scholarly journals UAV detection algorithm based on the difference of power dispersion

2021 ◽  
Vol 2093 (1) ◽  
pp. 012011
Author(s):  
Cheng Yuan ◽  
Long-fei Jia ◽  
Hong-li Cheng
Keyword(s):  
Image Transmission ◽  
Detection Algorithm ◽  
Complex Signal ◽  
Constant Frequency ◽  
Time Frequency ◽  
The Matrix ◽  
The Difference ◽  
Power Dispersion ◽  
Uav Image ◽  
Short Time

Abstract With the development and popularization of UAVs, illegal UAV accidents occur frequently. The complex signal environment in the city brings difficulties to detect UAV signal. In order to detect the UAV signal in the complex environment, this paper proposes a UAV detection algorithm based on the difference of power dispersion in time. Firstly, the algorithm performs short-time Fourier transform on the signal to obtain the time-frequency matrix. Secondly, The fixed frequency interference in the matrix is filtered by the local adaptive threshold. Finally, the UAV image transmission signal is detected by the discrete difference in time between image transmission signal and WiFi. Simulation results show that the algorithm can detect UAV signal under constant frequency interference and WiFi interference.

DETECTING NONLINEAR AND NONSTATIONARY PROPERTIES OF POST-APNEIC SNORING SOUNDS USING HILBERT–HUANG TRANSFORM

2019 ◽  
Vol 31 (03) ◽  
pp. 1950017
Author(s):  
Tsuyoshi Mikami ◽  
Hirotaka Takahashi ◽  
Kazuya Yonezawa
Keyword(s):  
Soft Tissues ◽  
Fourier Transforms ◽  
Sleep Apnea Syndrome ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Obstructive Sleep ◽  
Leibler Divergence ◽  
The Difference ◽  
Frequency Map ◽  
Short Time

This study focuses on patients with severe obstructive sleep apnea syndrome (OSAS), and clarifies the existence of nonlinear and nonstationary properties in post-apneic snoring sounds. Many researchers have tried to discover intrinsic properties of the snoring sounds in OSAS patients for the past decades using linear frequency analysis, but no one has shown any evidence of the existence of nonlinearity and nonstationarity based on the quantitative evaluation of the post-apneic snoring sounds. In this study, Hilbert–Huang transform (HHT), which is designed for analyzing nonlinear and nonstationary signals, is adopted to generate a time-frequency map and the temporal variation in the spectral density is quantitatively evaluated using the averaged Kullback–Leibler divergence (AKL). As a result, for six OSAS patients, there is a tendency that most of AKL calculated from post-apneic snores are higher than those from non-apneic snores, which indicates that post-apneic snores are more nonstationary. In addition, we also evaluated the difference between the HHT time-frequency maps and spectrograms using short-time fourier transforms (STFT). Such analyses revealed that frequency fluctuations inherent to snoring can be adequately represented through HHT, but not with STFT. These nonlinear and nonstationary properties seem to be highly related to the physiological phenomena of OSAS, two of which are the explosive airflow after reopening of the closed airway and the collision vibration of the soft tissues.

On the wavelet time-frequency analysis algorithm in identification of a cracked rotor

2002 ◽  
Vol 37 (3) ◽  
pp. 239-246 ◽  
Author(s):  
J Zou ◽  
J Chen ◽  
Y P Pu ◽  
P Zhong
Keyword(s):  
Numerical Simulation ◽  
Detection Algorithm ◽  
Sampling Frequency ◽  
Crack Model ◽  
Cracked Rotor ◽  
Simulation Research ◽  
Time Frequency ◽  
Local Flexibility ◽  
The Difference ◽  
Frequency Properties

Based on the hinge crack model and the local flexibility theorem, the local flexibility of a cracked rotor due to the crack and the modified function of the opening and closing of the crack are given; the corresponding dynamic equation of the cracked rotor is modelled; the numerical simulation solutions of the cracked rotor and the uncracked rotor are obtained. By the continuous wavelet time—frequency transform, the wavelet time-frequency properties of the uncracked rotor and the cracked rotor are discussed; the difference between the wavelet time-frequency properties of the cracked rotor and those of the uncracked rotor is presented. A new detection algorithm that uses the wavelet time-frequency transform to identify the crack is proposed. The influence of the sampling frequency on the accuracy and validity of the wavelet time-frequency transform is analysed by numerical simulation research; the preferred sampling frequency is suggested. The experiments on the cracked rotor and the uncracked rotor demonstrate the validity and availability of the algorithm in the identification of the cracked rotor in engineering practices.

