (TEB) de manière significative. Les algorithmes proposés sont validés à l'aide d'une part d'expériences off-line en utilisant un générateur AWG (arbitrary wave- form generator) à l'émetteur et un oscilloscope numérique à mémoire (DSO) en sortie de la détection cohérente au récepteur, et d'autre part un émetteur-récepteur temps-réel basé sur des plateformes FPGA et des convertisseurs numériques. Le TEB est utilisé pour montrer la validité du système intégré et en donner les performances
In this thesis, low-complexity algorithms and architectures for CO-OFDM systems are explored. First, low-complexity algorithms for estimation of timing and carrier frequency offset (CFO) in dispersive channel are studied. A novel low-complexity timing synchro- nization algorithm, which can withstand large amount of dispersive delay, is proposed and compared with previous proposals. Then, the problem of realization of low-complexity parallel architecture is studied. A generalized scalable parallel architecture, which can be used to realize any auto-correlation algorithm, is proposed. It is then extended to handle multiple parallel samples from ADC and provide outputs, which can match the input ADC rate. The scalability of the architecture for higher number of parallel outputs and different kinds of auto-correlation algorithms is explored. An algorithm-architecture approach is then applied to the entire CO-OFDM transceiver chain. At the transmitter side, radix-22 algorithm for IFFT is chosen and parallel Mul- tipath Delay Commutator (MDC) Feed-forward (FF) architecture is designed which con- sumes lesser resources compared to MDC FF architectures of radix-2/4. At the receiver side, efficient algorithm for Integer CFO estimation is adopted and efficiently realized with- out the use of complex multipliers. Reduction in complexity is achieved due to efficient architectures for timing synchronization, FFT and Integer CFO estimation. Fixed-point analysis for the entire transceiver chain is done to find fixed-point sensitive blocks, which affect bit error rate (BER) significantly. The algorithms proposed are validated using opti- cal experiments by the help of arbitrary waveform generator (AWG) at the transmitter and digital storage oscilloscope (DSO) and Matlab at the receiver. BER plots are used to show the validity of the system built. Hardware implementation of the proposed synchronization algorithm is validated using real-time FPGA platform
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Danjean, Ludovic. "Low-Complexity Iterative Reconstruction Algorithms in Compressed Sensing." International Foundation for Telemetering, 2013. http://hdl.handle.net/10150/579661.

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ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV
In this paper we focus on two low-complexity iterative reconstruction algorithms in compressed sensing. These algorithms, called the approximate message-passing algorithm and the interval-passing algorithm, are suitable to recover sparse signals from a small set of measurements. Depending on the type of measurement matrix (sparse or random) used to acquire the samples of the signal, one or the other reconstruction algorithm can be used. We present the reconstruction results of these two reconstruction algorithms in terms of proportion of correct reconstructions in the noise free case. We also report in this paper possible practical applications of compressed sensing where the choice of the measurement matrix and the reconstruction algorithm are often governed by the constraint of the considered application.
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Vorhies, John T. "Low-complexity Algorithms for Light Field Image Processing." University of Akron / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=akron1590771210097321.

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Uppman, Hannes. "On Some Combinatorial Optimization Problems : Algorithms and Complexity." Doctoral thesis, Linköpings universitet, Programvara och system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-116859.

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This thesis is about the computational complexity of several classes of combinatorial optimization problems, all related to the constraint satisfaction problems. A constraint language consists of a domain and a set of relations on the domain. For each such language there is a constraint satisfaction problem (CSP). In this problem we are given a set of variables and a collection of constraints, each of which is constraining some variables with a relation in the language. The goal is to determine if domain values can be assigned to the variables in a way that satisfies all constraints. An important question is for which constraint languages the corresponding CSP can be solved in polynomial time. We study this kind of question for optimization problems related to the CSPs. The main focus is on extended minimum cost homomorphism problems. These are optimization versions of CSPs where instances come with an objective function given by a weighted sum of unary cost functions, and where the goal is not only to determine if a solution exists, but to find one of minimum cost. We prove a complete classification of the complexity for these problems on three-element domains. We also obtain a classification for the so-called conservative case. Another class of combinatorial optimization problems are the surjective maximum CSPs. These problems are variants of CSPs where a non-negative weight is attached to each constraint, and the objective is to find a surjective mapping of the variables to values that maximizes the weighted sum of satisfied constraints. The surjectivity requirement causes these problems to behave quite different from for example the minimum cost homomorphism problems, and many powerful techniques are not applicable. We prove a dichotomy for the complexity of the problems in this class on two-element domains. An essential ingredient in the proof is an algorithm that solves a generalized version of the minimum cut problem. This algorithm might be of independent interest. In a final part we study properties of NP-hard optimization problems. This is done with the aid of restricted forms of polynomial-time reductions that for example preserves solvability in sub-exponential time. Two classes of optimization problems similar to those discussed above are considered, and for both we obtain what may be called an easiest NP-hard problem. We also establish some connections to the exponential time hypothesis.
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Smith, Justin N. "Computational complexity, bounded rationality and the theory of games." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365642.

