scholarly journals Hierarchical Cubical Tensor Decomposition through Low Complexity Orthogonal Transforms

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 864 ◽  
Author(s):  
Roumen K. Kountchev ◽  
Rumen P. Mironov ◽  
Roumiana A. Kountcheva
Keyword(s):  
Computational Complexity ◽  
Tensor Decomposition ◽  
Low Complexity ◽  
High Energy ◽  
Energy Concentration ◽  
Hadamard Transform ◽  
Discrete Wavelet ◽  
Comparison Results ◽  
Orthogonal Transforms ◽  
3D Discrete Wavelet Transform

In this work, new approaches are proposed for the 3D decomposition of a cubical tensor of size N × N × N for N = 2n through hierarchical deterministic orthogonal transforms with low computational complexity, whose kernels are based on the Walsh-Hadamard Transform (WHT) and the Complex Hadamard Transform (CHT). On the basis of the symmetrical properties of the real and complex Walsh-Hadamard matrices are developed fast computational algorithms whose computational complexity is compared with that of the famous deterministic transforms: the 3D Fast Fourier Transform, the 3D Discrete Wavelet Transform and the statistical Hierarchical Tucker decomposition. The comparison results show the lower computational complexity of the offered algorithms. Additionally, they ensure the high energy concentration of the original tensor into a small number of coefficients of the so calculated transformed spectrum tensor. The main advantage of the proposed algorithms is the reduction of the needed calculations due to the low number of hierarchical levels compared to the significant number of iterations needed to achieve the required decomposition accuracy based on the statistical methods. The choice of the 3D hierarchical decomposition is defined by the requirements and limitations related to the corresponding application area.

Approaches to Comparison and Their Influence on Social Comparison

2019 ◽  
pp. 430-442
Author(s):  
Arthur B. Markman
Keyword(s):  
Cognitive Psychology ◽  
Computational Complexity ◽  
Social Comparison ◽  
Mental Representation ◽  
Spatial Models ◽  
Structural Models ◽  
Low Complexity ◽  
Comparison Process ◽  
Social Settings ◽  
Computationally Intensive

Cognitive psychology identifies different assumptions about the mental representations that form the basis of theories of comparison. Each representation requires a different process to generate a comparison, and both the computational complexity and the output of the different processes differ. Spatial models require a low-complexity process but only reveal the distance between points representing individuals. Featural models are more intensive than spatial comparisons but provide access to particular commonalities and differences. Structural models are more computationally intensive but support a distinction between alignable and nonalignable differences. Social comparison theories make assumptions about how knowledge is represented, but they are rarely explicit about the type of comparison process that is likely to be involved. The merging of work on social comparison with more explicit cognitive science theories of comparison science has the potential to both identify gaps in the literature and expand our knowledge about how comparison operates in social settings. This chapter first discusses the concept of mental representation and then addresses spatial models of comparison, featured models of comparison, structural models of comparison, transformation models. The chapter concludes with a discussion of similarity models and social comparison.

scholarly journals Wi-Fi Backscatter System with Tag Sensors Using Multi-Antennas for Increased Data Rate and Reliability

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1314
Author(s):  
Taeoh Kim ◽  
Hyobeen Park ◽  
Yunho Jung ◽  
Seongjoo Lee
Keyword(s):  
Computational Complexity ◽  
Euclidean Distance ◽  
Multiple Antennas ◽  
Power Level ◽  
Low Complexity ◽  
Data Rate ◽  
Threshold Method ◽  
Channel State ◽  
Distance Method ◽  
Ber Performance

In this paper, we propose tag sensor using multi-antennas in a Wi-Fi backscatter system, which results in an improved data rate or reliability of the signal transmitted from a tag sensor to a reader. The existing power level modulation method, which is proposed to improve data rate in a Wi-Fi backscatter system, has low reliability due to the reduced distance between symbols. To address this problem, we propose a Wi-Fi backscatter system that obtains channel diversity by applying multiple antennas. Two backscatter methods are described for improving the data rate or reliability in the proposed system. In addition, we propose three low complexity demodulation methods to address the high computational complexity problem caused by multiple antennas: (1) SET (subcarrier energy-based threshold) method, (2) TCST (tag’s channel state-based threshold) method, and (3) SED (similar Euclidean distance) method. In order to verify the performance of the proposed backscatter method and low complexity demodulation schemes, the 802.11 TGn (task group n) channel model was utilized in simulation. In this paper, the proposed tag sensor structure was compared with existing methods using only sub-channels with a large difference in received CSI (channel state information) values or adopting power-level modulation. The proposed scheme showed about 10 dB better bit error rate (BER) performance and throughput. Also, proposed low complexity demodulation schemes were similar in BER performance with a difference of up to 1 dB and the computational complexity was reduced by up to 60% compared to the existing Euclidean distance method.