Small Floating Target Detection Algorithm Based on Time-Frequency Similarity

2014 ◽  
Vol 1030-1032 ◽  
pp. 1805-1809
Author(s):  
Jin Jiang ◽  
Ming Li ◽  
Yan Shen ◽  
Chong Yi Li
Keyword(s):  
Target Detection ◽  
Average Power ◽  
Detection Algorithm ◽  
Observation Time ◽  
Similarity Analysis ◽  
Mean Square ◽  
Time Frequency ◽  
Radar Echo ◽  
Time Average ◽  
Short Time

The features of radar echo of small floating target within sea clutter exists not only in target bins, but also exist in extend range bins. These lead to certain characteristic are similar between targets and extend bins. Short-time average power and mean-square Doppler bandwidth are extracted as two of these features and their similarities are been proved existing between target bin and extend bins by IPIX data. Although clutter bins may also have this similarity, it could be distinguished when observation time is enhanced. According to this characteristic, a detection algorithm is proposed based on time-frequency similarity analysis, the method works well when the average signal clutter ratio is about 5dB and the observation time is 300ms.

scholarly journals Measurement of Dielectric Liquid Electrification in the Shuttle System with Two Parallel Electrodes

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 970
Author(s):  
Dariusz Zmarzły ◽  
Paweł Frącz
Keyword(s):  
Dielectric Liquid ◽  
Short Time Fourier Transform ◽  
Liquid Sample ◽  
Constant Frequency ◽  
Time Frequency ◽  
Contact Electrification ◽  
Order Polynomial ◽  
Short Time ◽  
Rotating Electrodes ◽  
Shuttle System

In this paper, a device with swinging plate electrodes has been proposed to measure contact electrification of a liquid sample. The proposed structure is composed of two parallel metallic plates immersed in a dielectric liquid. One of the plates is swinging with a constant frequency in a range from 0.4 to 4 Hz. The paper investigates the dependence in time and frequency of electrode velocity and streaming electrification. The measured current occurs for a very low intermittent velocity of less than 10 mm/s. In this range, the electrification current is around 50 pA. For higher velocities of up to 150 mm/s, the current is at the level of 1200 pA. The time–frequency characteristic using short-time Fourier transform shows no temporal changes in the frequency spectrum. The dependence of electrification on shuttle speed was calculated and it can be approximated with a second order polynomial model with the determination coefficient higher than 0.9. The advantage of the sensor is the ability to measure electrification phenomena without the necessity of having rotating electrodes or having a large volume of flowing liquids.

USING SHORT-TIME FOURIER TRANSFORM AND WAVELET PACKET TRANSFORM TO ATTENUATE NOISE FROM HEART SOUND SIGNAL FOR WEARABLE E-HEALTHCARE DEVICE

2015 ◽  
Vol 15 (01) ◽  
pp. 1550009 ◽  
Author(s):  
KEHAN ZENG ◽  
ZHEN TAN ◽  
MINGCHUI DONG
Keyword(s):  
Fourier Transform ◽  
Heart Sound ◽  
Wavelet Packet ◽  
Detection Algorithm ◽  
Wavelet Packet Transform ◽  
Short Time Fourier Transform ◽  
Threshold Method ◽  
Time Frequency ◽  
Tree Leaf ◽  
Short Time

A soft-computing method attenuating noise from heart sound (HS) signal for wearable e-healthcare device is proposed. The HS signal is decomposed by third-level wavelet packet transform (WPT). An automatic HS cycle detection algorithm is applied to find HS cycles in the (3, 0) leaf signal of WPT tree. Based on the quasi-cyclic feature of HS, short-time Fourier transform is implemented for cycles of each WPT tree leaf signal to decompose each cycle into time-frequency fragments which are called particles. Furthermore, the novel cuboid method is proposed to identify constituents of HS and noise from such generated particles. The particles representing HS are then retained and merged into noise-quasi-free WPT tree leaf signals. Eventually the inverse WPT (IWPT) is employed to build the noise-quasi-free HS signal. The method is assessed using mean square error (MSE) and compared with wavelet multi-threshold method (WMTM) and Tang's method. The experimental results show that the proposed method not only filters HS signal effectively but also well retains its pathological information.