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Lundqvist, Samuel. "Computational algorithms for algebras." Doctoral thesis, Stockholm : Department of Mathematics, Stockholm University, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-31552.

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Diss. (sammanfattning) Stockholm : Stockholms universitet, 2009.
At the time of doctoral defence, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript. Paper 5: Manuscript. Paper 6: Manuscript. Härtill 6 uppsatser.
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Neyer, Gabriele. "Algorithms, complexity, and software engineering in computational geometry : case studies /." [S.l.] : [s.n.], 2000. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=13586.

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Brooks, Duncan John. "Adaptive algorithms for low complexity equalizers in mobile communications." Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.312445.

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Books on the topic "Low computational complexity algorithms"

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Kronsjö, Lydia. Computational complexity of sequential and parallel algorithms. Chichester: Wiley, 1985.

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Kronsjö, Lydia I. Computational complexity of sequential and parallel algorithms. Chichester: Wiley, 1986.

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Computational complexity of sequential and parallel algorithms. Chichester: Wiley, 1987.

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Wilf, Herbert S. Algorithms and complexity. Englewood Cliffs, N.J: Prentice-Hall, 1986.

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Algorithms and complexity. 2nd ed. Natick, Mass: A.K. Peters, 2002.

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1939-, Steiglitz Kenneth, ed. Combinatorial optimization: Algorithms and complexity. Mineola, N.Y: Dover Publications, 1998.

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Neapolitan, Richard E. Foundations of algorithms. 4th ed. Sudbury, Mass: Jones and Bartlett Publishers, 2011.

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Kumarss, Naimipour, ed. Foundations of algorithms. 4th ed. Sudbury, Mass: Jones and Bartlett Publishers, 2011.

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Algorithms: Their complexity and efficiency. 2nd ed. Chichester: Wiley, 1987.

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Complexity theory: Exploring the limits of efficient algorithms. Berlin: Springer, 2005.

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Book chapters on the topic "Low computational complexity algorithms"

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Novak, Miroslav. "Algorithm Optimizations: Low Computational Complexity." In Advances in Pattern Recognition, 213–31. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-143-5_10.

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Yao, Lin, and Kai Yao. "A Low Complexity Intrusion Detection Algorithm." In Computational Science – ICCS 2007, 461–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72588-6_76.

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Shan, Ying-ying, and Xuan Wang. "A Low Computational Complexity Multiple Description Image Coding Algorithm Based on JPEG Standard." In Novel Algorithms and Techniques in Telecommunications and Networking, 173–76. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3662-9_29.

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Kim, Sosun, Nam Su Chang, Chang Han Kim, Young-Ho Park, and Jongin Lim. "A Fast Inversion Algorithm and Low-Complexity Architecture over GF(2 m )." In Computational Intelligence and Security, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596981_1.

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Kim, Sanghun, Seokho Yoon, Hyoung-Kee Choi, and Sun Yong Kim. "A Low Complexity and Robust Frequency Offset Estimation Algorithm for OFDM-Based WLAN Systems." In Computational Science – ICCS 2006, 961–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758525_127.

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Turcza, Paweł, Tomasz Zieliński, and Mariusz Duplaga. "Hardware Implementation Aspects of New Low Complexity Image Coding Algorithm for Wireless Capsule Endoscopy." In Computational Science – ICCS 2008, 476–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69384-0_53.

