High-Performance Tool for the Test of Long-Memory and Self-Similarity

2014 ◽  
pp. 93-114 ◽  
Author(s):  
Julio Ramírez-Pacheco ◽  
Deni Torres-Román ◽  
Homero Toral-Cruz ◽  
Leopoldo Vargas
Keyword(s):  
Long Memory ◽  
High Performance ◽  
Self Similarity

A study on the variations in long-range dependence of solar energetic particles during different solar cycles

2018 ◽  
Vol 13 (S340) ◽  
pp. 47-48
Author(s):  
V. Vipindas ◽  
Sumesh Gopinath ◽  
T. E. Girish
Keyword(s):  
Long Range ◽  
Long Memory ◽  
Hurst Exponent ◽  
High Energy ◽  
Energetic Particles ◽  
Solar Energetic Particles ◽  
Long Range Dependence ◽  
Solar Cycles ◽  
Self Similarity ◽  
High Energy Particles

AbstractSolar Energetic Particles (SEPs) are high-energy particles ejected by the Sun which consist of protons, electrons and heavy ions having energies in the range of a few tens of keVs to several GeVs. The statistical features of the solar energetic particles (SEPs) during different periods of solar cycles are highly variable. In the present study we try to quantify the long-range dependence (or long-memory) of the solar energetic particles during different periods of solar cycle (SC) 23 and 24. For stochastic processes, long-range dependence or self-similarity is usually quantified by the Hurst exponent. We compare the Hurst exponent of SEP proton fluxes having energies (>1MeV to >100 MeV) for different periods, which include both solar maximum and minimum years, in order to find whether SC-dependent self-similarity exist for SEP flux.

High performance pedestrian detector using local segmentation self-similarity in complex scenes

2014 ◽  
Vol 24 (1) ◽  
pp. 93-101 ◽  
Author(s):  
Hongbo Gao ◽  
Hongyu Wang ◽  
Xiaokai Liu ◽  
Xiaorui Ma
Keyword(s):  
High Performance ◽  
Self Similarity ◽  
Complex Scenes

scholarly journals Focusing on Detail: Deep Hashing Based on Multiple Region Details (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13991-13992
Author(s):  
Quan Zhou ◽  
Xiushan Nie ◽  
Yang Shi ◽  
Xingbo Liu ◽  
Yilong Yin
Keyword(s):  
High Performance ◽  
Original Data ◽  
Multimedia Data ◽  
Self Similarity ◽  
Imbalance Problem ◽  
Retrieval Efficiency ◽  
Loss Term ◽  
Image Details ◽  
Hash Codes ◽  
Local Image

Fast retrieval efficiency and high performance hashing, which aims to convert multimedia data into a set of short binary codes while preserving the similarity of the original data, has been widely studied in recent years. Majority of the existing deep supervised hashing methods only utilize the semantics of a whole image in learning hash codes, but ignore the local image details, which are important in hash learning. To fully utilize the detailed information, we propose a novel deep multi-region hashing (DMRH), which learns hash codes from local regions, and in which the final hash codes of the image are obtained by fusing the local hash codes corresponding to local regions. In addition, we propose a self-similarity loss term to address the imbalance problem (i.e., the number of dissimilar pairs is significantly more than that of the similar ones) of methods based on pairwise similarity.

scholarly journals On the 5G Communications: Fractal-Shaped Antennas for PPDR Applications

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mihai-Virgil Nichita ◽  
Maria-Alexandra Paun ◽  
Vladimir-Alexandru Paun ◽  
Viorel-Puiu Paun
Keyword(s):  
Standing Wave ◽  
High Performance ◽  
Disaster Relief ◽  
Dipole Antenna ◽  
Voltage Standing Wave Ratio ◽  
Antenna Design ◽  
Dipole Antennas ◽  
Self Similarity ◽  
Optimum Operation ◽  
Fractal Antennas

