Frequency-coded optimization of hopped-frequency pulse signal based on genetic algorithm

2005 ◽  
Vol 22 (1) ◽  
pp. 25-33
Author(s):  
Zheng Liu ◽  
Xuehua Mu
Keyword(s):  
Genetic Algorithm ◽  
Pulse Signal ◽  
Frequency Pulse

scholarly journals The Application of Low-Frequency Transition in the Assessment of the Second-Order Zeeman Frequency Shift

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8333
Author(s):  
Yang Bai ◽  
Xinliang Wang ◽  
Junru Shi ◽  
Fan Yang ◽  
Jun Ruan ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Frequency Shift ◽  
Low Frequency ◽  
Pulse Signal ◽  
Second Order ◽  
Magnetic Field Measurement ◽  
Central Frequency ◽  
Zeeman Frequency ◽  
The Magnetic Field ◽  
Frequency Pulse

Second-order Zeeman frequency shift is one of the major systematic factors affecting the frequency uncertainty performance of cesium atomic fountain clock. Second-order Zeeman frequency shift is calculated by experimentally measuring the central frequency of the (1,1) or (−1,−1) magnetically sensitive Ramsey transition. The low-frequency transition method can be used to measure the magnetic field strength and to predict the central fringe of (1,1) or (−1,−1) magnetically sensitive Ramsey transition. In this paper, we deduce the formula for magnetic field measurement using the low-frequency transition method and measured the magnetic field distribution of 4 cm inside the Ramsey cavity and 32 cm along the flight region experimentally. The result shows that the magnetic field fluctuation is less than 1 nT. The influence of low-frequency pulse signal duration on the accuracy of magnetic field measurement is studied and the optimal low-frequency pulse signal duration is determined. The central fringe of (−1,−1) magnetically sensitive Ramsey transition can be predicted by using a numerical integrating of the magnetic field “map”. Comparing the predicted central fringe with that identified by Ramsey method, the frequency difference between these two is, at most, a fringe width of 0.3. We apply the experimentally measured central frequency of the (−1,−1) Ramsey transition to the Breit-Rabi formula, and the second-order Zeeman frequency shift is calculated as 131.03 × 10−15, with the uncertainty of 0.10 × 10−15.

scholarly journals A Novel MOGA-SVM Multinomial Classification for Organ Inflammation Detection

2019 ◽  
Vol 9 (11) ◽  
pp. 2284 ◽  
Author(s):  
Kwok Chui ◽  
Miltiadis Lytras
Keyword(s):  
Genetic Algorithm ◽  
Pulse Signal ◽  
Health Condition ◽  
Support Vector ◽  
Clinical Measurement ◽  
Multi Objective Genetic Algorithm ◽  
Alternative Measures ◽  
Crucial Information ◽  
Sensitivity Specificity

Wrist pulse signal (WPS) contains crucial information of humans’ health condition. It can serve as an alternative method for diagnosing of organ inflammation instead of traditional clinical measurement. In this paper, a novel multi-objective genetic algorithm based support vector machine (MOGA-SVM) has been proposed for the multinomial classification of the inflammations of appendix, pancreas, and duodenum. A customized similarity kernel (KCS) has been optimally designed. The performance of multinomial classification using KCS is compared with five types of kernels, linear, radial basis function (RBF), polynomial and sigmoid kernel, as well as mixtures of polynomial and RBF, to verify the effectiveness of KCS. The sensitivity, specificity and accuracy (Acc) of the proposed method are 92%, 91.2%, and 91.6% respectively. The results have demonstrated that KCS improves the accuracy of classification from 8.9% to 59.6%. When compared to related work, the proposed method increases the performance by more than 10%. It is believed that WPS can serve as alternative measures to diagnose organ inflammations.

scholarly journals ENERGY PROPAGATION OF THE LOW-FREQUENCY PULSE ENERGY IN VITYAZ BAY

2020 ◽  
Author(s):  
Д.С. Манульчев
Keyword(s):  
Pulse Energy ◽  
Acoustic Pulse ◽  
Low Frequency ◽  
Pulse Signal ◽  
Signal Propagation ◽  
Field Studies ◽  
Energy Propagation ◽  
Digital Radio ◽  
Energy Signal ◽  
Frequency Pulse

Представлены результаты натурных исследований распространения низкочастотного акустического импульсного сигнала в бухте Витязь, Японское море. Измерения были проведены с помощью цифровых радиогидроакустических буев и импульсного пневмоизлучателя, свешиваемого с борта катера. Показано, что на трассе длиной 2,2 км со средней глубиной 30 м формируется сигнал в виде двух импульсов с соизмеримыми амплитудами и с задержкой 0,19 с, что, по-видимому, связано с наличием накопленного в бухте осадочного слоя. Данное предположение подтверждается численным моделированием путем введения в модельный волновод песочно-илистой подложки как канала распространения энергии импульсного сигнала. The paper presents the results of field studies on the propagation of a low- frequency acoustic pulse signal in Vityaz Bay, Japanese Sea. The measurements were carried out using digital radio-acoustic buoys and a pulsed air emitter hanging from the side of the boat. It was shown that on a 2.2 km long path with an average depth of 30 m, a signal is formed in the form of two pulses with comparable amplitudes and with a delay of 0.19 s, which is apparently due to the presence of a sedimentary layer accumulated in the bay. This assumption is confirmed by numerical simulation by introducing into the model waveguide a sandy-silty substrate as a pulse energy signal propagation channel.

The Pig Tracking System Based on AVR Microcontroller and GPS/GSM

2010 ◽  
Vol 139-141 ◽  
pp. 2195-2198 ◽  
Author(s):  
Hong Juan Wang ◽  
Shi Min Zhang ◽  
Peng Zhang ◽  
Li Yun Shi
Keyword(s):  
Oil And Gas ◽  
Tracking System ◽  
Low Frequency ◽  
Pulse Signal ◽  
Normal Operation ◽  
Magnetic Pulse ◽  
Oil And Gas Pipelines ◽  
The Right ◽  
Avr Microcontroller ◽  
Frequency Pulse

Oil and gas pipelines must be cleaned regularly to ensure their normal operation. It is significant to track the pig when it’s working in the pipeline. With the GPS and GSM technology, this paper introduces a kind of intelligent pig tracking system, The system uses ultra-low frequency electromagnetic wave with strong penetrating to transmit data. It concludes two parts: transmitter part and receiving part. The transmitter part which connects with the pig is controlled by SCM, interval transmitting ultra-low frequency pulse signal. The receiving part uses AVR SCM as its core controller and is mainly composed of magnetic pulse signal receiving module, GSM module, GPS module and LCD module. When the pig is working, the transmitting part interval transmits ultra-low frequency pulse signal. After receiving the right signal, the receiving part will send the location information to the designated GSM handsets. This system makes pig remote monitoring come true.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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