A UNIFIED APPROACH FOR GENERATING OPTIMUM GRADIENT FIR ADAPTIVE ALGORITHMS WITH TIME-VARYING CONVERGENCE FACTORS

1991 ◽  
Vol 01 (01) ◽  
pp. 19-42 ◽  
Author(s):  
WASFY B. MIKHAEL ◽  
FRANK H. WU
Keyword(s):  
Computational Complexity ◽  
Mean Squared Error ◽  
Adaptive Algorithms ◽  
Time Varying ◽  
Unified Approach ◽  
Squared Error ◽  
Wide Range ◽  
The Mean ◽  
Single Data ◽  
And Performance

In this paper, a unified approach for generating fast block- and sequential-gradient LMS FIR tapped delay line (TDL) adaptive algorithms is presented. These algorithms employ time-varying convergence factors which are tailored for the adaptive filter coefficients and updated at each block or single data iteration. The convergence factors are chosen to minimize the mean squared error (MSE) and are easily computed from readily available signals. The general formulation leads to three classes of adaptive algorithms. These algorithms. ordered in a descending order of their computational complexity and performance. are: the optimum block adaptive algorithm with individual adaptation of parameters (OBAI), the optimum block adaptive (OBA) and OBA shifting (ODAS) algorithms, and the homogeneous adaptive (HA) algorithm. In this paper, it is shown how each class of algorithms is obtained from the previous one, by a simple trade-off between adaptation performance and computational complexity. Implementation aspects of the generated algorithms are examined and their performance is evaluated and compared with several recently proposed algorithms by means of computer simulations under a wide range of adaptation conditions. The evaluation results show that the generated algorithms have attractive features in the comparisons due to the considerable reduction in the number of iterations required for a given adaptation accuracy. The improvement, however. is achieved at the expense of a relatively modest increase in the number of computations per data sample.

The sinkage characteristics and prediction of a planetary rover based on a similarity model experiment

2018 ◽  
Vol 233 (10) ◽  
pp. 3762-3774
Author(s):  
Han Huang ◽  
Shucai Xu ◽  
Zou Meng ◽  
Jianqiao Li ◽  
Jinhuan Zhang
Keyword(s):  
Mean Squared Error ◽  
Rear Wheel ◽  
Experimental Results ◽  
Slip Ratio ◽  
Slip Conditions ◽  
Apparent Slip ◽  
Squared Error ◽  
The Mean ◽  
And Performance ◽  
Similarity Law

The environment on an extraterrestrial planet is complex, with soft surfaces and low gravity, which make it easy for rovers to sink and skid. Excessive sinkage may occur under large slip conditions of probe rovers and could influence the survey mission. Predicting the sinkage performance of wheels under slip conditions is important for the development and performance evaluation of exploration rovers. This paper presents a dimensional analysis on the main parameters of the wheel–soil interaction system; the analysis was performed based on the similarity law, for which corresponding similar scale values were obtained. Referring to the lunar surface gravity environment, we have produced a 1/2 scaling model rover. To investigate the sinkage characteristics of the model rover, tests were performed with different wheel loads (5 N, 7 N, and 9 N) and soil states (loose, natural, and compact). The characteristic parameters of a rear wheel rut were also analyzed, including rut depth (hereinafter referred to as apparent sinkage) and slip ratio (hereinafter referred to as apparent slip ratio). Experimental results were analyzed to evaluate the sinkage characteristics and to draw conclusions. Sinkage models for the rover under different soil states were proposed, and verification and error analyses for the sinkage models were conducted using indices such as the mean relative error and root mean squared error. The experimental results and conclusions are useful for optimal rover design and improvement/verification of wheel–soil interaction mechanics models.

Enhancement of Gradient for Touching and Overlapping Objects

2020 ◽  
Vol 17 (2) ◽  
pp. 1173-1176
Author(s):  
Wan Mahani Abdullah ◽  
Shahrul Nizam Yaakob ◽  
Ainul Maulid Ahmad ◽  
Mu’azah Md Aziz ◽  
Mohamad Izril Ishak ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Gradient Image ◽  
Squared Error ◽  
Complex Background ◽  
Performance Matrix ◽  
The Mean ◽  
And Performance ◽  
Gradient Enhancement

Normally, gradient image is sometime poor especially for touching and overlapping objects. The proposed method manipulates the use of HSV channels in order to enhance the gradient image obtained for objects with complex background. Only S and V channels are used in this technique. The proposed gradient enhancement approaches were tested on HSV channel images. The Standard Sobel and Laplace of Gaussian (LoG) technique was used to compare the results and performance. The Mean Squared Error (MSE) and Peak signal-to-noise ratio (PSNR) values were calculated as a performance matrix for the implementation. The results show the improvement of the gradient image if compared to existence approach.