Destruction of Actin Filaments by Osmium Tetroxide

1977 ◽  
Vol 35 ◽  
pp. 466-467
Author(s):  
P. Maupin-Szamier ◽  
T. D. Pollard
Keyword(s):  
Actin Filaments ◽  
Time Course ◽  
Osmium Tetroxide ◽  
Rabbit Muscle ◽  
Muscle Actin ◽  
Sodium Phosphate Buffer ◽  
Transmission Electron ◽  
The Difference ◽  
Rates Of Decay ◽  
Short Time

We have studied the destruction of rabbit muscle actin filaments by osmium tetroxide (OSO4) to develop methods which will preserve the structure of actin filaments during preparation for transmission electron microscopy.Negatively stained F-actin, which appears as smooth, gently curved filaments in control samples (Fig. 1a), acquire an angular, distorted profile and break into progressively shorter pieces after exposure to OSO4 (Fig. 1b,c). We followed the time course of the reaction with viscometry since it is a simple, quantitative method to assess filament integrity. The difference in rates of decay in viscosity of polymerized actin solutions after the addition of four concentrations of OSO4 is illustrated in Fig. 2. Viscometry indicated that the rate of actin filament destruction is also dependent upon temperature, buffer type, buffer concentration, and pH, and requires the continued presence of OSO4. The conditions most favorable to filament preservation are fixation in a low concentration of OSO4 for a short time at 0°C in 100mM sodium phosphate buffer, pH 6.0.

Tem analysis of multiple-energy arsenic implanted and Rta'd silicon

1987 ◽  
Vol 45 ◽  
pp. 246-247
Author(s):  
R.A. Herring
Keyword(s):  
Device Fabrication ◽  
High Concentration ◽  
Tem Analysis ◽  
Defect Clusters ◽  
High Fluences ◽  
Small Defect ◽  
Before And After ◽  
The Matrix ◽  
The Difference ◽  
Factor Type

Rapid thermal annealing (RTA) of ion-implanted Si is important for device fabrication. The defect structures of 2.5, 4.0, and 6.0 MeV As-implanted silicon irradiated to fluences of 2E14, 4E14, and 6E14, respectively, have been analyzed by electron diffraction both before and after RTA at 1100°C for 10 seconds. At such high fluences and energies the implanted As ions change the Si from crystalline to amorphous. Three distinct amorphous regions emerge due to the three implantation energies used (Fig. 1). The amorphous regions are separated from each other by crystalline Si (marked L1, L2, and L3 in Fig. 1) which contains a high concentration of small defect clusters. The small defect clusters were similar to what had been determined earlier as being amorphous zones since their contrast was principally of the structure-factor type that arises due to the difference in extinction distance between the matrix and damage regions.

Development of Prolonged Delivery of Tramadol and Dissolution Translation by Statistical Data Treatment

2011 ◽  
Vol 4 (1) ◽  
pp. 1331-1337
Author(s):  
P B Parejiya ◽  
B S Barot ◽  
P K Shelat
Keyword(s):  
Drug Release ◽  
Study Data ◽  
Stability Study ◽  
Dissolution Time ◽  
Matrix Tablet ◽  
Burst Effect ◽  
The Matrix ◽  
The Mean ◽  
The Difference ◽  
Dissolution Efficiency