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Zontone, Pamela, Antonio Affanni, Riccardo Bernardini, Alessandro Piras, and Roberto Rinaldo. "Low-Complexity Classification Algorithm to Identify Drivers’ Stress Using Electrodermal Activity (EDA) Measurements." In Biomedical Engineering and Computational Intelligence, 25–33. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21726-6_3.

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Yang, Jia-lin. "On an Improved K-Best Algorithm with High Performance and Low Complexity for MIMO Systems." In Smart Innovations in Communication and Computational Sciences, 309–18. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8971-8_28.

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Rathod, D. P., and R. N. Awale. "An Efficient Genetic Based Algorithm for an Irregular Low Density Parity Check Code with Low Computational Complexity and Low Error Floor." In Communications in Computer and Information Science, 249–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36321-4_23.

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Brucker, Peter. "Computational Complexity." In Scheduling Algorithms, 37–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24804-0_3.

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Conference papers on the topic "Low computational complexity algorithms"

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Hull, A. W., and W. K. Jenkins. "Low computational complexity adaptive algorithms for IIR digital filters." In [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1991. http://dx.doi.org/10.1109/icassp.1991.150817.

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Chew, Li Wern, Li-Minn Ang, and Kah Phooi Seng. "Low-Complexity Line-Based Motion Estimation Algorithm." In 2007 International Conference on Computational Intelligence and Security (CIS 2007). IEEE, 2007. http://dx.doi.org/10.1109/cis.2007.204.

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Liu, Fang, Sinong Wang, Swapna Buccapatnam, and Ness Shroff. "UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/338.

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In this work, we address the open problem of finding low-complexity near-optimal multi-armed bandit algorithms for sequential decision making problems. Existing bandit algorithms are either sub-optimal and computationally simple (e.g., UCB1) or optimal and computationally complex (e.g., kl-UCB). We propose a boosting approach to Upper Confidence Bound based algorithms for stochastic bandits, that we call UCBoost. Specifically, we propose two types of UCBoost algorithms. We show that UCBoost(D) enjoys O(1) complexity for each arm per round as well as regret guarantee that is 1/e-close to that of the kl-UCB algorithm. We propose an approximation-based UCBoost algorithm, UCBoost(epsilon), that enjoys a regret guarantee epsilon-close to that of kl-UCB as well as O(log(1/epsilon)) complexity for each arm per round. Hence, our algorithms provide practitioners a practical way to trade optimality with computational complexity. Finally, we present numerical results which show that UCBoost(epsilon) can achieve the same regret performance as the standard kl-UCB while incurring only 1% of the computational cost of kl-UCB.
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Gao Jing, Wang Jinkuan, Xie Zhibin, and Yan Dongmei. "A modified PTS PAPR reduction algorithm with low computational complexity." In IET 2nd International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN 2008). IEE, 2008. http://dx.doi.org/10.1049/cp:20081004.

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Weithoffer, Stefan, Rami Klaimi, Charbel Abdel Nour, Norbert Wehn, and Catherine Douillard. "Low-complexity Computational Units for the Local-SOVA Decoding Algorithm." In 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications. IEEE, 2020. http://dx.doi.org/10.1109/pimrc48278.2020.9217318.

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Zhao, Yanhua, Vladica Sark, Milos Krstic, and Eckhard Grass. "Low Computational Complexity Algorithm for Hand Gesture Recognition using mmWave RADAR." In 2022 International Symposium on Wireless Communication Systems (ISWCS). IEEE, 2022. http://dx.doi.org/10.1109/iswcs56560.2022.9940253.

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Soma, Umamaheshwar, Anil Kumar Tipparti, and Srinivasa Rao Kunupalli. "Improved performance of low complexity K-best sphere decoder algorithm." In 2017 International Conference on Inventive Communication and Computational Technologies (ICICCT). IEEE, 2017. http://dx.doi.org/10.1109/icicct.2017.7975248.

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Jin, Longxu, Jin Li, Min Zhang, and Yinan Wu. "Low-Complexity Multispectral Images Compression Algorithm Based Distributed Compressive Sensing." In 2013 6th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2013. http://dx.doi.org/10.1109/iscid.2013.149.