scholarly journals PSX-11 Effects of lamb’s breed and energy concentration of diet on nutrient digestibility and growth performance

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 466-467
Author(s):  
Anderson Pereira ◽  
Hyane Lima ◽  
Leonardo M Freitas ◽  
Henrique Parente ◽  
Antônio Lima ◽  
...  
Keyword(s):  
Block Design ◽  
High Energy ◽  
Nutrient Digestibility ◽  
Low Energy ◽  
Energy Concentration ◽  
Metabolic Adaptation ◽  
Fat Depots ◽  
Arid Conditions ◽  
Food Shortages ◽  
Subcutaneous Adipose

Abstract The accumulation of subcutaneous adipose deposits occurs in many genotypes of animals adapted to tropical arid conditions. In sheep, good adaptation of fat-tailed sheep breeds, as Rabo Largo, to arid environmental conditions and food shortages can also undergo digestive and metabolic adaptation, including a greater capacity for digestion of poor roughage. Forty lambs (18±3 kg initial BW) were assigned in a randomized completely block design with a 2x2 factorial arrangement of treatments, with 2 breeds – B (Santa Inês- SI and Rabo Largo-RL) and 2 diets – D (low and high energy), resulting in four treatments: SILE, SIHE, RLLE and RLHE. Lambs (20 SI and 20 RL) were individually penned during 43 d and fed 1 of 2 diets with different concentrate: roughage ratio: low energy-LE (with 70% hay and 10.7% CP, DM basis) and high energy-HE (70% concentrate and 12.7% CP, DM basis). At the end of performance period, the intake was recorded and total feces collected for 5 d. Data were analyzed by ANOVA and when a significant effect (P < 0.05) was found, means were compared using Tukey’s method. The G:F ratio had effect only for D (0.12, 0.22, 0.10 and 0.24 for SILE, SIHE, RLLE and RLHE, respectively). There was observed an effect of D and B (P < 0.05) for all variables related to growth and digestibility, with higher means for SI and HE, except for NDF intake (495, 322, 340 and 268 g/d for SILE, SIHE, RLLE and RLHE, respectively) and NDF digestibility (63, 58, 59 and 45% for SILE, SIHE, RLLE and RLHE). It was observed an interaction D x B on CP intake, NDF intake and NDF digestibility. Breed and diets affected the performance and digestibility of lambs. However, RLLE increased the NDF digestibility, but decreased the ADG, suggesting higher fat depots accumulation.

scholarly journals Milk Urea Concentration in Dairy Sheep: Accounting for Dietary Energy Concentration

Animals ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 1118 ◽  
Author(s):  
Valeria Giovanetti ◽  
Filippo Boe ◽  
Mauro Decandia ◽  
Giovanni Cristoforo Bomboi ◽  
Alberto Stanislao Atzori ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Energy Content ◽  
High Energy ◽  
Urea Concentration ◽  
Energy Concentration ◽  
Net Energy ◽  
Dietary Energy ◽  
Dairy Sheep ◽  
Dairy Ewes ◽  
Milk Urea

In dairy sheep milk urea concentration (MUC) is highly and positively correlated with dietary crude protein (CP) content and, to a lesser extent, with protein intake. However, the effect of dietary energy and carbohydrate sources on MUC of lactating ewes is not clear. Thus, the objective of this study was to assess the effects of diets differing in energy concentration and carbohydrate sources on MUC values in lactating dairy ewes. Two experiments were conducted (experiment 1, E1, and experiment 2, E2) on Sarda ewes in mid and late lactation kept in metabolic cages for 23 d. In both experiments, homogeneous groups of five ewes were submitted to four (in E1) or three (in E2) dietary treatments, consisting of pelleted diets ranging from low energy (high-fiber diets: 1.2–1.4 Mcal of net energy for lactation (NEL)) to high energy (high-starch diets: 1.7–1.9 Mcal of NEL) contents, but with a similar CP concentration (18.4% dry matter (DM), on average). Each diet had a different main ingredient as follows: corn flakes, barley meal, beet pulp, or corn cobs in E1 and corn meal, dehydrated alfalfa, or soybean hulls in E2. Regression analysis using treatment means from both experiments showed that the best predictor of MUC (mg/100 mL) was the dietary NEL (Mcal/kg DM, MUC = 127.6 − 51.2 × NEL, R2 = 0.85, root of the mean squared error (rmse) = 4.36, p < 0.001) followed by the ratio CP/NEL (g/Mcal, MUC = −14.9 + 0.5 × CP/ NEL, R2 = 0.83, rmse = 4.63, p < 0.001). A meta-regression of an extended database on stall-fed dairy ewes, including the E1 and E2 experimental data (n = 44), confirmed the predictive value of the CP/ NEL ratio, which resulted as the best single predictor of MUC (MUC = −13.7 + 0.5 × CP/NEL, R2 = 0.93, rmse = 3.30, p < 0.001), followed by dietary CP concentration (MUC = −20.7 + 3.7 × CP, R2 = 0.82, rmse = 4.89, p < 0.001). This research highlights that dietary energy content plays a pivotal role in modulating the relationship between MUC and dietary CP concentration in dairy sheep.

