Real-time multi-mode robust filtering method for rocket upper stage

2017 ◽  
Author(s):  
Huang Pu ◽  
Li Heng-nian ◽  
Lu Cao ◽  
Zhang Ding-Bo
Keyword(s):  
Real Time ◽  
Robust Filtering ◽  
Filtering Method ◽  
Upper Stage ◽  
Multi Mode

A spatio-temporal noise robust filtering method for separation of 2D incident and reflected irregular waves

2021 ◽  
Vol 237 ◽  
pp. 109544
Author(s):  
Gustavo E. Coelho ◽  
Maria Graça Neves ◽  
António Pascoal ◽  
Álvaro Ribeiro ◽  
Peter Frigaard
Keyword(s):  
Irregular Waves ◽  
Robust Filtering ◽  
Filtering Method ◽  
Temporal Noise ◽  
Spatio Temporal ◽  
Noise Robust

scholarly journals Three Revised Kalman Filtering Models for Short-Term Rail Transit Passenger Flow Prediction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Pengpeng Jiao ◽  
Ruimin Li ◽  
Tuo Sun ◽  
Zenghao Hou ◽  
Amir Ibrahim
Keyword(s):  
Real Time ◽  
Nonparametric Regression ◽  
Kalman Filtering ◽  
Rail Transit ◽  
Correction Coefficient ◽  
Short Term ◽  
Transit System ◽  
Filtering Method ◽  
Passenger Flow ◽  
Model Based

Short-term prediction of passenger flow is very important for the operation and management of a rail transit system. Based on the traditional Kalman filtering method, this paper puts forward three revised models for real-time passenger flow forecasting. First, the paper introduces the historical prediction error into the measurement equation and formulates a revised Kalman filtering model based on error correction coefficient (KF-ECC). Second, this paper employs the deviation between real-time passenger flow and corresponding historical data as state variable and presents a revised Kalman filtering model based on Historical Deviation (KF-HD). Third, the paper integrates nonparametric regression forecast into the traditional Kalman filtering method using a Bayesian combined technique and puts forward a revised Kalman filtering model based on Bayesian combination and nonparametric regression (KF-BCNR). A case study is implemented using statistical passenger flow data of rail transit line 13 in Beijing during a one-month period. The reported prediction results show that KF-ECC improves the applicability to historical trend, KF-HD achieves excellent accuracy and stability, and KF-BCNR yields the best performances. Comparisons among different periods further indicate that results during peak periods outperform those during nonpeak periods. All three revised models are accurate and stable enough for on-line predictions, especially during the peak periods.

Switching filtering method for interactive systems

2019 ◽  
Vol 233 (10) ◽  
pp. 1340-1350
Author(s):  
Junyi Hou ◽  
Lei Yu ◽  
Yifan Fang ◽  
Shumin Fei
Keyword(s):  
Real Time ◽  
Subjective Evaluation ◽  
Objective Evaluation ◽  
Interactive Systems ◽  
Interactive System ◽  
The Real ◽  
Noise Interference ◽  
Filtering Method ◽  
Time Performance ◽  
Filtering Effect

Aiming at the problem that the mixed noise interference caused by the mixed projection noise system is not accurate and the real-time performance is poor, this article proposes an adaptive system switching filtering method based on Bayesian estimation switching rules. The method chooses joint bilateral filtering and improved adaptive median filtering as the filtering subsystems and selects the sub-filtering system suitable for the noise by switching rules to achieve the purpose of effectively removing noise. The simulation experiment was carried out by the self-developed human–computer interactive projection image system platform. Through the subjective evaluation, objective evaluation, and running time comparison analysis, a better filtering effect was achieved, and the balance between the filtering precision and the real-time performance of the interactive system was well obtained. Therefore, the proposed method can be widely applied to various human–computer interactive image filtering systems.

scholarly journals Power Efficient Scheduling Algorithms for Real-time Tasks on Multi-mode Microcontrollers

2018 ◽  
Vol 130 ◽  
pp. 557-566 ◽  
Author(s):  
Douglas Lautner ◽  
Xiayu Hua ◽  
Scott DeBates ◽  
Miao Song ◽  
Shangping Ren
Keyword(s):  
Real Time ◽  
Scheduling Algorithms ◽  
Power Efficient ◽  
Multi Mode
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