The present study was carried out to fabricate a prolonged design for tramadol using Kollidon SR (Polyvinyl acetate and povidone based matrix retarding polymer). Matrix tablet formulations were prepared by direct compression of Kollidon SR of a varying proportion with a fixed percentage of tramadol. Tablets containing a 1:0.5 (Drug: Kollidon SR) ratio exhibited a rapid rate of drug release with an initial burst effect. Incorporation of more Kollidon SR in the matrix tablet extended the release of drug with subsequent minimization of the burst effect as confirmed by the mean dissolution time, dissolution efficiency and f2 value. Among the formulation batches, a direct relationship was obtained between release rate and the percentage of Kollidon SR used. The formulation showed close resemblance to the commercial product Contramal and compliance with USP specification. The results were explored and explained by the difference of micromeritic characteristics of the polymers and blend of drug with excipients. Insignificant effects of various factors, e.g. pH of dissolution media, ionic strength, speed of paddle were found on the drug release from Kollidon-SR matrix. The formulation followed the Higuchi kinetic model of drug release. Stability study data indicated stable character of Batch T6 after short-term stability study.

scholarly journals Strain Sensitivity Enhancement of Broadband Ultrasonic Signals in Plates Using Spectral Phase Filtering

2021 ◽  
Vol 11 (6) ◽  
pp. 2582
Author(s):  
Lucas M. Martinho ◽  
Alan C. Kubrusly ◽  
Nicolás Pérez ◽  
Jean Pierre von der Weid
Keyword(s):  
Fourier Transform ◽  
Guided Waves ◽  
Strain Level ◽  
Energy Concentration ◽  
Short Time Fourier Transform ◽  
Time Frequency ◽  
Frequency Representation ◽  
The Fourier Transform ◽  
Short Time ◽  
Sensitivity Gain

The focused signal obtained by the time-reversal or the cross-correlation techniques of ultrasonic guided waves in plates changes when the medium is subject to strain, which can be used to monitor the medium strain level. In this paper, the sensitivity to strain of cross-correlated signals is enhanced by a post-processing filtering procedure aiming to preserve only strain-sensitive spectrum components. Two different strategies were adopted, based on the phase of either the Fourier transform or the short-time Fourier transform. Both use prior knowledge of the system impulse response at some strain level. The technique was evaluated in an aluminum plate, effectively providing up to twice higher sensitivity to strain. The sensitivity increase depends on a phase threshold parameter used in the filtering process. Its performance was assessed based on the sensitivity gain, the loss of energy concentration capability, and the value of the foreknown strain. Signals synthesized with the time–frequency representation, through the short-time Fourier transform, provided a better tradeoff between sensitivity gain and loss of energy concentration.

scholarly journals Detection of Ventricular Fibrillation Based on Ballistocardiography by Constructing an Effective Feature Set

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3524
Author(s):  
Rongru Wan ◽  
Yanqi Huang ◽  
Xiaomei Wu
Keyword(s):  
Ventricular Fibrillation ◽  
Cross Validation ◽  
Rhythmic Activity ◽  
Detection Algorithm ◽  
Motion Artifacts ◽  
Cardiac Monitoring ◽  
Mechanical Activity ◽  
Time Frequency ◽  
S Transform ◽  
Fatal Arrhythmia

Ventricular fibrillation (VF) is a type of fatal arrhythmia that can cause sudden death within minutes. The study of a VF detection algorithm has important clinical significance. This study aimed to develop an algorithm for the automatic detection of VF based on the acquisition of cardiac mechanical activity-related signals, namely ballistocardiography (BCG), by non-contact sensors. BCG signals, including VF, sinus rhythm, and motion artifacts, were collected through electric defibrillation experiments in pigs. Through autocorrelation and S transform, the time-frequency graph with obvious information of cardiac rhythmic activity was obtained, and a feature set of 13 elements was constructed for each 7 s segment after statistical analysis and hierarchical clustering. Then, the random forest classifier was used to classify VF and non-VF, and two paradigms of intra-patient and inter-patient were used to evaluate the performance. The results showed that the sensitivity and specificity were 0.965 and 0.958 under 10-fold cross-validation, and they were 0.947 and 0.946 under leave-one-subject-out cross-validation. In conclusion, the proposed algorithm combining feature extraction and machine learning can effectively detect VF in BCG, laying a foundation for the development of long-term self-cardiac monitoring at home and a VF real-time detection and alarm system.

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