82 research outputs found

    A statistical and clustering study on Youtube 2D and 3D video recommendation graph

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    Direction of arrival estimation using robust complex Lasso

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    The Lasso (Least Absolute Shrinkage and Selection Operator) has been a popular technique for simultaneous linear regression estimation and variable selection. In this paper, we propose a new novel approach for robust Lasso that follows the spirit of M-estimation. We define MM-Lasso estimates of regression and scale as solutions to generalized zero subgradient equations. Another unique feature of this paper is that we consider complex-valued measurements and regression parameters, which requires careful mathematical characterization of the problem. An explicit and efficient algorithm for computing the MM-Lasso solution is proposed that has comparable computational complexity as state-of-the-art algorithm for computing the Lasso solution. Usefulness of the MM-Lasso method is illustrated for direction-of-arrival (DoA) estimation with sensor arrays in a single snapshot case.Comment: Paper has appeared in the Proceedings of the 10th European Conference on Antennas and Propagation (EuCAP'2016), Davos, Switzerland, April 10-15, 201

    Multichannel sparse recovery of complex-valued signals using Huber's criterion

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    In this paper, we generalize Huber's criterion to multichannel sparse recovery problem of complex-valued measurements where the objective is to find good recovery of jointly sparse unknown signal vectors from the given multiple measurement vectors which are different linear combinations of the same known elementary vectors. This requires careful characterization of robust complex-valued loss functions as well as Huber's criterion function for the multivariate sparse regression problem. We devise a greedy algorithm based on simultaneous normalized iterative hard thresholding (SNIHT) algorithm. Unlike the conventional SNIHT method, our algorithm, referred to as HUB-SNIHT, is robust under heavy-tailed non-Gaussian noise conditions, yet has a negligible performance loss compared to SNIHT under Gaussian noise. Usefulness of the method is illustrated in source localization application with sensor arrays.Comment: To appear in CoSeRa'15 (Pisa, Italy, June 16-19, 2015). arXiv admin note: text overlap with arXiv:1502.0244

    Π­ΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΎΠ΅ исслСдованиС систСмы ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ Π½Π° основС FBMC/OQAM