In this study, one method of using antennas based on fractals to cover few kinds of public protection and disaster relief (PPDR) communications was presented. Dedicated antenna forms, necessary for antenna design by 5G implementation, were enhanced to suit the requirements of specific applications. Employing fractal-shaped antennas have allowed us to accomplish all these actions, which request compact, conformal, and broadband high performance devices. Antennas derived from Koch’s curve fractals are studied. In order to implement PPDR communications in 5G technology, frequency bandwidths of importance have been carefully selected and properly included in the antenna developments under MATLAB environment. Important information necessary for antenna designers, such as 360 degrees directivity at various frequencies, the impedance (resistance and reactance) along the bandwidth of interest, as well as voltage standing wave ratio (VSWR) along the bandwidth of interest for dipole, one-iteration, and two-iteration Koch’s curves, respectively, have been obtained. The characteristic of directivity at selected frequencies is also highlighted. In order to maximize antenna parameters, this study has successfully proposed using fractal antennas, objects that use self-similarity property of fractals for optimum operation in several frequency ranges. For the studied antennas, we have obtained the following results regarding the maximum gains in dBi (which is the unit of the ratio between the gains of the antenna compared to the gain of an isotropic antenna). For the dipole antennas, the gains are 2.73 dBi and 4.76 dBi at 460 MHz and 770 MHz, respectively. The gains for one-iteration fractal Koch antenna are 6.91 dBi and 4.51 dBi at 460 MHz and 770 MHz, respectively, and finally, for two-iteration fractal Koch antenna, the gains are 4.91 dBi and 3.28 dBi at 460 MHz and 770 MHz, respectively. Moreover, the impedance along the bandwidth is approximately 360 Ohms for two-iteration fractal Koch antenna, 180 Ohms for one-iteration fractal Koch antenna, and 140 Ohms for dipole antenna, respectively.

Self-similarity of level-based wavepacket modeling of high-performance military aircraft noise

2016 ◽  
Vol 140 (4) ◽  
pp. 3097-3097
Author(s):  
Tracianne B. Neilsen ◽  
Kent L. Gee ◽  
Blaine M. Harker ◽  
Alan T. Wall ◽  
Michael M. James
Keyword(s):  
High Performance ◽  
Aircraft Noise ◽  
Military Aircraft ◽  
Self Similarity

scholarly journals Estimation of the self-similarity parameter in long memory processes

1970 ◽  
Vol 38 ◽  
pp. 32-37 ◽  
Author(s):  
MMA Sarker
Keyword(s):  
Long Memory ◽  
The Self ◽  
Similar Process ◽  
Long Range Dependence ◽  
Self Similarity ◽  
Similarity Parameter ◽  
Data Set ◽  
Memory Processes ◽  
Long Memory Processes ◽  
Self Similar

Long memory processes, where positive correlations between observations far apart in time and space decay very slowly to zero with increasing time lag, occur quite frequently in fields such as hydrology and economics. Stochastic processes that are invariant in distribution under judicious scaling of time and space, called self-similar process, can parsimoniously model the long-run properties of phenomena exhibiting long-range dependence. Four of the heuristic estimation approaches have been presented in this study so that the self-similarity parameter, H that gives the correlation structure in long memory processes, can be effectively estimated. Finally, the methods presented in this paper were applied to two observed time series, namely Nile River Data set and the VBR (Variable- Bit-Rate) data set. The estimated values of H for two data sets found from different methods suggest that all methods are not equally good for estimation. Keywords: Long memory process, long-range dependence, Self-similar process, Hurst Parameter, Gaussian noise. DOI: 10.3329/jme.v38i0.898 Journal of Mechanical Engineering Vol.38 Dec. 2007 pp.32-37  

scholarly journals Option Pricing under the Subordinated Market Models

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Longjin Lv ◽  
Changjuan Zheng ◽  
Luna Wang
Keyword(s):  
Brownian Motion ◽  
Option Pricing ◽  
Long Memory ◽  
Stock Price ◽  
Fractional Diffusion ◽  
Option Prices ◽  
European Options ◽  
Self Similarity ◽  
Market Models ◽  
Proposed Model

This paper aims to study option pricing problem under the subordinated Brownian motion. Firstly, we prove that the subordinated Brownian motion controlled by the fractional diffusion equation has many financial properties, such as self-similarity, leptokurtic, and long memory, which indicate that the fractional calculus can describe the financial data well. Then, we investigate the option pricing under the assumption that the stock price is driven by the subordinated Brownian motion. The closed-form pricing formula for European options is derived. In the comparison with the classic Black–Sholes model, we find the option prices become higher, and the “volatility smiles” phenomenon happens in the proposed model. Finally, an empirical analysis is performed to show the validity of these results.

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