Computationally Efficient Multisensor Fusion Estimation Algorithms

2010 ◽  
Vol 132 (2) ◽  
Author(s):  
Seokhyoung Lee ◽  
Vladimir Shin
Keyword(s):  
Computational Complexity ◽  
Computational Analysis ◽  
Approximation Scheme ◽  
Estimation Algorithm ◽  
Block Matrix ◽  
Cholesky Factorization ◽  
Computationally Efficient ◽  
Estimation Algorithms ◽  
Matrix Weights ◽  
Cross Covariance

This paper provides two computationally effective fusion estimation algorithms. The first algorithm is based on Cholesky factorization of a cross-covariance block matrix. This algorithm has low computational complexity and is equivalent to the standard composite fusion estimation algorithm as well. The second algorithm is based on a special approximation scheme for local cross-covariances. Such approximation is useful to compute matrix weights for fusion estimation in a multidimensional-multisensor environment. Subsequent computational analysis of the proposed fusion algorithms is presented with corresponding examples showing the low computational complexities of the new fusion estimation algorithms.

scholarly journals Cascade AOA Estimation Algorithm Based on Flexible Massive Antenna Array

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6797
Author(s):  
Tae-yun Kim ◽  
Suk-seung Hwang
Keyword(s):  
Computational Complexity ◽  
Antenna Array ◽  
Rapid Development ◽  
Estimation Algorithm ◽  
Signal Classification ◽  
Location Based Service ◽  
Angle Of Arrival ◽  
Multiple Signal Classification ◽  
Estimation Performance ◽  
Estimation Algorithms

The Angle-of-Arrival (AOA) has a variety of applications in civilian and military wireless communication fields. Due to the rapid development of the location-based service (LBS) industry, the importance of the AOA estimation technique has increased. Although a large antenna array is necessary to estimate accurate AOA information of many signals, the computational complexity of conventional AOA estimation algorithms, such as Multiple Signal Classification (MUSIC), is dramatically increased. In this paper, we propose a cascade AOA estimation algorithm employing CAPON and Beamspace MUSIC, based on a flexible (on/off) antenna array. First, this approach roughly finds AOA groups, including several signal AOAs using CAPON, by applying some of the antenna elements. Then, it estimates each signal AOA in the estimated AOA groups using Beamspace MUSIC by applying the full size of the antenna array. In addition to extremely low computational complexity, the proposed algorithm also has similar estimation performance to that of MUSIC. In particular, the proposed cascade AOA estimation algorithm is highly efficient when employing a massive antenna array. Representative computer simulation examples are provided to illustrate the AOA estimation performance of the proposed technique.

Efficient Motion Estimation Algorithms for Video Coding

2011 ◽  
Vol 225-226 ◽  
pp. 953-956 ◽  
Author(s):  
Ming Te Wu
Keyword(s):  
Computational Complexity ◽  
Motion Estimation ◽  
Video Coding ◽  
Estimation Algorithm ◽  
Motion Vectors ◽  
Estimation Algorithms ◽  
Objective Quality ◽  
Motion Estimation Algorithm ◽  
Partial Distortion

This work proposes an efficient motion estimation algorithm for video coding. The proposed method calculates the partial distortion by replacing a certain number pixels of each partial sub-macroblock. In addition to increase the probability of the rejection of unsuitable motion vectors without additional computations, the proposed approach reduce computational complexity significantly and obtains better objective quality than conventional motion estimation algorithms.

An Energy Efficient Estimation Algorithm for Wireless Sensor Network

2011 ◽  
Vol 216 ◽  
pp. 176-180
Author(s):  
Yong Ding ◽  
Yue Mei Su
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Estimation Algorithm ◽  
Efficient Estimation ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Current Energy

Wireless Sensor Networks functionality is closely related to network lifetime which depends on the energy consumption, so require energy- efficient protocols to improve the network lifetime. According to the analysis and summary of the current energy efficient estimation algorithms in wireless sensor network An energy-efficient algorithm is proposed,. Then this optimization algorithm proposed in the paper is adopted to improve the traditional diffusion routing protocol. Simulation results show that this algorithm is to effectively balance the network energy consumption, improve the network life-cycle and ensure the communication quality.

