Detection of Chirp Signal with Time-Varying Amplitude Based on FRFT

2014 ◽  
Vol 989-994 ◽  
pp. 4046-4049
Author(s):  
Yan Jun Wu ◽  
Ren Long Li ◽  
Xiao Wang
Keyword(s):  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Modulation Frequency ◽  
Gaussian Function ◽  
Angular Frequency ◽  
Estimation Methods ◽  
Time Varying ◽  
Chirp Signal ◽  
The Mean ◽  
General Method

The general method time-varying amplitude linear FM signal parameter estimation, the proposed parameter fractional Fourier transform for time-varying estimates of the magnitude of the chirp signal, and the related issues of a more in-depth research. Study the time-varying amplitude of the initial phase chirp signal, the initial angular frequency, modulation frequency and amplitude information extraction and estimation methods, and the magnitude of the Gaussian function varies with the magnitude of random variation and chirp signal for the object properties (parameters on parameter estimation estimate the mean square error) were simulated.

Detection and Parameter Estimation for Chirp Signal Based on Fractional Fourier Transform

2014 ◽  
Vol 599-601 ◽  
pp. 1474-1477
Author(s):  
Xin Chen ◽  
Min Tao ◽  
Tian Tang Pan ◽  
Yan Li
Keyword(s):  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Estimation Algorithm ◽  
Wave Parameter ◽  
Estimation Accuracy ◽  
Radar Signal ◽  
Chirp Signal ◽  
Computation Complexity ◽  
Maximum Value ◽  
Radar Echo

The Chirp signal has been used widely in radar signal, radar echo wave can established to be Chirp model. The estimation of radar echo wave parameter is a important task in radar signal processing. In this paper, we introduced three theories and algorithms of detection and estimation of Chirp signal: 2D peak searching algorithm, two steps searching of maximum value algorithm and pre-estimation algorithm firstly. The parameter estimation precision and computation complexity in low SNR was simulated for these three algorithms. The final simulation indicate that the two steps searching algorithm of maximum value take on nice estimation accuracy and low computation complexity in contrast.

Analysis of Parameter Estimation Using Pei Algorithm of FRFT

2014 ◽  
Vol 577 ◽  
pp. 758-761
Author(s):  
Bing Deng
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Estimation Accuracy ◽  
Chirp Signal ◽  
Factors Influencing

Parameter estimation of chirp signal is analyzed using Pei algorithm of FRFT (Fractional Fourier Transform). Firstly, the model of parameter estimation has been made. Secondly, the factors influencing the estimation accuracy have been analyzed. Finally, the simulation has been made to verify the conclusions.

A Novel Scheme for Time Delay Estimation in the Fractional Fourier Transform Domain

2013 ◽  
Vol 385-386 ◽  
pp. 1425-1428
Author(s):  
Xue Mei Li
Keyword(s):  
Time Delay ◽  
Fractional Fourier Transform ◽  
Estimation Method ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Estimation Methods ◽  
Fourier Domain ◽  
Transform Domain ◽  
Chirp Signal ◽  
Fourier Transform Domain

A time delay estimator based on the fractional bispectrum is proposed; and it is suitable for the chirp signal. The proposed time delay estimation technique can outperform the conventional time delay estimation methods associated with the bispectrum in the Fourier domain under the correlated Gaussian noises at lower SNR. Simulation results demonstrate the validity of this estimation method.

Detection and Parameter Estimation of Chirp Signal Based on Time-Frequency Analysis

2014 ◽  
Vol 989-994 ◽  
pp. 3989-3992
Author(s):  
Guang Zhi Wu ◽  
Gang Fu ◽  
Yan Jun Wu
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Chirp Signal ◽  
Wigner Transform ◽  
Time Frequency ◽  
The Relationship ◽  
Generic Time ◽  
Time Frequency Distribution ◽  
Better Than

Based on the relationship between the Radon-Wigner transform and fractional Fourier transform and the time frequency distribution, using the property that Radon-Wigner transform has better performance in time and frequency domain, detection and parameter estimation of Chirp signal have been done by Radon-Wigner transform or fractiona1 Fourier transform. The theoretica1 analysis and simulation prove that two techniques are better than generic time-frequency transform, such as Wigner-Ville transform.

scholarly journals A Bimodal Extension of the Exponential Distribution with Applications in Risk Theory

