scholarly journals Robust Recursive Least-Squares Finite Impulse Response Predictor in Linear Discrete-Time Stochastic Systems with Uncertain Parameters

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Stochastic Systems ◽  
Finite Impulse Response ◽  
The State ◽  
Recursive Least Squares ◽  
Prediction Algorithm ◽  
Estimation Accuracy ◽  
Cross Covariance ◽  
Observation Noise ◽  
The Cross ◽  
Robust Prediction

This paper newly proposes the robust RLS Wiener FIR prediction algorithm based on the innovation theory for the linear stochastic systems including with parameters. In the robust RLS Wiener predictor, the following information is used. (1) The system matrices for the signal and the degraded signal. (2) The observation matrices for the signal and the degraded signal. (3) The variance of the state for the degraded signal. (4) The cross-variance of the state for the signal with the state. (5) The variance of the observation noise. As a step to obtain the robust RLS Wiener FIR prediction algorithm, this paper presents the robust prediction algorithm of the signal using the covariance information etc. In the predictor, the following information is used. (1) The observation matrices for the signal and the degraded signal. (2) The variance of the state for the degraded signal. (3) The auto-covariance information of the state for the degraded signal. (4) The cross-covariance information of the state for the signal with that for the degraded signal. (5) The variance of the observation noise. The estimation accuracy of the proposed robust RLS Wiener FIR predictor is superior to the existing RLS Wiener FIR predictor.

scholarly journals Distributed Fusion Estimation for Multisensor Multirate Systems with Stochastic Observation Multiplicative Noises

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Peng Fangfang ◽  
Sun Shuli
Keyword(s):  
Computational Cost ◽  
Covariance Matrices ◽  
The State ◽  
Multirate Systems ◽  
Multiplicative Noises ◽  
Cross Covariance ◽  
Sampling Points ◽  
Optimal Fusion ◽  
The Cross ◽  
Local Filters

This paper studies the fusion estimation problem of a class of multisensor multirate systems with observation multiplicative noises. The dynamic system is sampled uniformly. Sampling period of each sensor is uniform and the integer multiple of the state update period. Moreover, different sensors have the different sampling rates and observations of sensors are subject to the stochastic uncertainties of multiplicative noises. At first, local filters at the observation sampling points are obtained based on the observations of each sensor. Further, local estimators at the state update points are obtained by predictions of local filters at the observation sampling points. They have the reduced computational cost and a good real-time property. Then, the cross-covariance matrices between any two local estimators are derived at the state update points. At last, using the matrix weighted optimal fusion estimation algorithm in the linear minimum variance sense, the distributed optimal fusion estimator is obtained based on the local estimators and the cross-covariance matrices. An example shows the effectiveness of the proposed algorithms.

A novel robust prediction algorithm based on REMD-MWNN for AIOps

2021 ◽  
pp. 107038
Author(s):  
Liang Chen ◽  
Wei Wang ◽  
Yun Yang ◽  
Yaoqiang Xu
Keyword(s):  
Prediction Algorithm ◽  
Robust Prediction

scholarly journals Adaptive Filtering Based on Legendre Polynomials

2020 ◽  
Author(s):  
Lu Shen ◽  
Yuriy Zakharov ◽  
Long Shi ◽  
Benjamin Henson
Keyword(s):  
Channel Estimation ◽  
Interference Cancellation ◽  
Legendre Polynomials ◽  
Adaptive Filters ◽  
Recursive Least Squares ◽  
Full Duplex ◽  
Estimation Accuracy ◽  
Underwater Acoustic Communications ◽  
Basis Expansion ◽  
New Family

Abstract:<div><br><div><pre><p>In system identification scenarios, classical adaptive filters, such as the recursive least squares (RLS) algorithm, predict the system impulse response. If a tracking delay is acceptable, interpolating estimators capable of providing more accurate estimates of time-varying impulse responses can be used; channel estimation in communications is an example of such applications. The basis expansion model (BEM) approach is known to be efficient for non-adaptive (block) channel estimation in communications. In this paper, we combine the BEM approach with the sliding-window RLS (SRLS) algorithm and propose a new family of adaptive filters. Specifically, we use the Legendre polynomials, thus the name the SRLS-L adaptive filter. The identification performance of the SRLS-L algorithm is evaluated analytically and via simulation. The analysis shows significant improvement in the estimation accuracy compared to the SRLS algorithm and a good match between the theoretical and simulation results. The performance is further investigated in application to the self-interference cancellation in full-duplex underwater acoustic communications, where a high estimation accuracy is required. A field experiment conducted in a lake shows significant improvement in the cancellation performance compared to the classical SRLS algorithm.</p> </pre></div></div>