scholarly journals A Novel Iterative Discrete Estimation Algorithm for Low-Complexity Signal Detection in Uplink Massive MIMO Systems

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 980 ◽  
Author(s):  
Hui Feng ◽  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing
Keyword(s):  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Damping Factor ◽  
Mimo Detection ◽  
Discrete Estimation

In this paper, a novel iterative discrete estimation (IDE) algorithm, which is called the modified IDE (MIDE), is proposed to reduce the computational complexity in MIMO detection in uplink massive MIMO systems. MIDE is a revision of the alternating direction method of multipliers (ADMM)-based algorithm, in which a self-updating method is designed with the damping factor estimated and updated at each iteration based on the Euclidean distance between the iterative solutions of the IDE-based algorithm in order to accelerate the algorithm’s convergence. Compared to the existing ADMM-based detection algorithm, the overall computational complexity of the proposed MIDE algorithm is reduced from O N t 3 + O N r N t 2 to O N t 2 + O N r N t in terms of the number of complex-valued multiplications, where Ntand Nr are the number of users and the number of receiving antennas at the base station (BS), respectively. Simulation results show that the proposed MIDE algorithm performs better in terms of the bit error rate (BER) than some recently-proposed approximation algorithms in MIMO detection of uplink massive MIMO systems.

Genetic algorithm based automated threshold estimation in translation invariant wavelet transform for denoising PD signal

2015 ◽  
Vol 34 (4) ◽  
pp. 1252-1269 ◽  
Author(s):  
R.V. Maheswari ◽  
B. Vigneshwaran ◽  
L. Kalaivani
Keyword(s):  
Genetic Algorithm ◽  
Wavelet Transform ◽  
Computational Complexity ◽  
Condition Monitoring ◽  
Random Noise ◽  
Life Time ◽  
Discrete Wavelet ◽  
Statistical Parameters ◽  
Translation Invariant ◽  
Content Type

Purpose – The purpose of this paper is to investigate the condition of insulation in high-voltage equipments using partial discharge (PD) measurements. It proposes the methods to eliminate several noises like white noise, random noise and discrete spectral interferences which severely pollutes the PD signals. The study aims to remove these noises from the PD signal effectively by preserving the signal features. Design/methodology/approach – This paper employs fast Fourier transform, discrete wavelet transform and translational invariant wavelet transform (TIWT) for denoising the PD signals. The simulated damped exponential pulse and damped oscillatory pulse with low- and high-level noises and a measured PD signal are considered for this analysis. The conventional wavelet denoising approach is also improved by estimating the automated global optimum threshold value using genetic algorithm (GA). The statistical parameters are evaluated and compared. Among these methods, GA-based TIWT approach provides robustness and reduces computational complexity. Findings – This paper provides effective condition monitoring of power apparatus using GA-based TIWT approach. This method provides the low value of mean square error, pulse amplitude distortion and also high reduction in noise level due to its robustness and reduced computational complexity. It suggests that this approach works well for both signals immersed in noise as well as for noise immersed in signals. Research limitations/implications – Because of the chosen PD signals, the research results may lack for multiple discharges. Therefore, researchers are encouraged to test the proposed propositions further. Practical implications – The paper includes implication for the development of online testing for equipment analysis and diagnostics during normal operating condition. Corrective actions can be planned and implemented, resulting in reduced unscheduled downtime. Social implications – This PD-based analysis often present well in advance of insulation failure, asset managers can monitor it over time and make informed strategic decisions regarding the repair or replacement of the equipment. These predictive diagnostics help society to prioritize investments before an unexpected outage occurs. Originality/value – This paper provides an enhanced study of condition monitoring of HV power apparatus by which life time of insulation can be increased by taking preventive measures.