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 679
Author(s):  
Jimmy Reyes ◽  
Emilio Gómez-Déniz ◽  
Héctor W. Gómez ◽  
Enrique Calderín-Ojeda
Keyword(s):  
Exponential Distribution ◽  
Hazard Rate ◽  
Rate Function ◽  
Estimation Methods ◽  
Inverse Gaussian ◽  
New Family ◽  
Tail Distribution ◽  
Zero Values ◽  
The Mean ◽  
Positive Support

There are some generalizations of the classical exponential distribution in the statistical literature that have proven to be helpful in numerous scenarios. Some of these distributions are the families of distributions that were proposed by Marshall and Olkin and Gupta. The disadvantage of these models is the impossibility of fitting data of a bimodal nature of incorporating covariates in the model in a simple way. Some empirical datasets with positive support, such as losses in insurance portfolios, show an excess of zero values and bimodality. For these cases, classical distributions, such as exponential, gamma, Weibull, or inverse Gaussian, to name a few, are unable to explain data of this nature. This paper attempts to fill this gap in the literature by introducing a family of distributions that can be unimodal or bimodal and nests the exponential distribution. Some of its more relevant properties, including moments, kurtosis, Fisher’s asymmetric coefficient, and several estimation methods, are illustrated. Different results that are related to finance and insurance, such as hazard rate function, limited expected value, and the integrated tail distribution, among other measures, are derived. Because of the simplicity of the mean of this distribution, a regression model is also derived. Finally, examples that are based on actuarial data are used to compare this new family with the exponential distribution.

scholarly journals Statistical Tests of Symbolic Dynamics

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 817
Author(s):  
Fernando López ◽  
Mariano Matilla-García ◽  
Jesús Mur ◽  
Manuel Ruiz Marín
Keyword(s):  
Monte Carlo ◽  
Symbolic Dynamics ◽  
Null Hypothesis ◽  
Statistical Tests ◽  
General Applicability ◽  
Monte Carlo Experiments ◽  
The Mean ◽  
Theoretical Application ◽  
New Statistics ◽  
General Method

A novel general method for constructing nonparametric hypotheses tests based on the field of symbolic analysis is introduced in this paper. Several existing tests based on symbolic entropy that have been used for testing central hypotheses in several branches of science (particularly in economics and statistics) are particular cases of this general approach. This family of symbolic tests uses few assumptions, which increases the general applicability of any symbolic-based test. Additionally, as a theoretical application of this method, we construct and put forward four new statistics to test for the null hypothesis of spatiotemporal independence. There are very few tests in the specialized literature in this regard. The new tests were evaluated with the mean of several Monte Carlo experiments. The results highlight the outstanding performance of the proposed test.

scholarly journals Potential of spectroscopic analyses for non-destructive estimation of tea quality-related metabolites in fresh new leaves

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroto Yamashita ◽  
Rei Sonobe ◽  
Yuhei Hirono ◽  
Akio Morita ◽  
Takashi Ikka
Keyword(s):  
Short Wave ◽  
Machine Learning Algorithms ◽  
Estimation Methods ◽  
Chemical Information ◽  
Tea Quality ◽  
The Mean ◽  
Processing Techniques ◽  
Spectral Patterns ◽  
Physical And Chemical ◽  
Non Destructive

AbstractSpectroscopic sensing provides physical and chemical information in a non-destructive and rapid manner. To develop non-destructive estimation methods of tea quality-related metabolites in fresh leaves, we estimated the contents of free amino acids, catechins, and caffeine in fresh tea leaves using visible to short-wave infrared hyperspectral reflectance data and machine learning algorithms. We acquired these data from approximately 200 new leaves with various status and then constructed the regression model in the combination of six spectral patterns with pre-processing and five algorithms. In most phenotypes, the combination of de-trending pre-processing and Cubist algorithms was robustly selected as the best combination in each round over 100 repetitions that were evaluated based on the ratio of performance to deviation (RPD) values. The mean RPD values were ranged from 1.1 to 2.7 and most of them were above the acceptable or accurate threshold (RPD = 1.4 or 2.0, respectively). Data-based sensitivity analysis identified the important hyperspectral regions around 1500 and 2000 nm. Present spectroscopic approaches indicate that most tea quality-related metabolites can be estimated non-destructively, and pre-processing techniques help to improve its accuracy.

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