scholarly journals APPLICATION OF AN ADAPTIVE STEP-SIZE ALGORITHM IN MODELS OF HYPERINFLATION

2012 ◽  
Vol 16 (S3) ◽  
pp. 355-375 ◽  
Author(s):  
Olena Kostyshyna
Keyword(s):  
New York ◽  
Mean Squared Error ◽  
American Economic Review ◽  
Sufficient Information ◽  
Recursive Algorithms ◽  
Time Varying ◽  
Step Size ◽  
Adaptive Step Size ◽  
Squared Error ◽  
Adaptive Step

An adaptive step-size algorithm [Kushner and Yin,Stochastic Approximation and Recursive Algorithms and Applications, 2nd ed., New York: Springer-Verlag (2003)] is used to model time-varying learning, and its performance is illustrated in the environment of Marcet and Nicolini [American Economic Review93 (2003), 1476–1498]. The resulting model gives qualitatively similar results to those of Marcet and Nicolini, and performs quantitatively somewhat better, based on the criterion of mean squared error. The model generates increasing gain during hyperinflations and decreasing gain after hyperinflations end, which matches findings in the data. An agent using this model behaves cautiously when faced with sudden changes in policy, and is able to recognize a regime change after acquiring sufficient information.

Computing trade-offs in robust design: Perspectives of the mean squared error

2011 ◽  
Vol 60 (2) ◽  
pp. 248-255 ◽  
Author(s):  
Sangmun Shin ◽  
Funda Samanlioglu ◽  
Byung Rae Cho ◽  
Margaret M. Wiecek
Keyword(s):  
Robust Design ◽  
Mean Squared Error ◽  
Squared Error ◽  
Trade Offs ◽  
The Mean

Slip-Clutch Torque Estimation via Real-Time Adaptive Lookup Table

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Wenpeng Wei ◽  
Hussein Dourra ◽  
Guoming Zhu
Keyword(s):  
Friction Coefficient ◽  
Real Time ◽  
Mean Squared Error ◽  
Surface Friction ◽  
Lookup Table ◽  
Recursive Least Squares ◽  
Time Varying ◽  
Squared Error ◽  
Output Torque ◽  
Clutch Torque

Abstract Transfer case clutch is crucial in determining traction torque distribution between front and rear tires for four-wheel-drive (4WD) vehicles. Estimating time-varying clutch surface friction coefficient is critical for traction torque control since it is proportional to the clutch output torque. As a result, this paper proposes a real-time adaptive lookup table strategy to provide the time-varying clutch surface friction coefficient. Specifically, the clutch-parameter-dependent (such as clutch output torque and clutch touchpoint distance) friction coefficient is first estimated with available low-cost vehicle sensors (such as wheel speed and vehicle acceleration); and then a clutch-parameter-independent approach is developed for clutch friction coefficient through a one-dimensional lookup table. The table nodes are adaptively updated based on a fast recursive least-squares (RLS) algorithm. Furthermore, the effectiveness of adaptive lookup table is demonstrated by comparing the estimated clutch torque from adaptive lookup table with that estimated from vehicle dynamics, which achieves 14.8 Nm absolute mean squared error (AMSE) and 2.66% relative mean squared error (RMSE).

scholarly journals Day-Ahead Forecasting of Hourly Photovoltaic Power Based on Robust Multilayer Perception

2018 ◽  
Vol 10 (12) ◽  
pp. 4863 ◽  
Author(s):  
Chao Huang ◽  
Longpeng Cao ◽  
Nanxin Peng ◽  
Sijia Li ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Power Plants ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Multilayer Perception ◽  
Squared Error ◽  
The Mean ◽  
Effectiveness And Efficiency ◽  
Mlp Network ◽  
Grid Operation ◽  
Better Than

Photovoltaic (PV) modules convert renewable and sustainable solar energy into electricity. However, the uncertainty of PV power production brings challenges for the grid operation. To facilitate the management and scheduling of PV power plants, forecasting is an essential technique. In this paper, a robust multilayer perception (MLP) neural network was developed for day-ahead forecasting of hourly PV power. A generic MLP is usually trained by minimizing the mean squared loss. The mean squared error is sensitive to a few particularly large errors that can lead to a poor estimator. To tackle the problem, the pseudo-Huber loss function, which combines the best properties of squared loss and absolute loss, was adopted in this paper. The effectiveness and efficiency of the proposed method was verified by benchmarking against a generic MLP network with real PV data. Numerical experiments illustrated that the proposed method performed better than the generic MLP network in terms of root mean squared error (RMSE) and mean absolute error (MAE).

