Ensuring the Real Time Signal Transmission Using GSM/Internet Technology for Remote Fetal Monitoring

2008 ◽  
pp. 291-298 ◽  
Author(s):  
Krzysztof Horoba ◽  
Janusz Wrobel ◽  
Dawid Roj ◽  
Tomasz Kupka ◽  
Adam Matonia ◽  
...  
Keyword(s):  
Real Time ◽  
Signal Transmission ◽  
Fetal Monitoring ◽  
Internet Technology ◽  
Time Signal ◽  
The Real

The Design and Implementation of RTOS Based on YL-236 Single Chip Microcomputer Training Device

2014 ◽  
Vol 543-547 ◽  
pp. 554-557
Author(s):  
Ming Fei Qu ◽  
Dan Zhao ◽  
Sha Tao
Keyword(s):  
Operating System ◽  
Real Time ◽  
Signal Transmission ◽  
Control Device ◽  
Training Device ◽  
Single Chip ◽  
Single Chip Microcomputer ◽  
The Real ◽  
Design And Implementation ◽  
Time Performance

Using the equipment, YL-236 single chip microcomputer (SCM) control device installation and debugging training platform, used in the SCM event of the National Vocational Students Skills Competition (NVSSC) as hardware carrier, this paper researched the application method of real-time operating system (RTOS) in the implementation of the SCM Skills Competition task, and apply the real-time multitasking operating system (RTMOS), RTX51, in the 8-bit 51 SCM. That allows switch of circulation tasks, supports the signal transmission, utilizes the interrupt function in parallel, and has very small demand for RAM. That makes whole SCM task to develop much easier and more convenient, and enhances the real-time performance and reliability of the SCM Skills Competition task at the same time.

scholarly journals Improved Real-time Denoising Method Based on Lifting Wavelet Transform

2014 ◽  
Vol 14 (3) ◽  
pp. 152-159 ◽  
Author(s):  
Zhaohua Liu ◽  
Yang Mi ◽  
Yuliang Mao
Keyword(s):  
Wavelet Transform ◽  
Real Time ◽  
Signal To Noise Ratio ◽  
Threshold Function ◽  
Time Signal ◽  
Signal Denoising ◽  
Lifting Wavelet Transform ◽  
Denoising Method ◽  
The Real ◽  
Lifting Wavelet

Abstract Signal denoising can not only enhance the signal to noise ratio (SNR) but also reduce the effect of noise. In order to satisfy the requirements of real-time signal denoising, an improved semisoft shrinkage real-time denoising method based on lifting wavelet transform was proposed. The moving data window technology realizes the real-time wavelet denoising, which employs wavelet transform based on lifting scheme to reduce computational complexity. Also hyperbolic threshold function and recursive threshold computing can ensure the dynamic characteristics of the system, in addition, it can improve the real-time calculating efficiency as well. The simulation results show that the semisoft shrinkage real-time denoising method has quite a good performance in comparison to the traditional methods, namely soft-thresholding and hard-thresholding. Therefore, this method can solve more practical engineering problems.

The real-time signal processor

1983 ◽  
Vol 31 (1) ◽  
pp. 83-95 ◽  
Author(s):  
F. Mintzer ◽  
K. Davies ◽  
A. Peled ◽  
F. Ris
Keyword(s):  
Real Time ◽  
Time Signal ◽  
The Real ◽  
Signal Processor

scholarly journals Real-time high-bandwidth mm-wave 5G NR signal transmission with analog radio-over-fiber fronthaul over multi-core fiber

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Simon Rommel ◽  
Evangelos Grivas ◽  
Bruno Cimoli ◽  
Delphin Dodane ◽  
Alvaro Morales ◽  
...  
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Signal Transmission ◽  
Access Network ◽  
Local Oscillator ◽  
Time Signal ◽  
Radio Access ◽  
Core Fibre ◽  
Core Fiber ◽  
Real Time Signal Processing

AbstractThis article presents an experimental demonstration of a high-capacity millimeter-wave 5G NR signal transmission with analog radio-over-fiber (ARoF) fronthaul over multi-core fiber and full real-time processing. The demonstration validates the core of the blueSPACE fronthaul architecture which combines ARoF fronthaul with space division multiplexing in the optical distribution network to alleviate the fronthaul capacity bottleneck and maintain a centralized radio access network with fully centralized signal processing. The introduction of optical beamforming in the blueSPACE architecture brings true multi-beam transmission and enables full spatial control over the RF signal. The proposed ARoF architecture features a transmitter that generates the ARoF signal and an optical signal carrying a reference local oscillator employed for downconversion at the remote unit from a single RF reference at the central office. A space division multiplexing based radio access network with multi-core fibre allows parallel transport of the uplink ARoF signal and reference local oscillator at the same wavelength over separate cores. A complete description of the real-time signal processing and experimental setup is provided and system performance is evaluated. Transmission of an 800 MHz wide extended 5G NR fronthaul signal over a 7-core fibre is shown with full real-time signal processing, achieving 1.4 Gbit/s with a bit error rate $$<3.8\times 10^{-3}$$ < 3.8 × 10 - 3 and thus below the limit for hard-decision forward error correction with 7% overhead.

Research on the real-time signal conditioning method for dispersion interferometer in HL-2M

2020 ◽  
Vol 22 (11) ◽  
pp. 115601
Author(s):  
Wei ZHANG ◽  
Tongyu WU ◽  
Jian ZHANG ◽  
Zejie YIN ◽  
Yan ZHOU
Keyword(s):  
Real Time ◽  
Time Signal ◽  
Signal Conditioning ◽  
The Real

Methods and Algorithms for Real Time Voice Noise Cleaning

2021 ◽  
Vol 26 (2) ◽  
pp. 184-196
Author(s):  
I.E. Vishnyakov ◽  
◽  
M.M. Masyagin ◽  
O.A. Odintsov ◽  
V.V. Sliusar ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
High Efficiency ◽  
Noise Suppression ◽  
Signal Transmission ◽  
Adaptive Method ◽  
Streaming Data ◽  
The Real ◽  
Operation Speed ◽  
Cleaning Methods

The voice cleaning methods and algorithms play a key role both in preprocessing speech for further analysis and recognition, and in improving the quality of communication between users of information networks. The real-time streaming noise cleaning methods are the most important and complex area. The ability to process streaming data without delays imposes a number of significant restrictions on the algorithm: it cannot be iterative with a previously unknown number of iterations, and cannot explicitly use the data before or after the current block being processed. In the work, a modern adaptive noise reduction method for speech that can work with minimal signal transmission delays has been proposed. A large-scale study of existing approaches has been conducted, with special attention paid to two groups of algorithms: noise detection algorithms and noise suppression algorithms. Based on them the developed algorithm meeting the specified requirements has been built and analyzed. A set of audio data of Russian speech with various noises superimposed on it has been created. The testing of the algorithm has been made and its comparison with existing actual noise cleaning methods has been performed. The proposed adaptive method of noise cleaning without using specialized apparatus means and subsidiary information is able to operate in the real time conditions. The testing of the developed algorithm using the metrics of segment NC and PESQ have shown the high efficiency of the development and its superiority to common noise cleaning implementations Speex and WebRTC with respect to the noise cleaning quality and operation speed.

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