Cairo: Urban Space, Surveillance and the State

2019 ◽  
pp. 31-72
Author(s):  
Yasmine Ramadan
Keyword(s):  
Cross Section ◽  
Urban Space ◽  
Magical Realism ◽  
The State ◽  
The Fantastic ◽  
The Cross ◽  
And Control ◽  
The City ◽  
Literary Techniques

This chapter focuses on the representation of the urban space of Cairo. It examines Sonallah Ibrahim’s Tilka-l-raʾiha (The Smell of it, 1966), Gamal al-Ghitani’s Waqaʾiʿ harat al-Zaʿfarani (The Zafarani Files, 1976), Ibrahim Aslan’s Malik al-hazin (The Heron, 1981), and Radwa Ashour’s, Faraj (Blue Lorries, 2008) reading the novels in opposition to the realist narratives of earlier decades. The shift away from the realist depictions of the urban metropolis as the site of national struggle, or of the alley as the cross-section of Egyptian society, is accompanied by a new representational aesthetics. Through the presentation of the city as the space of incarceration, the reimagination of the alley as a fantastic space, and the turn towards the previously ignored neighborhood of Imbaba, these writers showcase new literary techniques; aspects of magical realism; elements of the fantastic; a turn to hyper-realism, in order to represent the transformation of the urban space of Cairo into one of surveillance and control.

scholarly journals A Strong Tracking Mixed-Degree Cubature Kalman Filter Method and Its Application in a Quadruped Robot

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2251 ◽  
Author(s):  
Jikai Liu ◽  
Pengfei Wang ◽  
Fusheng Zha ◽  
Wei Guo ◽  
Zhenyu Jiang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Real Time ◽  
Quadruped Robot ◽  
The State ◽  
Estimation Accuracy ◽  
Robot System ◽  
Calculation Time ◽  
Motion State ◽  
Cubature Kalman Filter

The motion state of a quadruped robot in operation changes constantly. Due to the drift caused by the accumulative error, the function of the inertial measurement unit (IMU) will be limited. Even though multi-sensor fusion technology is adopted, the quadruped robot will lose its ability to respond to state changes after a while because the gain tends to be constant. To solve this problem, this paper proposes a strong tracking mixed-degree cubature Kalman filter (STMCKF) method. According to system characteristics of the quadruped robot, this method makes fusion estimation of forward kinematics and IMU track. The combination mode of traditional strong tracking cubature Kalman filter (TSTCKF) and strong tracking is improved through demonstration. A new method for calculating fading factor matrix is proposed, which reduces sampling times from three to one, saving significantly calculation time. At the same time, the state estimation accuracy is improved from the third-degree accuracy of Taylor series expansion to fifth-degree accuracy. The proposed algorithm can automatically switch the working mode according to real-time supervision of the motion state and greatly improve the state estimation performance of quadruped robot system, exhibiting strong robustness and excellent real-time performance. Finally, a comparative study of STMCKF and the extended Kalman filter (EKF) that is commonly used in quadruped robot system is carried out. Results show that the method of STMCKF has high estimation accuracy and reliable ability to cope with sudden changes, without significantly increasing the calculation time, indicating the correctness of the algorithm and its great application value in quadruped robot system.

scholarly journals Perturbation theory approach to predict the covariance matrices of the galaxy power spectrum and bispectrum in redshift space

2020 ◽  
Vol 497 (2) ◽  
pp. 1684-1711 ◽  
Author(s):  
Naonori S Sugiyama ◽  
Shun Saito ◽  
Florian Beutler ◽  
Hee-Jong Seo
Keyword(s):  
Perturbation Theory ◽  
Power Spectrum ◽  
Shot Noise ◽  
Signal To Noise Ratio ◽  
Covariance Matrices ◽  
Theory Approach ◽  
Cross Covariance ◽  
The Galaxy ◽  
The Cross ◽  
Non Gaussian

