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排序方式： 共有8326条查询结果，搜索用时 15 毫秒
991.
J. W. Yoo I. S. Song J. W. Shin P. G. Park 《International Journal of Communication Systems》2016,29(5):1012-1025
This paper presents a new variable step‐size diffusion affine projection algorithm (VSS‐DAPA) to advance the filter performance of the diffusion affine projection algorithm (DAPA). The proposed VSS strategy is developed for the DAPA, which can solve the distributed estimation problem over diffusion networks well. To obtain the optimal step size reasonably, we seek the update recursion of mean‐square deviation (MSD) that is suitable for the DAPA. The step size is optimally given through the minimization for the MSD of the DAPA at each iteration. The derived step size through the MSD minimization improves the filter performance with respect to the convergence and the estimation error in steady state. The results based on simulations demonstrate that the proposed VSS‐DAPA performs better than the existing algorithms with a system‐identification scenario in diffusion network. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
992.
In cellular networks, global channel state information (CSI) shall be shared among neighboring cells to mitigate various inter‐cell interference (ICI). In this paper, we propose that comparable ICI is mitigated while weak ICI is treated as noise. The amount of shared CSI is highly reduced, because of that only the CSI corresponding to comparable ICI is shared among neighboring cells. In the case of single user equipment in each cell, a joint singular value decomposition and interference alignment method is proposed along with the analysis of its approximate sum rate. Some nodes select singular value decomposition method, while others choose interference alignment method. The method at each node is determined by global selection principle or user classification principle. In the case of multiple UEs in each cell, all nodes utilize minimum mean square error method, but ICI is neglected at cell center users. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
993.
In this article, we propose the use of power function and least squares method for designing of a fractional order digital differentiator. The input signal is transformed into a power function by using Taylor series expansion, and its fractional derivative is computed using the Grunwald–Letnikov (G–L) definition. Next, the fractional order digital differentiator is modelled as a finite impulse response (FIR) system that yields fractional order derivative of the G–L type for a power function. The FIR system coefficients are obtained by using the least squares method. Two examples are used to demonstrate that the fractional derivative of the digital signals is computed by using the proposed technique. The results of the third and fourth examples reveal that the proposed technique gives superior performance in comparison with the existing techniques. 相似文献
994.
《Measurement》2016
Evaluation of the tolerance zone using discrete measured points plays a critical role in today’s manufacturing, metrology, and many industrial applications. The deviation zone is typically evaluated using a fitting method that locates an ideal desired geometry corresponding to a set of measured points while a function of the Euclidean distances of the measured points to the ideal surface becomes minimum. This paper presents a quick and reliable algorithm called Dynamic Principle Component Alignment (DPCA) for fitting complex surfaces to the coordinate metrology measured points using the information that is dynamically generated by Principal Component Analysis (PCA) of the measurement data and the corresponding fitted geometry. The developed algorithm efficiently eliminates the necessity for applying commonly used optimization methods for the fitting (localization) process, which decreases the computational cost and uncertainty of the evaluation process. Moreover, DPCA is very reliable and practical in coordinate metrology with large data sets in processes such as laser scanning and other optical methods. The results show that the proposed methodology more accurately finds fitting parameters in comparison with the other commonly used methods while the computational cost is considerably reduced. 相似文献
995.
J. F. Muñoz‐Rosas E. Álvarez‐Verdejo M. N. Pérez‐Aróstegui L. Gutiérrez‐Gutiérrez 《Quality and Reliability Engineering International》2016,32(2):453-464
A control chart is a very common tool used to monitor the quality of business processes. An estimator of the process variability is generally considered to obtain the control limits of a chart when parameters of the process are unknown. Assuming Monte Carlo simulations, this paper first compares the efficiency of the various estimators of the process variability. Two empirical measures used to analyze the performance of control charts are defined. Results derived from various empirical studies reveal the existence of a linear relationship between the performance of the various estimators of the process variability and the performance of charts. The various Monte Carlo simulations are conducted under the assumption that the process is in both situations of in‐control and out‐of‐control. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
996.
The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems. 相似文献
997.
Muhammad Haseeb Ahmad Zainab Shahbaz Muhammad Imran Muhammad Kamran Khan Niaz Muhammad Sanaullah Iqbal Waqas Ahmed Tanvir Ahmad 《Food Science & Nutrition》2021,9(11):6089-6098
The production of trans-fats and chemical changes during the process of frying are serious public health concerns and must be monitored efficiently. For this purpose, the canola oil was formulated with different ratio of extra virgin olive oil and palm olein using D-optimal mixture design, and the best formulation (67:22:11) based on free fatty acid (FFA) content, peroxide value (PV), and iodine value (IV) as responses was selected for multiple frying process. The data on FFA, PV, and IV along with Fourier transform-infrared (FT-IR) spectra were taken after each frying up to ten frying. The spectral data were preprocessed with standard normal variate followed by principal component analysis which is clearly showing the differentiation for various frying. Similarly, partial least square regression was applied to predict the FFA (0.37%–1.63%), PV (4.47–13.85 meqO2/kg), and IV (111.51–51.39 I2/100 g) which demonstrated high coefficient of determination (R2) 0.84, 0.83, and 0.81, respectively. It can be summarized that FT-IR can be used as a novel tool for fast and noninvasive quality determination of frying oils. 相似文献
998.
FCM和LS-SVM相结合的粮虫图像分割算法 总被引：1，自引：0，他引：1
模糊C均值(FCM)聚类算法广泛用于图像的自动分割,但是该算法对噪声十分敏感。因此提出一种改进的算法,在传统的FCM聚类的基础上,结合LS-SVM对图像进行分类。该方法对噪声有很强的鲁棒性和对像素聚类的正确性。 相似文献
999.
Mahdi Aliyari Shoorehdeli Mohammad Teshnehlab Ali Khaki Sedigh 《Neural computing & applications》2009,18(2):157-174
This paper suggests novel hybrid learning algorithm with stable learning laws for adaptive network based fuzzy inference system
(ANFIS) as a system identifier and studies the stability of this algorithm. The new hybrid learning algorithm is based on
particle swarm optimization (PSO) for training the antecedent part and gradient descent (GD) for training the conclusion part.
Lyapunov stability theory is used to study the stability of the proposed algorithm. This paper, studies the stability of PSO
as an optimizer in training the identifier, for the first time. Stable learning algorithms for the antecedent and consequent
parts of fuzzy rules are proposed. Some constraints are obtained and simulation results are given to validate the results.
It is shown that instability will not occur for the leaning rate and PSO factors in the presence of constraints. The learning
rate can be calculated on-line and will provide an adaptive learning rate for the ANFIS structure. This new learning scheme
employs adaptive learning rate that is determined by input–output data. 相似文献
1000.