Recognition of dynamically varying PRI modulation via deep learning and recurrence plot

Recognition of pulse repetition interval(PRI)modulation is a fundamental task in the interpretation of radar intentions.However,the existing PRI modulation recognition methods mainly focus on single-label classification of PRI sequences.The prerequisite for the effectiveness of these methods is that the PRI sequences are perfectly divided according to different modulation types before identification,while the actual situation is that radar pulses reach the receiver continuously,and there is no completely reliable method to achieve this division in the case of non-cooperative reception.Based on the above actual needs,this paper implements an algorithm based on the recurrence plot technique and the multi-target detection model,which does not need to divide the PRI sequence in advance.Compared with the sliding window method,it can more effectively realize the recognition of the dynamically varying PRI mo dulation.

Classification of Short Time Series in Early Parkinson’s Disease With Deep Learning of Fuzzy Recurrence Plots

There are many techniques using sensors and wearable devices for detecting and monitoring patients with Parkinson’s disease(PD).A recent development is the utilization of human interaction with computer keyboards for analyzing and identifying motor signs in the early stages of the disease.Current designs for classification of time series of computer-key hold durations recorded from healthy control and PD subjects require the time series of length to be considerably long.With an attempt to avoid discomfort to participants in performing long physical tasks for data recording,this paper introduces the use of fuzzy recurrence plots of very short time series as input data for the machine training and classification with long short-term memory(LSTM)neural networks.Being an original approach that is able to both significantly increase the feature dimensions and provides the property of deterministic dynamical systems of very short time series for information processing carried out by an LSTM layer architecture,fuzzy recurrence plots provide promising results and outperform the direct input of the time series for the classification of healthy control and early PD subjects.

Comparison study of typical algorithms for reconstructing time series from the recurrence plot of dynamical systems

The three most widely used methods for reconstructing the underlying time series via the recurrence plots （RPs） of a dynamical system are compared with each other in this paper. We aim to reconstruct a toy series, a periodical series, a random series, and a chaotic series to compare the effectiveness of the most widely used typical methods in terms of signal correlation analysis. The application of the most effective algorithm to the typical chaotic Lorenz system verifies the correctness of such an effective algorithm. It is verified that, based on the unthresholded RPs, one can reconstruct the original attractor by choosing different RP thresholds based on the Hirata algorithm. It is shown that, in real applications, it is possible to reconstruct the underlying dynamics by using quite little information from observations of real dynamical systems. Moreover, rules of the threshold chosen in the algorithm are also suggested.

Middle ear reconstruction estimated by recurrence plot technique

Middle ear surgery techniques have enabled to improve hearing destroyed by a disease. Despite huge improvement in instrumentation and techniques the results of hearing improvement surgery are still difficult to predict. This paper presents the results of vibrations measurements in a human middle ear obtained at the Medical University of Lublin. Vibrations of the stapes in the case of the intact ossicular chain, after cement incus rebuilding and incus interpositions are compared each other. In this aim a new approach of ossicles vibrations observation is introduced in order to complete information obtained from classical approach which bases on the transfer function. Measurements of ossicular chain vibrations are performed on fresh human temporal bone specimen using the laser doppler vibrometer. Next, after classical research, the extended analysis with the recurrence plots technique is performed.

Nonlinear dynamics in Divisia monetary aggregates:an application of recurrence quantification analysis

We construct recurrence plots(RPs)and conduct recurrence quantification analysis(RQA)to investigate the dynamic properties of the new Center for Financial Stability(CFS)Divisia monetary aggregates for the United States.In this study,we use the lat-est vintage of Divisia aggregates,maintained within CFS.We use monthly data,from January 1967 to December 2020,which is a sample period that includes the extreme economic events of the 2007–2009 global financial crisis.We then make comparisons between narrow and broad Divisia money measures and find evidence of a nonlinear but reserved possible chaotic explanation of their origin.The application of RPs to broad Divisia monetary aggregates encompasses an additional drift structure around the global financial crisis in 2008.Applying the moving window RQA to the growth rates of narrow and broad Divisia monetary aggregates,we identify periods of changes in data-generating processes and associate such changes to monetary policy regimes and financial innovations that occurred during those times.

Study on Chaotic Characteristics of the Friction Process between High Hardness Alloy Steel and Cemented Carbide under C60 Nanoparticle Fluid Lubrication

Friction and wear phenomenon is a complex nonlinear system,and it is also a significant problem in the process of metal cutting.In order to systematically analyze the friction and wear process of tool material-workpiece material friction pair in the cutting process of high hardness alloy steel under different lubrication conditions,the chaotic characteristics of friction process between high hardness alloy steel and cemented carbide under the lubrication C60 nano-particles fluid are studied based on the chaos theory.Firstly,the friction and wear experiments of the friction pair between high hardness alloy steel and cemented carbide tool are carried out based on the ring-block friction and wear tester,and the results of friction force signal in time domain and wear width are obtained.Then,the friction signals in time domain are processed and transformed based on phase space reconstruction and recurrence plot theory,and the recurrence plots of different experimental groups under different lubrication conditions are generated.The evolution law of recurrence plot is further observed and studied,and the recursive quantitative index is analyzed.Finally,the cutting experiments of tool wear are carried out.The results show that the proposed method can intuitively and accurately reveal the wear evolution process and the wear feature identification law of the tool material-high hardness alloy steel pair under different lubrication conditions.Meanwhile,it is found that when the concentration of C60 nanoparticles is 200∼300 ppm,the stability of the friction pair system is best.The proposed method can provide a strategy for wear prediction in cutting process,and provide a theoretical basis and technical support for antifriction lubrication methods in practical cutting applications.

Recurrence Quantification Analysis of Rough Surfaces Applied to Optical and Speckle Profiles

In this paper, Recurrence Quantification Analysis (RQA) is set as a practical nonlinear data tool to establish and compare surface roughness (Ra) through percentage parameters of a dynamical system: Recurrence (%REC), Determinism (%DET) and Laminarity (%LAM). Variations in surface roughness of different machining procedures from a typical metallic casting comparator are obtained from scattering intensity of a laser beam and expressed as changes in the statistics of speckle patterns and profiles optical properties. The application of the analysis (RQA) by Recurrence Plots (RPs), allowed to distinguish between machining procedures, highlighting features that other methods are unable to detect.

Multi-scale analysis of flow structures in fluidized beds with immersed tubes

Multi-scale analysis and non-linear analysis were combined to investigate the hydrodynamics of fluidized beds with and without horizontal tubes. Pressure fluctuations were measured and analyzed employing discrete wavelet analysis, recurrence plot analysis, and recurrence quantification analysis. A systematic procedure was followed to determine wavelet parameters. At low gas velocities, the energy of macro-structures reduces with the addition of the first tube and then increases with the addition of a second tube. However, there is no notable difference at high gas velocities. Determinism is high for the bed without tubes, which can be attributed to the periodic behavior of bubbles. Determinism decreases with the addition of tubes because the breakage of bubbles results in less periodic behavior. The three methods of analysis used in this study captured the effects of immersed tubes on the hydrodynamics of fluidized beds. Recurrence quantitative analysis was found to be a powerful and easy-to-use method that can capture the nonlinear characteristics of fluidized beds much more quickly than conventional methods of nonlinear analysis. This method can thus be effectively used for the online monitoring of hydrodynamic changes in fluidized beds.