scholarly journals On double stage minimax-shrinkage estimator for generalized Rayleigh model

2016 ◽  
Vol 5 (1) ◽  
pp. 39 ◽  
Author(s):  
Abbas Najim Salman ◽  
Maymona Ameen
Keyword(s):  
Sample Size ◽  
Shape Parameter ◽  
Mean Squared Error ◽  
Scale Parameter ◽  
Rayleigh Distribution ◽  
Shrinkage Estimator ◽  
Squared Error ◽  
Expected Sample Size ◽  
Generalized Rayleigh Distribution ◽  
The Mean

<p>This paper is concerned with minimax shrinkage estimator using double stage shrinkage technique for lowering the mean squared error, intended for estimate the shape parameter (a) of Generalized Rayleigh distribution in a region (R) around available prior knowledge (a<sub>0</sub>) about the actual value (a) as initial estimate in case when the scale parameter (l) is known .</p><p>In situation where the experimentations are time consuming or very costly, a double stage procedure can be used to reduce the expected sample size needed to obtain the estimator.</p><p>The proposed estimator is shown to have smaller mean squared error for certain choice of the shrinkage weight factor y(<strong>×</strong>) and suitable region R.</p><p>Expressions for Bias, Mean squared error (MSE), Expected sample size [E (n/a, R)], Expected sample size proportion [E(n/a,R)/n], probability for avoiding the second sample and percentage of overall sample saved  for the proposed estimator are derived.</p><p>Numerical results and conclusions for the expressions mentioned above were displayed when the consider estimator are testimator of level of significanceD.</p><p>Comparisons with the minimax estimator and with the most recent studies were made to shown the effectiveness of the proposed estimator.</p>

scholarly journals Performance Analysis of AOA-Based Localization Using the LS Approach: Explicit Expression of Mean-Squared Error

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Byung-Kwon Son ◽  
Do-Jin An ◽  
Joon-Ho Lee
Keyword(s):  
Explicit Expression ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Squared Error ◽  
Distance Weighted ◽  
The Mean ◽  
Passive Localization ◽  
Location Estimate

In this paper, a passive localization of the emitter using noisy angle-of-arrival (AOA) measurements, called Brown DWLS (Distance Weighted Least Squares) algorithm, is considered. The accuracy of AOA-based localization is quantified by the mean-squared error. Various estimates of the AOA-localization algorithm have been derived (Doğançay and Hmam, 2008). Explicit expression of the location estimate of the previous study is used to get an analytic expression of the mean-squared error (MSE) of one of the various estimates. To validate the derived expression, we compare the MSE from the Monte Carlo simulation with the analytically derived MSE.

Estimation of critical torque using intermittent isometric maximal voluntary contractions of the quadriceps in humans

2009 ◽  
Vol 106 (3) ◽  
pp. 975-983 ◽  
Author(s):  
Mark Burnley
Keyword(s):  
Laboratory Tests ◽  
Mean Squared Error ◽  
Voluntary Activation ◽  
Peripheral Fatigue ◽  
Contraction Time ◽  
Twitch Interpolation ◽  
Squared Error ◽  
The Mean ◽  
Duration Relationship ◽  
Voluntary Contractions

To determine whether the asymptote of the torque-duration relationship (critical torque) could be estimated from the torque measured at the end of a series of maximal voluntary contractions (MVCs) of the quadriceps, eight healthy men performed eight laboratory tests. Following familiarization, subjects performed two tests in which they were required to perform 60 isometric MVCs over a period of 5 min (3 s contraction, 2 s rest), and five tests involving intermittent isometric contractions at ∼35–60% MVC, each performed to task failure. Critical torque was determined using linear regression of the torque impulse and contraction time during the submaximal tests, and the end-test torque during the MVCs was calculated from the mean of the last six contractions of the test. During the MVCs voluntary torque declined from 263.9 ± 44.6 to 77.8 ± 17.8 N·m. The end-test torque was not different from the critical torque (77.9 ± 15.9 N·m; 95% paired-sample confidence interval, −6.5 to 6.2 N·m). The root mean squared error of the estimation of critical torque from the end-test torque was 7.1 N·m. Twitch interpolation showed that voluntary activation declined from 90.9 ± 6.5% to 66.9 ± 13.1% ( P < 0.001), and the potentiated doublet response declined from 97.7 ± 23.0 to 46.9 ± 6.7 N·m ( P < 0.001) during the MVCs, indicating the development of both central and peripheral fatigue. These data indicate that fatigue during 5 min of intermittent isometric MVCs of the quadriceps leads to an end-test torque that closely approximates the critical torque.

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