ABSTRACT In this paper, we predict the covariance matrices of both the power spectrum and the bispectrum, including full non-Gaussian contributions, redshift space distortions, linear bias effects, and shot-noise corrections, using perturbation theory (PT). To quantify the redshift-space distortion effect, we focus mainly on the monopole and quadrupole components of both the power and bispectra. We, for the first time, compute the 5- and 6-point spectra to predict the cross-covariance between the power and bispectra, and the autocovariance of the bispectrum in redshift space. We test the validity of our calculations by comparing them with the covariance matrices measured from the MultiDark-Patchy mock catalogues that are designed to reproduce the galaxy clustering measured from the Baryon Oscillation Spectroscopic Survey Data Release 12. We argue that the simple, leading-order PT works because the shot-noise corrections for the Patchy mocks are more dominant than other higher order terms we ignore. In the meantime, we confirm some discrepancies in the comparison, especially of the cross-covariance. We discuss potential sources of such discrepancies. We also show that our PT model reproduces well the cumulative signal-to-noise ratio of the power spectrum and the bispectrum as a function of maximum wavenumber, implying that our PT model captures successfully essential contributions to the covariance matrices.

Assessment of cross-laminated timber panels by the state-space approach

2019 ◽  
Vol 22 (11) ◽  
pp. 2375-2391
Author(s):  
Asad S Albostami ◽  
Zhangjian Wu ◽  
Lee S Cunningham
Keyword(s):  
State Space ◽  
Three Dimensional ◽  
The State ◽  
Composite Panel ◽  
State Space Approach ◽  
Cross Laminated Timber ◽  
Practical Applications ◽  
The Cross ◽  
Analytical Approaches ◽  
Space Approach

In this article, cross-laminated timber panels are investigated as a novel engineering application of the state-space approach. As cross-laminated timber is a laminated composite panel, the three-dimensional analytical method provided by the state-space approach offers the potential for improved accuracy over existing common approaches to the analysis of cross-laminated timber. Before focusing on the specific application to cross-laminated timber, the general theory of the state-space approach is outlined. The method is then applied to describe the behaviour of a number of cross-laminated timber panel configurations previously examined experimentally and analytically. In order to demonstrate the capability of the state-space approach in this application, the results are compared with those from various two-dimensional and three-dimensional analytical approaches and finite element modelling briefly. With a view to design, different failure criteria are explored to assess the ultimate strength of the cross-laminated timber panels. The state-space approach demonstrates its superior capability in capturing the nonlinear distribution of the elastic stresses through the thickness of the cross-laminated timber panels over a range of span-to-thickness ratios common in practical applications.

scholarly journals A Scheme of MEMS-SINS Initial Alignment Aided by Laser Spot Perception System for the Boom-Type Roadheader

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yang Shen ◽  
Shichen Fu ◽  
Pengjiang Wang ◽  
Rui Li ◽  
Yu Lan ◽  
...  
Keyword(s):  
Microelectromechanical Systems ◽  
Unscented Kalman Filter ◽  
The State ◽  
Laser Spot ◽  
Initial Alignment ◽  
Working Face ◽  
Perception System ◽  
Cross Covariance ◽  
Before And After ◽  
Fading Factor

The initial alignment is one of the difficult problems of the strapdown inertial navigation system based on the microelectromechanical systems (MEMS-SINS) applied to the navigation of boom-type roadheader under a coalmine. To overcome the complex environment of the underground coalmine and the large noise of the MEMS gyroscope, the laser spot perception system (LSPS) was developed to provide the heading information of the roadheader to aid the initial alignment of the MEMS-SINS. During the process of initial alignment, the differential equation of heading error is derived, the heading error is extended as a state variable, and a nonlinear initial alignment model aided by heading error is built up. To cope with the time-varying noise statistics of MEMS-SINS in the working face of the coal mine roadway, a simplified strong tracking Unscented Kalman Filter (SST-UKF) algorithm is proposed by combining covariance matching technology with UKF. In the calculation of the measurement prediction covariance and the cross covariance, the fading factor is introduced, respectively, to avoid the contradiction between the residuals before and after the introduction; according to the characteristics of the observation equation being a linear equation, it proves that the state prediction covariance matrix change does not affect the observation measurement and uses unscented transform (UT) only once in the state estimation and variance prediction; thus, the computational burden of the algorithm is reduced and the real-time performance is improved. The simulation and onboard experiment results show that the proposed scheme can achieve horizontal alignment within 40 s and convergence azimuth misalignment angle to 0.9° within 450 s, which fully meets the requirements of MEMS-SINS initial alignment for underground coalmine roadheader.

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