Results 241 to 250 of about 5,545,221 (295)

An empirical signal separation algorithm for multicomponent signals based on linear time-frequency analysis

Mechanical systems and signal processing, 2019
The empirical mode decomposition (EMD) is a powerful tool for non-stationary signal analysis. It has been used successfully for non-stationary signals separation and time-frequency representation.
Lin Li, Lin Li, H. Cai, Qingtang Jiang, H. Ji   +4 more
semanticscholar   +1 more source

Multicomponent analysis of electrochemical signals in the wavelet domain

Talanta, 2003
Successful applications of multivariate calibration in the field of electrochemistry have been recently reported, using various approaches such as multilinear regression (MLR), continuum regression, partial least squares regression (PLS) and artificial neural networks (ANN).
COCCHI, Marina, J. L. Hidalgo Hidalgo De Cisneros, I. Naranjo Rodruguez, J. M. Palacios Santnder, SEEBER, Renato, ULRICI, Alessandro   +5 more
openaire   +2 more sources

Self-Matching Chirplet Extraction Transform: A Novel Tool for Dense Multicomponent Signals Analysis and Machinery Fault Diagnosis

IEEE Sensors Journal
This study introduces a novel time–frequency (TF) analysis methodology, designated as the self-matching chirplet extraction transform (SMCET). This innovative technique is specifically crafted for the analysis of nonstationary signals characterized by ...
Hong-Yi Wu, Yong Lv, Rui Yuan, Bowen Li, Xingkai Yang, Weihang Zhu   +5 more
semanticscholar   +1 more source

Separation of Multicomponent Chirp Signals Using Morphological Component Analysis and Fractional Fourier Transform

IEEE Geoscience and Remote Sensing Letters, 2020
A chirp signal is a large-bandwidth signal which is widely used in engineering. In many applications, it is necessary to decompose a mixed chirp signal into its components.
Z. Shao, Jiangheng He, S. Feng
semanticscholar   +1 more source

What is a multicomponent signal?

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992
Multicomponent signals, which produce delineated concentrations in the time-frequency plane, are common in nature, human speech being a prime example. An explanation of what types of signals are multicomponent is presented. The idea is generalized to time-scale. The recognition of multicomponent signals is considered. >
openaire   +1 more source

Detection and classification of multicomponent signals

[1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers, 2002
The multicomponent nature of many naturally occurring signals, such as speech, is exploited to provide a new means of detection and classification. A component of a multicomponent signal is defined in terms of the local bandwidth about the instantaneous frequency in the time-frequency distribution.
A.B. Fineberg, R.J. Mammone
openaire   +1 more source

An Algorithm for Parameter Estimation of Multicomponent Chirp Signals

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
This paper presents an algorithm for estimating the parameters of multicomponent chirp signals. The estimator is based on the cubic phase function (CPF), which is efficient to estimate the parameters of monocomponent polynomial phase signals (PPS) with order is less than or equal to 3.
Jianyu Yang, Pu Wang, Jintao Xiong
openaire   +1 more source

On the instantaneous frequencies of multicomponent AM-FM signals

IEEE Signal Processing Letters, 1998
We study the instantaneous frequencies (IFs) of multicomponent AM-FM signals by extending the work on the two-component case by Loughlin and Tacer (see ibid.,, vol. 4, no.5, p.123-25, 1997) to the more general M-component case. A novel necessary and sufficient condition for the valid interpretation of the IF as a nonnegatively weighted average of the ...
Dong Wei 0003, Alan C. Bovik
openaire   +1 more source

Refinement in the estimation of multicomponent polynomial-phase signals

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
In this paper, we consider precise parameter estimation of multicomponent polynomial-phase signals (mc-PPSs). Two estimation refinement methods are proposed and both are initialized by coarse estimates provided by any technique for the mc-PPS estimation.
Slobodan Djukanovic, Marko Simeunovic, Igor Djurovic   +2 more
openaire   +1 more source

Multicomponent Signal Decomposition Using Morphological Operations

2018 IEEE 23rd International Conference on Digital Signal Processing (DSP), 2018
In this paper, we consider the component decomposition (CD) problem in a non-stationary multicomponent signal (MCS). A new technique by manipulation of morphological operations is developed to solve the CD problem. The spectrogram of the MCS is first converted into a binary image.
Huiping Zhuang, Beom-Seok Oh, Dongyun Lin, Kar-Ann Toh, Zhiping Lin 0001   +4 more
openaire   +1 more source