Real-Time Multicast and Memory Replication Channels with Delay Bounded Error Detection and Retry Capabilities

2011 ◽  
Author(s):  
Jing Qian ◽  
Kane Kim ◽  
Zhen Zhang ◽  
Juan A. Colmenares ◽  
Kyung-Deok Moon ◽  
...  
Keyword(s):  
Real Time ◽  
Error Detection ◽  
Bounded Error ◽  
Memory Replication

Real-time error detection techniques based on FPGA

2013 ◽  
Vol 33 (5) ◽  
pp. 1459-1462
Author(s):  
Xiaoming JU ◽  
Jiehao ZHANG ◽  
Yizhong ZHANG
Keyword(s):  
Real Time ◽  
Error Detection ◽  
Time Error ◽  
Detection Techniques

Unmanned aerial vehicle reconnaissance image recognition based on convolutional neural network

2021 ◽  
pp. 1-10
Author(s):  
Lipeng Si ◽  
Baolong Liu ◽  
Yanfang Fu
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Image Recognition ◽  
Error Detection ◽  
Convolution Neural Network ◽  
Data Sets ◽  
Small Target ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Real Time Tracking

The important strategic position of military UAVs and the wide application of civil UAVs in many fields, they all mark the arrival of the era of unmanned aerial vehicles. At present, in the field of image research, recognition and real-time tracking of specific objects in images has been a technology that many scholars continue to study in depth and need to be further tackled. Image recognition and real-time tracking technology has been widely used in UAV aerial photography. Through the analysis of convolution neural network algorithm and the comparison of image recognition technology, the convolution neural network algorithm is improved to improve the image recognition effect. In this paper, a target detection technique based on improved Faster R-CNN is proposed. The algorithm model is implemented and the classification accuracy is improved through Faster R-CNN network optimization. Aiming at the problem of small target error detection and scale difference in aerial data sets, this paper designs the network structure of RPN and the optimization scheme of related algorithms. The structure of Faster R-CNN is adjusted by improving the embedding of CNN and OHEM algorithm, the accuracy of small target and multitarget detection is improved as a whole. The experimental results show that: compared with LENET-5, the recognition accuracy of the proposed algorithm is significantly improved. And with the increase of the number of samples, the accuracy of this algorithm is 98.9%.

Residue Checker with Signed-Digit Arithmetic for Error Detection of Arithmetic Circuits

2003 ◽  
Vol 12 (01) ◽  
pp. 41-53 ◽  
Author(s):  
Shugang Wei ◽  
Kensuke Shimizu
Keyword(s):  
Real Time ◽  
Error Detection ◽  
Binary Tree ◽  
Word Length ◽  
Arithmetic Circuits ◽  
Binary Number ◽  
Residue Number ◽  
Residue Arithmetic ◽  
Large Product ◽  
Binary Tree Structure

This paper presents a fast residue checker for the error detection of arithmetic circuits. The residue checker consists of a number of residue arithmetic circuits such as adders, multipliers and binary-to-residue converters based on radix-two signed-digit (SD) number arithmetic. The proposed modulo m (m = 2p ± 1) adder is designed with a p-digit SD adder, so that the modulo m addition time is independent of the word length of operands. The modulo m multiplier and binary-to-residue number converter are constructed with a binary tree structure of the modulo m SD adders. Thus, the modulo m multiplication is performed in a time proportional to log 2 p and an n-bit binary number is converted into a p-digit SD residue number, n ≫ p, in a time proportional to log 2(n/p). By using the presented residue arithmetic circuits, the error detection can be performed in real-time for a large product-sum circuit.

Development of a Real–Time Embedded Remote Triggering and Monitoring System with SC12

2012 ◽  
Author(s):  
Yew Leong Chui ◽  
Abdul Rahman Ramli
Keyword(s):  
Embedded System ◽  
Key Words ◽  
Real Time ◽  
Monitoring System ◽  
Error Detection ◽  
Data Interpretation ◽  
Time Error ◽  
Simultaneous Operation ◽  
Diagnostic Features ◽  
Remote Triggering

Kertas kerja ini membentangkan sistem kawalan dan pemantauan jarak jauh dengan menggunakan SC12. Satu penukar protokol dengan unit interpretasi data telah direka bentuk dan dilaksana. Untuk menambahkan saluran operasi unit interpretasi data, satu ciri auto–diagnostik pintar telah dilaksana untuk mengesan ralat. Kata kunci: Sistem terbenam, sistem pemicuan dan pemantauan, auto-diagnostik This paper presents a real–time embedded remote triggering and monitoring system using SC12. A protocol converter associated with data interpretation unit has been developed and implemented. In order to expand simultaneous operation channel with data interpretation unit, intelligent auto–diagnostic features has been implemented for run–time error detection purposes. Key words: Embedded system, triggering and monitoring system, auto-diagnostic

A direct comparison of patient-based real-time quality control techniques: The importance of the analyte distribution

2020 ◽  
Vol 57 (3) ◽  
pp. 206-214 ◽  
Author(s):  
Joel D Smith ◽  
Tony Badrick ◽  
Francis Bowling
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Error Detection ◽  
Alanine Aminotransferase ◽  
Clinical Chemistry ◽  
Moving Average ◽  
Moving Averages ◽  
Skewed Distributions ◽  
Real Patient ◽  
Box Cox Transformation

Background Patient-based real-time quality control (PBRTQC) techniques have been described in clinical chemistry for over 50 years. PBRTQC has a number of advantages over traditional quality control including commutability, cost and the opportunity for real-time monitoring. However, there are few systematic investigations assessing how different PBRTQC techniques perform head-to-head. Methods In this study, we compare moving averages with and without truncation and moving medians. For analytes with skewed distributions such as alanine aminotransferase and creatinine, we also investigate the effect of Box–Cox transformation of the data. We assess the ability of each technique to detect simulated analytical bias in real patient data for multiple analytes and to retrospectively detect a real analytical shift in a creatinine and urea assay. Results For analytes with symmetrical distributions, we show that error detection is similar for a moving average with and without four standard deviation truncation limits and for a moving median. In contrast to analytes with symmetrically distributed results, moving averages perform poorly for right skewed distributions such as alanine aminotransferase and creatinine and function only with a tight upper truncation limit. Box–Cox transformation of the data both improves the performance of moving averages and allows all data points to be used. This was also confirmed for retrospective detection of a real analytical shift in creatinine and urea. Conclusions Our study highlights the importance of careful assessment of the distribution of patient results for each analyte in a PBRTQC program with the optimal approaches dependent on whether the patient result distribution is symmetrical or skewed.

Real-time Bounded-error State Estimation for Vehicle Tracking

2009 ◽  
Vol 28 (1) ◽  
pp. 34-48 ◽  
Author(s):  
E. Seignez ◽  
M. Kieffer ◽  
A. Lambert ◽  
E. Walter ◽  
T. Maurin
Keyword(s):  
State Estimation ◽  
Real Time ◽  
Vehicle Tracking ◽  
Bounded Error ◽  
Error State
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