USING AN IMPROVED BEE MEMORY DIFFERENTIAL EVOLUTION ALGORITHM FOR PARAMETER ESTIMATION TO SIMULATE BIOCHEMICAL PATHWAYS

2014 ◽  
Vol 22 (01) ◽  
pp. 101-121 ◽  
Author(s):  
CHUII KHIM CHONG ◽  
MOHD SABERI MOHAMAD ◽  
SAFAAI DERIS ◽  
MOHD SHAHIR SHAMSIR ◽  
LIAN EN CHAI ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Estimation Algorithm ◽  
Convergence Time ◽  
Unknown Parameters ◽  
Estimation Algorithms ◽  
Bee Colony ◽  
De Algorithm ◽  
Cell Cycle Pathway ◽  
Parameter Values

When analyzing a metabolic pathway in a mathematical model, it is important that the essential parameters are estimated correctly. However, this process often faces few problems like when the number of unknown parameters increase, trapping of data in the local minima, repeated exposure to bad results during the search process and occurrence of noisy data. Thus, this paper intends to present an improved bee memory differential evolution (IBMDE) algorithm to solve the mentioned problems. This is a hybrid algorithm that combines the differential evolution (DE) algorithm, the Kalman filter, artificial bee colony (ABC) algorithm, and a memory feature. The aspartate and threonine biosynthesis pathway, and cell cycle pathway are the metabolic pathways used in this paper. For three production simulation pathways, the IBMDE managed to robustly produce the estimated optimal kinetic parameter values with significantly reduced errors. Besides, it also demonstrated faster convergence time compared to the Nelder–Mead (NM), simulated annealing (SA), the genetic algorithm (GA) and DE, respectively. Most importantly, the kinetic parameters that were generated by the IBMDE have improved the production rates of desired metabolites better than other estimation algorithms. Meanwhile, the results proved that the IBMDE is a reliable estimation algorithm.

Addressing pose estimation issues for machine vision based UAV autonomous serial refuelling

2007 ◽  
Vol 111 (1120) ◽  
pp. 389-396 ◽  
Author(s):  
G. Campa ◽  
M. R. Napolitano ◽  
M. Perhinschi ◽  
M. L. Fravolini ◽  
L. Pollini ◽  
...  
Keyword(s):  
Machine Vision ◽  
Pose Estimation ◽  
Estimation Algorithm ◽  
Computational Effort ◽  
Unmanned Aircraft ◽  
Light Sources ◽  
Estimation Algorithms ◽  
Trade Offs ◽  
Labeling Algorithms ◽  
Selection Of

Abstract This paper describes the results of an effort on the analysis of the performance of specific ‘pose estimation’ algorithms within a Machine Vision-based approach for the problem of aerial refuelling for unmanned aerial vehicles. The approach assumes the availability of a camera on the unmanned aircraft for acquiring images of the refuelling tanker; also, it assumes that a number of active or passive light sources – the ‘markers’ – are installed at specific known locations on the tanker. A sequence of machine vision algorithms on the on-board computer of the unmanned aircraft is tasked with the processing of the images of the tanker. Specifically, detection and labeling algorithms are used to detect and identify the markers and a ‘pose estimation’ algorithm is used to estimate the relative position and orientation between the two aircraft. Detailed closed-loop simulation studies have been performed to compare the performance of two ‘pose estimation’ algorithms within a simulation environment that was specifically developed for the study of aerial refuelling problems. Special emphasis is placed on the analysis of the required computational effort as well as on the accuracy and the error propagation characteristics of the two methods. The general trade offs involved in the selection of the pose estimation algorithm are discussed. Finally, simulation results are presented and analysed.

Nearby Phase Search Algorithm with Reduced Complexity for Higher Order QAM Formats

2013 ◽  
Vol 760-762 ◽  
pp. 1869-1873
Author(s):  
Li Min Xia ◽  
Xian Zhou ◽  
Dong Yan ◽  
Na Na Zhang ◽  
Xiao Yun Wu
Keyword(s):  
Computational Complexity ◽  
Bit Error Rate ◽  
High Speed ◽  
Optical Transmission ◽  
Search Algorithm ◽  
Estimation Algorithm ◽  
Coherent Receivers ◽  
Multi Level ◽  
Reduced Complexity ◽  
Laser Line Width

This paper proposes a nearby phase search (NPS) algorithm based on BPS estimation algorithm in optical coherent receivers. And its suitable for arbitrary multi-level modulation. Making use of the continuity of phase change, the proposed NPS algorithm is applied to process nearby symbols by taking the pre-estimation phase of each symbol block as reference point. Compared to the traditional blind phase search (BPS) algorithm and its improved two-stage BPS algorithm, the performance of the proposed NPS algorithm is greatly improved in ultra-high speed coherent optical transmission system. By the simulation, the effectiveness and feasibility of the proposed algorithm are demonstrated in 28GBaud 16-QAM and 64-QAM system. Its shown that the computational complexity of the NPS algorithm greatly reduces in the guarantee of laser line width tolerance and bit error rate.

scholarly journals Application of Multivariate Modeling for Radiation Injury Assessment: A Proof of Concept