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Anagreh, Mohammad, Peeter Laud, and Eero Vainikko. "Privacy-preserving Parallel Computation of Shortest Path Algorithms with Low Round Complexity." In 8th International Conference on Information Systems Security and Privacy. SCITEPRESS - Science and Technology Publications, 2022. http://dx.doi.org/10.5220/0010775700003120.

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Bae, Seung Chun, Jae Wook Park, and Won Cheol Lee. "Genetic algorithm based efficient positioning error compensation technique with low computational complexity." In TENCON 2009 - 2009 IEEE Region 10 Conference. IEEE, 2009. http://dx.doi.org/10.1109/tencon.2009.5395935.

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Reports on the topic "Low computational complexity algorithms"

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Ariyawansa, K. A. Low-Complexity Interior Point Algorithms for Stochastic Programming: Derivation Analysis and Performance Evaluation. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada418278.

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Gil, Oliver Fernández, and Anni-Yasmin Turhan. Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics. Technische Universität Dresden, 2020. http://dx.doi.org/10.25368/2022.261.

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Classical regular path queries (RPQs) can be too restrictive for some applications and answering such queries under approximate semantics to relax the query is desirable. While for answering regular path queries over graph databases under approximate semantics algorithms are available, such algorithms are scarce for the ontology-mediated setting. In this paper we extend an approach for answering RPQs over graph databases that uses weighted transducers to approximate paths from the query in two ways. The first extension is to answering approximate conjunctive 2-way regular path queries (C2RPQs) over graph databases and the second is to answering C2RPQs over ELH and DL-LiteR ontologies. We provide results on the computational complexity of the underlying reasoning problems and devise approximate query answering algorithms.
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Russo, David, Daniel M. Tartakovsky, and Shlomo P. Neuman. Development of Predictive Tools for Contaminant Transport through Variably-Saturated Heterogeneous Composite Porous Formations. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7592658.bard.

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The vadose (unsaturated) zone forms a major hydrologic link between the ground surface and underlying aquifers. To understand properly its role in protecting groundwater from near surface sources of contamination, one must be able to analyze quantitatively water flow and contaminant transport in variably saturated subsurface environments that are highly heterogeneous, often consisting of multiple geologic units and/or high and/or low permeability inclusions. The specific objectives of this research were: (i) to develop efficient and accurate tools for probabilistic delineation of dominant geologic features comprising the vadose zone; (ii) to develop a complementary set of data analysis tools for discerning the fractal properties of hydraulic and transport parameters of highly heterogeneous vadose zone; (iii) to develop and test the associated computational methods for probabilistic analysis of flow and transport in highly heterogeneous subsurface environments; and (iv) to apply the computational framework to design an “optimal” observation network for monitoring and forecasting the fate and migration of contaminant plumes originating from agricultural activities. During the course of the project, we modified the third objective to include additional computational method, based on the notion that the heterogeneous formation can be considered as a mixture of populations of differing spatial structures. Regarding uncertainly analysis, going beyond approaches based on mean and variance of system states, we succeeded to develop probability density function (PDF) solutions enabling one to evaluate probabilities of rare events, required for probabilistic risk assessment. In addition, we developed reduced complexity models for the probabilistic forecasting of infiltration rates in heterogeneous soils during surface runoff and/or flooding events Regarding flow and transport in variably saturated, spatially heterogeneous formations associated with fine- and coarse-textured embedded soils (FTES- and CTES-formations, respectively).We succeeded to develop first-order and numerical frameworks for flow and transport in three-dimensional (3-D), variably saturated, bimodal, heterogeneous formations, with single and dual porosity, respectively. Regarding the sampling problem defined as, how many sampling points are needed, and where to locate them spatially in the horizontal x₂x₃ plane of the field. Based on our computational framework, we succeeded to develop and demonstrate a methdology that might improve considerably our ability to describe quntitaively the response of complicated 3-D flow systems. The results of the project are of theoretical and practical importance; they provided a rigorous framework to modeling water flow and solute transport in a realistic, highly heterogeneous, composite flow system with uncertain properties under-specified by data. Specifically, they: (i) enhanced fundamental understanding of the basic mechanisms of field-scale flow and transport in near-surface geological formations under realistic flow scenarios, (ii) provided a means to assess the ability of existing flow and transport models to handle realistic flow conditions, and (iii) provided a means to assess quantitatively the threats posed to groundwater by contamination from agricultural sources.
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