scholarly journals Low-Complexity Detection Algorithms for Spatial Modulation MIMO Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Xinhe Zhang ◽  
Yuehua Zhang ◽  
Chang Liu ◽  
Hanzhong Jia
Keyword(s):  
Computational Complexity ◽  
Mimo Systems ◽  
Optimal Solution ◽  
Low Complexity ◽  
Search Tree ◽  
Spatial Modulation ◽  
Algorithm Analysis ◽  
Detection Algorithms ◽  
Search Order ◽  
Ber Performance

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.

scholarly journals Neural Network Approach to MPPT Control and Irradiance Estimation

2020 ◽  
Vol 10 (15) ◽  
pp. 5051
Author(s):  
Žarko Zečević ◽  
Maja Rolevski
Keyword(s):  
Neural Network ◽  
Computational Complexity ◽  
Low Complexity ◽  
Maximum Power ◽  
Photovoltaic Module ◽  
Neural Network Approach ◽  
Point Tracking ◽  
The Neural Network ◽  
Power Point ◽  
The One

Photovoltaic (PV) modules require maximum power point tracking (MPPT) algorithms to ensure that the amount of power extracted is maximized. In this paper, we propose a low-complexity MPPT algorithm that is based on the neural network (NN) model of the photovoltaic module. Namely, the expression for the output current of the NN model is used to derive the analytical, iterative rules for determining the maximal power point (MPP) voltage and irradiance estimation. In this way, the computational complexity is reduced compared to the other NN-based MPPT methods, in which the optimal voltage is predicted directly from the measurements. The proposed algorithm cannot instantaneously determine the optimal voltage, but it contains a tunable parameter for controlling the trade-off between the tracking speed and computational complexity. Numerical results indicate that the relative error between the actual maximum power and the one obtained by the proposed algorithm is less than 0.1%, which is up to ten times smaller than in the available algorithms.

scholarly journals PCA-Aided Linear Precoding in Massive MIMO Systems with Imperfect CSI

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Van-Khoi Dinh ◽  
Minh-Tuan Le ◽  
Vu-Duc Ngo ◽  
Chi-Hieu Ta
Keyword(s):  
Principal Component Analysis ◽  
Computational Complexity ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Principal Component ◽  
Low Complexity ◽  
Component Analysis ◽  
Linear Precoding ◽  
Block Diagonalization

In this paper, a low-complexity linear precoding algorithm based on the principal component analysis technique in combination with the conventional linear precoders, called Principal Component Analysis Linear Precoder (PCA-LP), is proposed for massive MIMO systems. The proposed precoder consists of two components: the first one minimizes the interferences among neighboring users and the second one improves the system performance by utilizing the Principal Component Analysis (PCA) technique. Numerical and simulation results show that the proposed precoder has remarkably lower computational complexity than its low-complexity lattice reduction-aided regularized block diagonalization using zero forcing precoding (LC-RBD-LR-ZF) and lower computational complexity than the PCA-aided Minimum Mean Square Error combination with Block Diagonalization (PCA-MMSE-BD) counterparts while its bit error rate (BER) performance is comparable to those of the LC-RBD-LR-ZF and PCA-MMSE-BD ones.

scholarly journals Review on Recent Developments in Laser Driven Inertial Fusion

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
M. Ghoranneviss ◽  
A. Salar Elahi
Keyword(s):  
Fusion Energy ◽  
Laser Pulses ◽  
High Energy ◽  
Energy Concentration ◽  
Inertial Fusion ◽  
Short Pulses ◽  
Confinement Fusion ◽  
Recent Developments ◽  
Very High Energy ◽  
High Energy Concentration

Discovery of the laser in 1960 hopes were based on using its very high energy concentration within very short pulses of time and very small volumes for energy generation from nuclear fusion as “Inertial Fusion Energy” (IFE), parallel to the efforts to produce energy from “Magnetic Confinement Fusion” (MCF), by burning deuterium-tritium (DT) in high temperature plasmas to helium. Over the years the fusion gain was increased by a number of magnitudes and has reached nearly break-even after numerous difficulties in physics and technology had been solved. After briefly summarizing laser driven IFE, we report how the recently developed lasers with pulses of petawatt power and picosecond duration may open new alternatives for IFE with the goal to possibly ignite solid or low compressed DT fuel thereby creating a simplified reactor scheme. Ultrahigh acceleration of plasma blocks after irradiation of picosecond (PS) laser pulses of around terawatt (TW) power in the range of 1020 cm/s2was discovered by Sauerbrey (1996) as measured by Doppler effect where the laser intensity was up to about 1018 W/cm2. This is several orders of magnitude higher than acceleration by irradiation based on thermal interaction of lasers has produced.

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