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
David L. Bolduc ◽  
Vilmar Villa ◽  
David J. Sandgren ◽  
G. David Ledney ◽  
William F. Blakely ◽  
...  
Keyword(s):  
Predictive Power ◽  
Radiation Injury ◽  
Estimation Algorithm ◽  
Absolute Number ◽  
Blood Parameters ◽  
Serum Chemistry ◽  
Independent Variables ◽  
Estimation Algorithms ◽  
Injury Assessment ◽  
Total Body

Multivariate radiation injury estimation algorithms were formulated for estimating severe hematopoietic acute radiation syndrome (H-ARS) injury (i.e., response category three or RC3) in a rhesus monkey total-body irradiation (TBI) model. Classical CBC and serum chemistry blood parameters were examined prior to irradiation (d 0) and on d 7, 10, 14, 21, and 25 after irradiation involving 24 nonhuman primates (NHP) (Macaca mulatta) given 6.5-Gy60CoΥ-rays (0.4 Gy min−1) TBI. A correlation matrix was formulated with the RC3 severity level designated as the “dependent variable” and independent variables down selected based on their radioresponsiveness and relatively low multicollinearity using stepwise-linear regression analyses. Final candidate independent variables included CBC counts (absolute number of neutrophils, lymphocytes, and platelets) in formulating the “CBC” RC3 estimation algorithm. Additionally, the formulation of a diagnostic CBC and serum chemistry “CBC-SCHEM” RC3 algorithm expanded upon the CBC algorithm model with the addition of hematocrit and the serum enzyme levels of aspartate aminotransferase, creatine kinase, and lactate dehydrogenase. Both algorithms estimated RC3 with over 90% predictive power. Only the CBC-SCHEM RC3 algorithm, however, met the critical three assumptions of linear least squares demonstrating slightly greater precision for radiation injury estimation, but with significantly decreased prediction error indicating increased statistical robustness.

A computational scheme to estimate the Leontief model matrix coefficients according to input-output table data for the southern regions of the Tyumen Oblast

2021 ◽  
Vol 19 (12) ◽  
pp. 2360-2383
Author(s):  
Denis A. GOVORKOV ◽  
Viktor P. NOVIKOV ◽  
Il'ya G. SOLOV'EV ◽  
Vladimir R. TSIBUL'SKII
Keyword(s):  
Least Squares Method ◽  
Estimation Algorithm ◽  
Balance Model ◽  
Input Output ◽  
Output Data ◽  
Tyumen Oblast ◽  
Estimation Algorithms ◽  
Additional Information ◽  
Output Matrix ◽  
Reference Input

Subject. This article deals with the control and management aspects of regional development on the basis of Leontief’s balance model. Objectives. The article aims to develop schemes for stable estimation of aggregate parameters of region balance models based on a shortened sample of input-output statistical data and rules for their subsequent regularization. Methods. For the study, we used multiple forms of regional economic balance model transformation based on the aggregation of data of the selected regional subsystems. Results. The primary estimates of aggregate input-output matrix for the southern regions of the Tyumen Oblast were obtained from the statistical input-output data for 2014–2018. To comply with the productivity conditions, additional information was introduced into the estimation algorithm reflecting the balance dependence for the reference input-output matrix for the Russian Federation and for the southern regions of the Tyumen Oblast in retrospective (2004–2013). Conclusions. The result of regularization of aggregate input-output matrix for the southern regions of the Tyumen Oblast obtained from the statistical input-output data on the basis of the least squares method indicates that the backward estimation technique cannot act as a basic tool for the primary construction of balance models of regional economies. However, backward estimation algorithms with subsequent regularization are effective in correcting the reference input-output matrix using actual data of the region’s socio-economic development.

scholarly journals Conditional Analysis for Mixed Covariates, with Application to Feed Intake of Lactating Sows

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
S. Y. Park ◽  
C. Li ◽  
S. M. Mendoza Benavides ◽  
E. van Heugten ◽  
A. M. Staicu
Keyword(s):  
Feed Intake ◽  
Dynamic Change ◽  
Estimation Algorithm ◽  
Joint Estimation ◽  
Efficient Estimation ◽  
Specific Information ◽  
Computationally Efficient ◽  
Modeling Framework ◽  
Lactating Sows ◽  
Information Vector

We propose a novel modeling framework to study the effect of covariates of various types on the conditional distribution of the response. The methodology accommodates flexible model structure, allows for joint estimation of the quantiles at all levels, and provides a computationally efficient estimation algorithm. Extensive numerical investigation confirms good performance of the proposed method. The methodology is motivated by and applied to a lactating sow study, where the primary interest is to understand how the dynamic change of minute-by-minute temperature in the farrowing rooms within a day (functional covariate) is associated with low quantiles of feed intake of lactating sows, while accounting for other sow-specific information (vector covariate).

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.

Sign in / Sign up

Export Citation Format

Share Document