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    Introduction. This paper investigates a transmission system based on FBMC/OQAM multiplexing. This system is characterized by a high spectral efficiency, thereby attracting interest as an alternative transmission method in future wireless mobile communication standards. However, a disadvantage of the system is the high complexity of signal processing. There are numerous publications that study the FBMC/OQAM system from a theoretical perspective. This paper presents an experimental study of a transmission system based on FBMC/OQAM.Aim. Verification of a transmission system based on FBMC/OQAM multiplexing in a wireless channel.Materials and methods. Computer simulation modeling in Matlab and experimental research using Keysight and Rohde & Schwarz certified measuring instruments.Results. A model of synthesis and signal processing was developed, and a frame structure was proposed. The processing included synchronization, since the study was carried out in a wireless double-dispersive channel. Time synchronization was provided by the method of time-domain correlation. A preamble consisting of two symbols was used for CFO compensation. Channel estimation in FBMC/OQAM was conducted by pilot symbols spread over the time-frequency domain, a method with an auxiliary pilot to compensate for intrinsic interference, as well as Zero Forcing and a linear interpolator. As a result, dependences of the bit error rate on the Eb/N0 in various channels were obtained. An error rate of 10βˆ’4 was achieved under the Eb/N0 equal to 13.4 dB, 15.3 dB and 20.9 dB in the first, second and third channel, respectively.Conclusion. A FBMC/OQAM-based transmission system with a linear equalizer can operate without a cyclic prefix in a multipath wireless channel, providing comparable noise immunity to OFDM-CP. Long frames should be used to obtain greater spectral efficiency, due to the presence of a transition zone at the beginning and end of the FBMC/OQAM frame.Π’Π²Π΅Π΄Π΅Π½ΠΈΠ΅. Данная Ρ€Π°Π±ΠΎΡ‚Π° посвящСна исслСдованию систСмы ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ Π½Π° основС ΠΌΡƒΠ»ΡŒΡ‚ΠΈΠΏΠ»Π΅ΠΊΡΠΈΡ€ΠΎΠ²Π°Π½ΠΈΡ FBMC/OQAM. ΠΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΡΡ‚ΡŒ исслСдования связана с высокой ΡΠΏΠ΅ΠΊΡ‚Ρ€Π°Π»ΡŒΠ½ΠΎΠΉ ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒΡŽ Π΄Π°Π½Π½ΠΎΠΉ систСмы, благодаря ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΉ ΠΎΠ½Π° рассматриваСтся ΠΊΠ°ΠΊ Π°Π»ΡŒΡ‚Π΅Ρ€Π½Π°Ρ‚ΠΈΠ²Π½Ρ‹ΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ Π² Π±ΡƒΠ΄ΡƒΡ‰ΠΈΡ… стандартах бСспроводной мобильной связи. Однако нСдостатком систСмы являСтся высокая ΡΠ»ΠΎΠΆΠ½ΠΎΡΡ‚ΡŒ ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ сигналов. Π‘Ρ€Π΅Π΄ΠΈ отСчСствСнных ΠΈ Π·Π°Ρ€ΡƒΠ±Π΅ΠΆΠ½Ρ‹Ρ… ΠΏΡƒΠ±Π»ΠΈΠΊΠ°Ρ†ΠΈΠΉ встрСчаСтся мноТСство Ρ€Π°Π±ΠΎΡ‚ с тСорСтичСским исслСдованиСм систСмы FBMC/OQAM. Π’ Π΄Π°Π½Π½ΠΎΠΉ ΡΡ‚Π°Ρ‚ΡŒΠ΅ прСдставлСны Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ исслСдования систСмы ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ Π½Π° Π΅Π΅ основС.ЦСль Ρ€Π°Π±ΠΎΡ‚Ρ‹. ВСрификация ΠΌΠΎΠ΄Π΅Π»ΠΈ систСмы ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ Π΄Π°Π½Π½Ρ‹Ρ… Π½Π° основС FBMC/OQAM Π² бСспроводном ΠΊΠ°Π½Π°Π»Π΅ связи.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΠ΅Ρ‚ΡΡ ΠΌΠ΅Ρ‚ΠΎΠ΄ ΠΈΠΌΠΈΡ‚Π°Ρ†ΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½ΠΎΠ³ΠΎ модСлирования Π² срСдС Matlab ΠΈ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½ΠΎΠ΅ исслСдованиС с использованиСм сСртифицированного ΠΈΠ·ΠΌΠ΅Ρ€ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ оборудования Keysight ΠΈ Rohde & Schwarz.Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π‘Ρ‹Π»Π° Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π° модСль формирования ΠΈ ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ сигнала, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π° структура  ΠΊΠ°Π΄Ρ€Π°.Β  ΠŸΠΎΠΊΠ°Π΄Ρ€ΠΎΠ²Π°ΡΒ  ΠΎΠ±Ρ€Π°Π±ΠΎΡ‚ΠΊΠ°Β  Π²Ρ‹ΠΏΠΎΠ»Π½ΡΠ»Π°ΡΡŒΒ  с  ΡƒΡ‡Π΅Ρ‚ΠΎΠΌΒ  Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠΉΒ  ΠΈΒ  частотной  синхронизации,Β  ΠΏΠΎΡΠΊΠΎΠ»ΡŒΠΊΡƒΒ  исслСдованиС  ΠΏΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒΒ  Π²Β  бСспроводном  ΠΊΠ°Π½Π°Π»Π΅Β  с  частотно-Π²Ρ€Π΅ΠΌΠ΅Π½Π½Ρ‹ΠΌΒ  рассСяниСм.Β  ВрСмСнная синхронизация ΠΎΠ±Π΅ΡΠΏΠ΅Ρ‡ΠΈΠ²Π°Π»Π°ΡΡŒ коррСляционным ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ Π²ΠΎ Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠΉ области. Для компСнсации  рассогласования  ΠΎΠΏΠΎΡ€Π½Ρ‹Ρ…Β  Π³Π΅Π½Π΅Ρ€Π°Ρ‚ΠΎΡ€ΠΎΠ²Β  ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΠ»Π°ΡΡŒΒ  ΠΎΡ†Π΅Π½ΠΊΠ°Β  с  ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽΒ  ΠΏΡ€Π΅Π°ΠΌΠ±ΡƒΠ»Ρ‹,Β  состоящСй ΠΈΠ· Π΄Π²ΡƒΡ… символов. Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ использовалась ΠΎΡ†Π΅Π½ΠΊΠ° ΠΊΠ°Π½Π°Π»Π° ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ Zero Forcing, Π° Ρ‚Π°ΠΊΠΆΠ΅ эквалайзСр с Π»ΠΈΠ½Π΅ΠΉΠ½Ρ‹ΠΌΒ  интСрполятором.Β  Для  ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚Π½ΠΎΠΉΒ  ΠΎΡ†Π΅Π½ΠΊΠΈΒ  ΠΊΠ°Π½Π°Π»Π°Β  Π²Β  FBMC/OQAMΒ  использовались  ΠΏΠΈΠ»ΠΎΡ‚Π½Ρ‹Π΅ символы, распрСдСлСнныС ΠΏΠΎ всСй частотно-Π²Ρ€Π΅ΠΌΠ΅Π½Π½ΠΎΠΉ сСткС, Π° Ρ‚Π°ΠΊΠΆΠ΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ с Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ ΠΏΠΈΠ»ΠΎΡ‚ΠΎΠΌ для компСнсации мСТканальной ΠΈΠ½Ρ‚Π΅Ρ€Ρ„Π΅Ρ€Π΅Π½Ρ†ΠΈΠΈ. Π’ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π΅ Ρ€Π°Π±ΠΎΡ‚Ρ‹ ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Ρ‹ зависимости коэффициСнта Π±ΠΈΡ‚ΠΎΠ²Ρ‹Ρ… ошибок ΠΎΡ‚ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΡ энСргии, приходящСйся Π½Π° Π±ΠΈΡ‚ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, ΠΊ энСргии ΡˆΡƒΠΌΠ° Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ…Β  ΠΊΠ°Π½Π°Π»Π°Ρ….Β  Достигнут  коэффициСнт  ошибок  10βˆ’4Β  ΠΏΡ€ΠΈΒ  ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΡΡ…Β  энСргии,Β  приходящСйся  Π½Π°Β  Π±ΠΈΡ‚ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, ΠΊ мощности ΡˆΡƒΠΌΠ°, Ρ€Π°Π²Π½Ρ‹Ρ… 13.4 Π΄Π‘ Π² ΠΏΠ΅Ρ€Π²ΠΎΠΌ ΠΊΠ°Π½Π°Π»Π΅, 15.3 Π΄Π‘ Π²ΠΎ Π²Ρ‚ΠΎΡ€ΠΎΠΌ ΠΈ 20.9 Π΄Π‘ Π² Ρ‚Ρ€Π΅Ρ‚ΡŒΠ΅ΠΌ. Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. БистСма ΠΏΠ΅Ρ€Π΅Π΄Π°Ρ‡ΠΈ Π½Π° основС FBMC/OQAM с Π»ΠΈΠ½Π΅ΠΉΠ½Ρ‹ΠΌ эквалайзСром ΠΌΠΎΠΆΠ΅Ρ‚ Ρ€Π°Π±ΠΎΡ‚Π°Ρ‚ΡŒ Π±Π΅Π· цикличСского  прСфикса  Π²Β  бСспроводном  ΠΊΠ°Π½Π°Π»Π΅Β  связи  с  ΠΌΠ½ΠΎΠ³ΠΎΠ»ΡƒΡ‡Π΅Π²ΠΎΡΡ‚ΡŒΡŽ,Β  обСспСчивая  ΡΡ€Π°Π²Π½ΠΈΠΌΡƒΡŽΒ  с OFDM-CPΒ  ΠΏΠΎΠΌΠ΅Ρ…ΠΎΡƒΡΡ‚ΠΎΠΉΡ‡ΠΈΠ²ΠΎΡΡ‚ΡŒ.Β  Для  получСния  большСй  ΡΠΏΠ΅ΠΊΡ‚Ρ€Π°Π»ΡŒΠ½ΠΎΠΉΒ  эффСктивности  Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΒ  ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Ρ‚ΡŒ Π΄Π»ΠΈΠ½Π½Ρ‹Π΅ ΠΊΠ°Π΄Ρ€Ρ‹, ΠΏΠΎΡΠΊΠΎΠ»ΡŒΠΊΡƒ Π² Π½Π°Ρ‡Π°Π»Π΅ ΠΈ ΠΊΠΎΠ½Ρ†Π΅ ΠΊΠ°Π΄Ρ€Π° FBMC/OQAM имССтся пСрСходная Π·ΠΎΠ½Π°

    The Graph Curvature Calculator and the curvatures of cubic graphs

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    We classify all cubic graphs with either non-negative Ollivier-Ricci curvature or non-negative Bakry-\'Emery curvature everywhere. We show in both curvature notions that the non-negatively curved graphs are the prism graphs and the M\"obius ladders. We also highlight an online tool for calculating the curvature of graphs under several variants of these curvature notions that we use in the classification. As a consequence of the classification result we show, that non-negatively curved cubic expanders do not exist
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